Stem Research for Students [1, 1 ed.] 9781465289612

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Stem Research for Students [1, 1 ed.]
 9781465289612

Table of contents :
Contents
Preface
About the Authors
PART ONE - Engaging in Experimentation
CHAPTER 1 - Conducting Experiments
CHAPTER 2 - Refining Experiments
CHAPTER 3 - Analyzing an Experimental Design
CHAPTER 4 - Experimenting Precisely
PART TWO - Analyzing and Interpreting Experimental Data
CHAPTER 5 - Selecting and Calculating Descriptive Statistics
CHAPTER 6 - Selecting and Constructing Graphs
CHAPTER 7 - Making Sense of Experiments
PART THREE - Engaging in Engineering Design
CHAPTER 8 - Designing, Building, and Testing a Model
Introduction
Designing a Device to Solve a Problem
Engineering Design Process
Using Brainstorming and Argumentation Effectively
Using a Rubric to Assess a Design
Focusing on Design
Assessing and Improving a Design Brief
References
APPENDIX A - Correlations With Nationwide Learning Standards
Next Generation Science Standards
Common Core Standards
ISTE Standards - Students
APPENDIX B - Using Safe Procedures
Chemicals
Electricity, Radiation, and Projectiles
Mold, Bacteria, and Other Microbes
Invertebrates, Non-Human Vertebrates, and Human Subjects
Environmental Field Studies
References
APPENDIX C - Definitions of Key Terms
Index

Citation preview

Disclaimer Adult supervision is required when students are working on science activities and projects. Use proper equipment (gloves, forceps, safety glasses, etc.) and take other safety precautions such as tying up loose hair and clothing and washing hands when the work is done. Use extra care with chemicals, dry ice, boiling water, or any heating elements. Hazardous chemicals and live cultures (organisms) must be handled and disposed of according to appropriate directions from teachers. Follow science fair's rules and regulations and the standard scientific practices and procedures required by schools. No responsibility is implied or taken for anyone who sustains injuries as a result of using the materials or ideas, or performing the procedures described in this book.

Cover image © Shutterstock, Inc. Box image ©Vador/Shutterstock.com My Workspace lightbulb ©VLADGRIN/Shutterstock.com Front Matter and Appendix Opener: ©Sergey Nivens/Shutterstock.com Part One Opener: ©WDG Photo/Shutterstock.com Part Two Opener: ©gopixa/Shutterstock.com Part Three Opener: ©STILLFX/Shutterstock.com

Kendall Hunt pub l ishing

company

www.kendallhunt.com Send all inquiries to: 4050 Westmark Drive Dubuque,IA 52004-1840 Copyright© 2016 by Kendall Hunt Publishing Company ISBN 978-1-4652-7368-0

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the copyright owner. Printed in the United States of America

Contents Preface .. . .. . .. . .. . .. .............. . ....... . . .. . .. .. .. . .. . .................. v About the Authors .......................................................... .xi

PART ONE: ENGAGING IN EXPERIMENTATION .............................. . 1

Chapter 1-Conducting Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Chapter 2-Refining Experiments. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Chapter 3-Analyzing an Experimental Design .. . .............. . .. . . . .... . ......... 59 Chapter 4--Experimenting Precisely .. .. .... . . . .............. . .. . . . .... . .... . .... 89

PART TWO: ANALYZING AND INTERPRETING EXPERIMENTAL DATA ............119

Chapter 5-Selecting and Calculating Descriptive Statistics .......................... 121 Chapter 6--Selecting and Constructing Graphs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157 Chapter 7-Making Sense of Experiments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193

PART THREE: ENGAGING IN ENGINEERING DESIGN ........................ .227

Chapter 8-Designing, Building, and Testing Models ............ . .. . . . ............. 229

APPENDIX ...... . .................................................. .255

A-Correlations With Nationwide Leaming Standards .... . ...... . .. . . . .... . .... . ... 256 B-Using Safe Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261 C-Definitions of Key Terms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 265

INDEX . ................................................................... 273

iii

l?reface Through centuries of investigations, STEM professionals have developed the current body of scientific, technical, engineering, and mathematical knowledge. This knowledge provides a foundation for understanding the natural world and for launching investigations which expand our understanding. STEM Research for Students, Volume 1 enables students to understand scientific experimentation, engineering design, and mathematical relationships. We live in an increasingly complex and interconnected world where knowledge grows at an exponential rate. Because of the extensive knowledge which exists, and the rate at which it is expanding, it is impossible for a person to learn all the ideas in a discipline. To prepare students for the society in which they will live and work, nationwide standards have been written to guide development, implementation, and assessment of educational programs at all levels. Each chapter of this book is correlated with nationwide standards developed for science and engineering, mathematics, reading and writing in technical subjects, and the use of digital technology. These standards include the: ►

Next Generation Science Standards;



Common Core State Standards for Mathematics;



Common Core State Standards for English Language & Literacy in History/Social Studies, Science, and Technical Subjects; and



International Standards for Technology in Education Standards for Students.

Many states have adopted these standards, and others have used them as a reference for refining and updating their statewide educational standards.

V

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Preface

STEM DISCIPLINES AND CONNECTIONS Every school discipline is important in a person's education-the arts, sciences, humanities, and physical education. Although this book is focused on STEM, cross-disciplinary applications occur throughout. STEM is an acronym which refers to science, technology, engineering, and mathematics. Each of the STEM disciplines has a different goal: ►

Science seeks to explain how the natural world works;



Technology and engineering seek to modify the world to meet human needs and wants, with engineering being more analytical and scientifically based;



Mathematics seeks to describe, analyze, and interpret patterns and relationships (Salinger, 2008).

Despite these differing goals, the STEM disciplines are intricately connected and interdependent. All of the disciplines use digital technology tools-including advanced modeling and simulation techniques-to enhance productivity, collaboration, and creativity. Technical reading and writing skills are essential for understanding the existing body of STEM knowledge and for communicating the results of scientific, engineering, and mathematical projects. Many chapters of this book end with a section entitled "Exploring STEM Connections." In this section, the core chapter investigation is used as a prompt for exploring connections to multiple scientific disciplines, technology, engineering, and mathematics.

IDEAS, DOMAINS, AND PRACTICES The Next Generation Science Standards identifies core scientific ideas which have the greatest explanatory power and can serve as a foundation for continued learning. These scientific ideas are grouped into four disciplines-the physical sciences, life sciences, Earth and space sciences, and engineering. In addition, cross-cutting concepts, such as patterns and systems, are identified; these cross-cutting concepts transcend all STEM disciplines. In the Common Core State Standards for Mathematics the most important mathematical concepts are grouped into domains. Examples include ratio and proportional relationships, geometry, algebra, and statistics and probability. In this book there will be opportunities to apply mathematical concepts to chapter investigations. When STEM professionals conduct experiments, design a product, or solve a mathematical problem they utilize certain practices. To use a practice requires a set of knowledge about the practice.

Preface

vii

This book focuses on major practices used by scientists, engineers, and mathematicians; these practices are summarized below: STEM PRACTICES Scientific and Engineering Practices ►

Asking questions and defining problems



Developing and using models



Planning and carrying out investigations



Analyzing and interpreting data

► Using mathematics and computational

th inking ►

Constructing explanations and designing solutions

Mathematical Practices ►

Make sense of problems and persevere in solving them



Reason abstractly and quantitatively

► Construct viable arguments and

crit ique the reasoning of others ► Model w ith mathematics ►

Use appropriate tools strategically



Attend to precision

► Engaging in argument from evidence

► Look for and make use of structure



► Look for and express regularity in

Obtaining, eva luating, and commun icating information

repeated reasoning

Credit: National Governors Association Center for Best Practices, 2010, Mathematics, pp. 6-8; NGSS Lead States, 2013, Volume 1, p. xx.

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Preface

BUILDING A STRONG FOUNDATION The first volume of STEM Research for Students provides a strong foundation in the STEM practices and enables students to understand scientific experimentation, engineering design, and mathematical relationships. This volume is divided into three parts: ►

Part One: Engaging in Experimentation. Practices used in designing an experiment (testable question, hypothesis, variables, control group, and repeated trials) and writing precise and safe experimental procedures.



Part Two: Analyzing and Interpreting Experimental Data. Practices involved in constructing data tables, selecting and calculating descriptive statistics, selecting and constructing graphs, analyzing and summarizing results, making sense of an experiment, and communicating findings.



Part Three: Engaging in Engineering Design. Practices used in creating a device to meet a need including understanding the problem, using the engineering design process, applying brainstorming and argumentation effectively, and writing a design brief.

ASSESSING PROGRESS This book includes two types of assessment-practice opportunities for targeted STEM practices and tools for assessing and improving products. More than fifteen practice sets are provided in Volume One. In each chapter, the practice sets are clearly labeled. Each tool-a checklist or rubric-summarizes expectations for a specific product and is designed to guide product development. Self and peer assessments are encouraged, and argumentation skills are used to give feedback. Suggested point values are provided for each component of a checklist or rubric. These values reflect the relative importance of various components. Teachers can use a checklist or rubric for either formative or summative assessment, and may modify the criteria or point values to reflect their learning objectives.

Preface

ix

CREATING EFFECTIVE STEM PROJECTS Once students have developed a strong foundation in the STEM practices and applied them to their coursework, they can move to creating knowledge. The second volume of STEM Research for Students guides students through the process of creating effective scientific experiments, engineering designs, and mathematical investigations. This volume is divided into four parts: ►

Part Four: Designing, Conducting, and Reporting Experiments. Practices involved in creating original experiments including brainstorming ideas, analyzing and addressing safety risks, reviewing the scientific literature, conducting a team mini-project within the classroom, and writing a formal scientific paper.



Part Five: Engineering to Meet Human Needs. Essential practices for defining an engineering problem, writing a design brief, using data to improve a design, and creating an original engineering project.



Part Six: Using Mathematics to Detect Patterns and Relationships. Extended opportunities to use algebra and statistics in data analysis and to create an original mathematics project, either in theoretical or applied mathematics.



Part Seven: Exploring STEM Competitions. Practices used by STEM professionals when preparing visual displays, communicating findings, and interacting with peers and judges.

PRIOR PUBLICATIONS Cothron, Giese, and Rezba previously published books and articles on strategies for incorporating scientific research into the K-12 science curriculum. ►

Students and Research: Practical Strategies for Science Classrooms and Competitions (4th ed.) was designed for middle and senior high school teachers. The book has been used nationwide with pre-service and in-service teachers. In addition, Cothron, Giese, and Rezba: (a) taught various workshops, undergraduate, and graduate courses throughout Virginia, (b) made numerous presentations and taught short courses at regional and national meetings of the National Science Teachers Association, and (c) conducted division-wide workshops in multiple states including Florida, Georgia, Indiana, Kentucky, Louisiana, Massachusetts, Michigan, Missouri, New Hampshire, North Carolina, Ohio, Oklahoma, Pennsylvania, Tennessee, Texas, Virginia, Washington, West Virginia, and Washington DC. For their work with Virginia teachers, Cothron, Giese, and Rezba received the Distinguished Service Award from the Virginia Association of Science Teachers.



Science Experiments and Projects for Students (4th ed.) was written for middle and high school students in advanced classes, specialty schools, or research programs outside the regular school day and year.

x Preface ►

Science Experiments by the Hundreds (3rd ed.} was based upon materials typically found in homes and was designed for students, grades 4-8, and their parents. The accompanying teacher's guide focused on teachers of these grade levels.



Articles. Sixteen articles on student research were published in The Science Teacher, Science Scope, Science World, The American Biology Teacher, and Science Activities. Excerpts were included in Biology on a Shoestring and Biology Labs that Work: The Best of How-To-Do-It, which were published by the National Association of Biology Teachers. Cothron, Giese, and Rezba are joint recipients of a Distinguished Achievement Award for Excellence in Educational Journalism from the Education Press Association of America.

REFERENCES Confrey, J., & Krupa, E. E . (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C . Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subj ects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors A ssociation Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_Standards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www. apsva.us/cms/lib2/VA01000586/Centricity/ Domain/29/CTAE_Committee_Report. pdf

About the Autllors

JULIA H. COTHRON, EdD has worked with middle and high school teachers to create effective strategies for developing students' research skills and has served as a mentor to thousands of students and teachers. During her "official career," she taught middle and senior high students, led the Hanover County (VA) Public Schools' science and general secondary programs, served as the Executive Director of the MathScience Innovation Center in Richmond, Virginia, and taught numerous workshops and courses for K-12 teachers. Now retired, she maintains her active involvement with STEM education and serves on the boards of the Virginia Mathematics & Science Coalition, Virginia Association of Science Teachers, and Virginia Junior Academy of Science. Her commitment to student research is based upon her high school research experience, which inspired her to become a science educator.

RONALD N. GIESE, EdD is a professor emeritus of science education at The College of William and Mary; he has worked with both pre-service and in-service teachers to develop strategies for generating research topics and to implement science fairs that maximize student learning. Dr. Giese has served as a consultant to Scholastic Science World, to the Naturalist Center at the National Museum of Natural History, Smithsonian Institution, and to numerous school systems, museums, and science curricular projects. PAULA KLONOWSKI LEACH, EdD is the Director of the Institute for Teaching through Technology and Innovative Practices (ITTIP) at Longwood University. She leads implementation of professional development programs for K-12 science and mathematics teachers which are focused on the integration of engineering, robotics, and emerging technologies in the classroom. Previously, she was the state Science Coordinator at the Virginia Department of Education (VDOE), where she was responsible for coordinating and sustaining statewide science initiatives that supported the Virginia Standards of Learning. Prior to working at VDOE, she was a division science coordinator and a middle school science and special education teacher in Powhatan, Virginia.

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About the Authors

VIRGINIA {GINGER) VIMPENY LEWIS, PhD is an Assistant Professor of Mathematics Education at Longwood University where she teaches mathematics courses for pre-service elementary, middle, and high school teachers. She also provides professional development for practicing teachers focused on improving mathematics instruction. Prior to working at Longwood University, Dr. Lewis was a middle school mathematics teacher in Powhatan, Virginia. Her interest in the use of technology and the integration of science to enhance mathematics instruction began during her middle school teaching career. Dr. Lewis has presented at state and national conferences and serves on the board of the Virginia Council of Teachers of Mathematics. RICHARD J. REZBA, PhD is a professor emeritus of science education at Virginia Commonwealth University where he worked with elementary and secondary teachers to develop instructional strategies in science that are challenging and fun. His research interests include parental involvement, student experimentation, and assessment. Dr. Rezba directed several projects that involved the infusion of various forms of instructional technology into the teaching and learning of science.

T Engaging in Experimentation

CHAPTER 1 Conducting Experiments CHAPTER 2 Refining Experiments CHAPTER 3 Analyzing an Experimental Design CHAPTER 4 Experimenting Precisely

CHAPTER

1 Conducting Experiments

CONTENTS Introduction Learning Objectives Correlations With Nationw ide Standa rds

4 4 4

Conducting an Experiment Box 1-1 Experiment- Rapid Swingers

6 7

Identifying Experimental Components Independent Variable Dependent Variable Controlled Variables Testable Question Constructing a Hypothesis Support for the Hypothesis Box 1-2 Practice-Variables, Questions, and Hypot heses

9 9 9 9 10 10 11 13

Assessing an Experiment Using a Checklist Box 1-3 Checklist-Conduct ing an Experiment Comparing Assessment s Using Argumentation Skills Box 1-4 Practice-Assessing Experiments

15 15 16 18 18 21

Exploring STEM Connections Science Technology and Eng ineering Mathemat ics Box 1-5 STEM Perspective- Rapid Swingers

23 23 23 24 25

References

29 3

4

Part One

Engaging in Experimentation

INTRODUCTION What do describing the life in a forest, identifying the best wood glue, or simply answering the question-"What happens?"-have in common? One answer is that each requires observing and investigating the world, with the intent of developing better explanations of how the world works. Through investigations, scientists have developed our current body of scientific knowledge. Likewise, future investigations will expand our understanding of the natural world. An experiment is a specific type of investigation in which scientists intentionally change, or vary, one factor to determine its impact on another factor. When scientists design experiments they include specific components, each of which serves a specific purpose.

Learning Objectives Specific learning objectives for Chapter 1, Conducting Experiments, include: ►

Ask a testable question to investigate the relationship between variables;



Develop a hypothesis to predict the relationship between variables;



Distinguish between a directional and non-directional hypothesis and describe ways that you can acquire the background needed to make a directional hypothesis;



Identify the independent and dependent variables in an experiment;



Identify the controlled variables in an experiment;



Construct strong operational definitions for the independent, dependent, and controlled variables;



Use data as evidence to evaluate a hypothesis and to answer a scientific question;



Use a checklist to evaluate an experiment so better data can be generated to test a hypothesis and answer a scientific question; and



Use argumentation skills to compare assessments of an experiment.

Correlations With Nationwide Standards In Table 1-1, the core chapter objectives and STEM concepts are correlated with nationwide learning standards. The correlations for "Exploring STEM Connections" are shown in italics. For a synopsis see Appendix A.

Chapter 1

TABLE 1-1

Conducting Experiments

Correlations of Learning Objectives With Nationwide Learning Standards

NEXT GENERATION SCIENCE STANDARDS ►

Scientific & Engineering Practices: Asking questions and defining problems; Planning and carrying out invest igations; Engaging in argument from evidence; Using mathematics and computational thinking; Constructing explanations and designing solutions; Obtaining, evaluating, and communicating information



Cross-Cutting Concepts: Patterns; Cause and effect; Systems and system models; Stability and change



Disciplinary Core Ideas: Motion and stability; Energy; Earth's place in the universe; Earth's systems; Engineering design; Links among engineering, technology, science, and society

COMMON CORE STANDARDS-MATHEMATICS ►

Mathematical Practices: Const ruct viable arguments and crit ique the reasoning of others; Attend to precision



Mathematical Domains: Int erpreting categorical and quantit ative data; Expressions and equations; Quantities

COMMON CORE STANDARDS-LITERACY IN SCIENCE AND TECHNICAL SUBJECTS ►

Reading: Cite textual evidence; Determine key ideas or conclusions; Follow multistep procedure; Det ermine meaning of symbols, key terms, etc.; Read and comprehend text



Writing : Writ e arguments; Conduct short research projects; Gather relevant information; Draw information from informational texts

ISTE STANDARDS-STUDENTS ►

Creativity and innovation : Ident ify trends and forecast possibilities; Use models and simulations



Research and information fluency: Process data and report resu lts; Locate .. . use information from a variety of sources



Critical thinking, problem solving, and decision making: Collect and analyze dat a t o ident ify solut ions and/or make informed decisions



Digital citizenship: Demonst rat e personal responsibility for learning; Advocate and practice safe, legal, and responsible use of technology; Exhibit a positive attitude toward using technology that supports collaboration, learning, and productivity



Technology operation and concepts: Understand and use technology systems

Source: Confrey & Krupa, 2012, p. 9; Morphew, V. N., 2011, pp. 299- 300; National Governors Association Center fo r Best Practices, 2010, English language & literacy, pp. 64-66; National Governors Association Center for Best Practices, 20 10, Mathematics, pp. 6- 8; NGSS Lead St ates, 2013, Volume 1, p. 1; NGSS Lead States, 2013, Volume 2, pp. 67- 79 .

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Part One

Engaging in Experimentation

CONDUCTING AN EXPERIMENT To design a good experiment you need to understand the phenomena you are investigating. You can gain this knowledge by conducting a simple experiment and observing what happens. Then, you can use the observations to design a more refined experiment. To begin learning to design good experiments conduct the experiment in Box 1-1, Rapid Swingers.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

EXPERIMENT Rapid Swingers

QUESTION

How do different length pendulums swing?

HYPOTHESIS

Construct your own.

MATERIALS ► Large paper cl ips

SAFETY ► Wea r safety goggles and appropriate

protective clothing.

► 1.5 m of string ►

Scissors



Met ric ru ler



Timer (s)



Washers- diamet er about 3 cm



Follow your teacher's directions for safety, clean ing the laboratory, and disposing of materials.



See Append ix B, Using Safe Procedures

PROCEDURE 1. At one end of the string t ie a loop that f its firm ly, but not tight ly, around your index f inger. 2. Measure a distance of 100 cm from t he bottom of the loop. Mark the poi nt. Cut t he string about 8 cm below t he marked point.

!

i

3. Tw ist a large paper cl ip into an "S" sha pe. 4. Tie the end of t he string to the "S" shaped paper cl ip so t here is 1 m between t he two knots at each end of the string. 5. Put your index finger in the loop and put one washer on the paper clip hook.

-

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cu -0 C:

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@

6. Hang the pendu lum so it swings freely. 7. Keeping t he string taunt, pu ll the washer 6 cm to one side and release it. 8. Release the w asher and count the number of complete swings in 30 s. A complete swing occurs when t he washer swings over and back. Record your data. 9. Repeat the experiment using strings t hat are 80, 60, 40, and 20 cm long between the two knots. To save st ring you can re-cut the string to the shorter lengths (see steps 2- 4). 7

DATA TABLE Length (cm)

Number of Swings in 30 s

20 40 60 80 100 ANALYZING THE EXPERIMENT 1. What did you hypot hesize?

2. What did you purposely cha nge?

3. What responded to the change?

4. W hat did you keep the sa me?

5. Did the dat a support your hypothesis? Explain .

8

Chapter 1

Conducting Experiments

9

IDENTIFYING EXPERIMENTAL COMPONENTS You just performed a special type of investigation, an experiment. In the experiment you changed something to see what happened. Variables are things in an experiment that change and take on different values.

Independent Variable In the pendulum experiment you purposely changed the length of the pendulum. Scientists call the variable which is purposely changed or manipulated the independent variable. In the experiment you had one independent variable-the length of the pendulum. You changed the length five ways by using 20, 40, 60, 80, and 100 cm strings. The five ways you changed the length of the pendulum are the levels of the independent variable. The levels are the specific values-kind, size, or amount-of the independent variable tested. As a beginning researcher you should choose only one variable to purposely change. If you change more than one variable, such as the length of the pendulum and the size of the washer, you will not know which variable caused the response.

Dependent Variable In the pendulum experiment, there was also another variable-the number of swings in 30 s. The pendulums had different numbers of swings because the lengths of the strings were different. The variable that responds in an experiment is the dependent variable.

Controlled Variables Certain things were kept the same in the pendulum experiment. You used the same type of string. You kept the mass constant by using the same type of washer. You pulled the string the same distance (6 cm) to the side before releasing the washer. You counted the number of swings over the same time period, 30 s. Controlled variables are the things you intentionally keep the same in an experiment. Can you think of other controlled variables? If your results are unexpected, perhaps another variable- in addition to the length of the pendulum- was affecting the number of swings. Look carefully at the experiment. Are there potential variables you did not control? How could you control them so they remain constant? The terms controlled variables and constants have been used as synonyms in experiments, with some authors preferring one term over another. In prior publications, we used the term constants because we think it avoids confusion with the control group, which will be discussed in Chapter 2. However, because the Next Generation Science Standards uses controlled variables we will use this term. Just remember, the controlled variables are the factors which are kept the same (constant) and not allowed to vary.

10

Part One

Engaging in Experimentation

Testable Question We discussed how good questions made our body of scientific knowledge possible and will continue to drive scientific advances. Scientific questions are testable: You can design an experiment and collect data to provide a real answer to the question. Testable questions communicate what you want to learn about the effect of the independent variable on the dependent variable. Good questions describe the problem so a hypothesis can be generated. Many good scientific questions begin with words such as how, does, what, and if. The question"How do pendulums swing?"-begins with how. Even so, it is not a good question. You need to narrow the question to focus on the variables being investigated. A better question is "How does the length of a pendulum affect the number of swings?"

Constructing a Hypothesis Before you experiment you should predict what will happen. Think about how changing the independent variable will affect the dependent variable. This prediction is called a hypothesis. One way to write a hypothesis is to use an "if . .. , then ..." sentence structure.

General format. If the (independent variable) is (describe how you changed it), then the (dependent variable) will (describe the effect). Revised hypothesis. If the length of the pendulum is increased, then the number of swings will decrease.

Chapter 1 Conducting Experiments

11

Before scientists experiment they hypothesize what will happen. The hypothesis is a prediction that is not a wild guess. Instead, the hypothesis predicts how the scientist thinks changing the independent variable will impact the dependent variable. In mathematical and computer models, the independent variable is the input and the dependent variable is the output.

E

0

u

.,,; u

.8

i

::::,

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@ Scientists prefer a directional, rather than a non-directional, hypothesis. Direction means using words such as increase, decrease, less than, more than, slower, faster, and stays the same. The revised hypothesis for Rapid Swingers was a directional hypothesis because it stated that an increase in the length of the string would decrease the number of swings. If the hypothesis had only stated that a change would occur it would be a non-directional hypothesis. If you can only write a non-directional hypothesis you need to read reliable sources, or conduct a pilot study where you can "play around" with the variables and observe how they interact. Then, you can write a directional hypothesis based upon the additional information.

Support for the Hypothesis When the hypothesis and experimental results agree scientists say the hypothesis is supported. If the hypothesis and the results do not agree the hypothesis is refuted. Scientists do not say a hypothesis is right or wrong, correct or incorrect. In the pendulum experiment what was your hypothesis? Did your results support or refute the hypothesis? Also, scientists do not say that a single experiment proves or disproves a hypothesis. Each experiment provides evidence that a hypothesis is supported or refuted. An experiment must be conducted many times to determine the effect of a pendulum's length on the number of swings. You would need to do even more experiments if you wanted to know the impact of using different size washers, changing the mass of the string, or pulling the washer back different distances. In this section, you learned to ask a testable question and to write a hypothesis that predicted the relationship between variables. You distinguished among the independent, dependent, and controlled variables. To assess your understanding of these experimental components, try the questions in Box 1-2, Practice- Variables, Questions, and Hypotheses.

12

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Variables, Questions, and Hypotheses 1. Identify t he independent variable, levels of the independent variable, and the dependent va riable. a. M ichael put 100 red, 100 brown, and 100 yellow corn seeds in his bird feeder. He counted t he number of seeds of each color that remained after 2 days.

b. Leticia timed how fast apple slices t urned brown after being dipped in different preservatives, such as lemon juice, fruit freshener, and lime soda.

2. Identify t he independent variable, levels of the independent variable, dependent va riable, and controlled variables. a. Elizabeth tested how high f ive brands of new tennis balls would bounce when dropped from a height of 2 m. She dropped t he ba lls so t hey hit the same f loor tile each time.

b. Carlos wondered if different colors of plastic w rap affected the time for bread to mold. He w rapped a slice of bread in clea r plastic w rap. Before wrapping the bread he placed 5 ml of water in the center of the bread. He repeated the process with red and blue plastic wrap. The bread came from the center of the same loaf. He used t he same amou nt and brand of plastic wrap . He wrapped the slices of bread the same way.

13

3. Identify the independent variable and dependent variable in each hypothesis. a. If a liquid is placed in conta iners with different height sides, then it wil l evaporate fastest in the container with the lowest sides.

b. If a greater amount of soap is added to water, then fewer drops of water can be placed on a penny.

4. You are interested in how classical, rock and roll, and hard rock music affect a person's pu lse rate. a. Write a testable question on this topic.

b. Write a non-directional hypothesis using an "if . . . , then . .. " sentence structure.

c. Write a directiona l hypothesis using an "if ... , then ... " sentence structure.

5. Determine if the following hypothesis is supported or refuted by the data. a. Alberto thought people wou ld be able to taste sma ll amounts of sugar more easily than vinegar or salt. He found people could detect 2 ml of sa lt in a liter of water. However, they needed only 1.5 ml of sugar and 0.5 ml of vinegar per liter of water to taste the substance.

14

Chapter 1 Conducting Experiments

15

ASSESSING AN EXPERIMENT Through the Rapid Swingers experiment you learned core experimental components: the question, hypothesis, independent and dependent variables, and controlled variables. Many experiments found in books, on the Web, or in videos contain these experimental components. However, the author may not make these components explicit, or even include all of them. You can learn more about experimentation by reviewing experiments, identifying their strengths and weaknesses, and recommending improvements.

Using a Checklist Teachers often use a list to communicate expectations for an assignment. Later, they may use the list as criteria for grading your work. Throughout this book we will provide checklists for assessing and improving experimental components, as well as suggested point values for grading the final product. See Box 1-3, Checklist- Conducting an Experiment, for a checklist which focuses on the experimental components learned in Chapter 1: the question, hypothesis, independent variable, dependent variable, and controlled variables.

onducting an Experiment SELF CHECK

EXPERIMENTAL COMPONENT

PEER CHECK

POINT VALUE

QUESTION 1. Is there a question?

5

2 Does the question commun icate what you want to learn about the interaction of the independent and dependent variables?

10

HYPOTHESIS 3. ls there a hypothesis?

5

4. Does t he hypothesis clearly stat e how changing the independent variable wi ll affect the dependent variable? 5. Is a directional hypothesis written? If not, is a reason provided for the non-directiona l hypothesis?

10

5

INDEPENDENT VARIABLE 6. Is there just one independent variable?

10

7. Is the independent variable operationa lly defined?

5

8. Are the levels of the independent variable clearly stated?

10

9. Are the levels of the variable operat ionally defined?

5

DEPENDENT VARIABLE 10. ls there one or more dependent variables?

10

11. Are the dependent variable(s) operational ly defined?

5

CONTROLLED VARIABLES 12. Does the list of controlled variables include the major factors that might impact the experimental outcome?

10

13. ls each of the identified controlled variables operational ly defined?

10

TOTAL COMMENTS

16

100

GRADE

Chapter 1 Conducting Experiments

17

In the checklist you encountered a new phrase, operationally defined, which means the experimenter precisely stated how a variable will be measured or described. If you defined the length of a pendulum as short, medium, or long, the operational definition would be weak. Instead, it would be better to measure the length (cm) of the pendulum, as was done in Rapid Swingers. This experiment had a strong operational definition of the dependent variable, the number of swings in 30 s. The experiment also defined what a complete swing was-the washer swinging over and back one time. Now, it is your turn to use the checklist to assess the quality of a textbook activity, A Working Heart (see Figure 1-1). After you have assessed this typical activity read the following section to see how your analysis compares with ours.

FIGURE 1-1

PURPOSE

A Working Heart To determine the effects of temperature on the heartbeat of Daphnia.

MATERIALS ► Daphn ia



Beaker (250 ml)



Microscope



Sma ll test tube (13 mm x 100 mm)



Water at va rious temperatures



Graduat ed cylinder, 100 ml



Glass slide



Foam cup



Medicine dropper

► Petroleum jelly ►

Toothpick

PROCEDURE 1. Each lab group w ill use one temperature of water, e.g., Q°, 10°, 20°, 30°, or 40°C . 2. Put 150 m l of w ater in a foa m cup. Use water at your assigned temperature. 3. Place the cup in a 250 ml beaker for greater stabil ity. 4. Put a test tube of water contain ing some Daphnia into your cup of water. Place a clean glass slide in the cup so the sl ide w ill be the sa me temperature as the Daphnia. 5. Wait 10 min. Then, quickly dry the slide. 6. Usi ng a toothpick, place a small amount of petroleum jelly near the cent er of the sl ide. 7. Use a med icine dropper to remove a Daphn ia from the t est t ube. Place the Daphnia on the petroleum jel ly. 8. Qu ickly place the slide on the stage of a microscope. Focus t he microscope. 9. Count the number of the Daphnia's heartbeats in 30 s.

18

Part One

Engaging in Experimentation

Comparing Assessments With the checklist you identified various strengths and weaknesses of the experiment, which may be different from ours. By comparing assessments you can develop a stronger set of recommendations for improving the experiment. The Daphnia activity begins with a purpose, not a question. Despite this, the purpose communicates what the experimenter wanted to learn about the interaction of the independent and dependent variables. This purpose can be changed into a testable question, such as "How does temperature affect the heartbeat of Daphnia ?" Question.

Hypothesis. Even without a stated hypothesis you can identify the independent and dependent variables. If you have studied cold- and warm-blooded animals you can probably make a hypothesis. If not, use reliable print or Web resources to learn about Daphnia so you can make a

better prediction. Remember, a hypothesis is not a wild guess and you need to make a directional hypothesis, if possible. There is one independent variable, the temperature of the water, which is operationally defined as degrees Celsius (°C). The levels of the independent variable are clearly stated, e.g. , 0°, 10°, 20°, 30°, and 40°C. Independent variable.

The dependent variable is identified and operationally defined as the number of Daphnia heartbeats in 30 s. Dependent variable.

In this experiment a number of things were kept constant: Putting the same amount of water (150 ml) into a foam cup, placing the foam cup into a beaker (250 ml), using the same size test tube (13 mm x 100 mm), and waiting 10 min. These controlled variables were operationally defined using metric measurements. The same organism was used and directions were given for mounting the Daphnia on a slide using petroleum jelly and a toothpick. One important factor was not well defined, the size of the foam cup. Size would impact how much of the test tube was immersed in the water and the amount of heat transferred. The experiment said to put Daphnia into the test tube, but did not specify the amount of water from the Daphnia culture to add to the tube. Variations in the amount of culture water would impact the final temperature of the Daphnia. Did you observe other problems with the controlled variables? If so, what were they? How could you define these variables more precisely? Controlled variables.

Using Argumentation Skills As you applied the checklist to the Daphnia lab, you conversed with classmates, your lab group, or even the entire class. When you conversed you engaged in argumentation. Scientists use the process of argumentation to reach evidence-based conclusions. Each time you discussed a question, especially if there was not a clear-cut (yes/no) answer, you engaged in argumentation. Evidencenot opinion-is required for a good argument. The Next Generation Science Standards identify

Chapter 1 Conducting Experiments

19

"engaging in argumentation from evidence" as a practice used by scientists and engineers as they conduct research. These standards describe specific argumentation skills that you should use, such as: ►

Construct and/or support an argument with evidence;



Distinguish between evidence and opinion in one's own and other's arguments;



Listen actively to arguments to indicate agreement or disagreement, based on evidence;



Respectfully provide and receive critiques from peers by citing relevant evidence and posing specific questions to clarify information provided by a peer (NGSS, 2013, Volume 2, pp. 76-77).

Throughout this book you will engage in argumentation using your oral, written, and media skills. These argumentation skills will benefit you in all aspects of your life, not just in STEM classrooms. In this section you used a checklist to evaluate an experiment so better data can be generated to test a hypothesis and to answer a scientific question. Also, you were introduced to operational definitions, which precisely state how a variable is described or measured. Use the checklist to assess the experiments in Box 1-4, Practice- Assessing Experiments. Compare your assessment with your peers' assessments.

20

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Assessing Experiments DIRECTIONS Use t he checklist from Box 1-3 to assess one of the typical lab activities below, or one assigned by your teacher from your classroom materials. For your convenience, a checklist follows.

1. Typical Lab Activity-Disintegrating Socks QUESTION

How fast do socks disintegrate?

MATERIALS ►

Shovel



Tap water



Old nylon, cotton, and wool socks



Graduated cylinder, 250 ml



Container to transport water

► Soda bottle, 1 L

PROCEDURE 1. Dig a hole. 2. Wet the nylon sock with 250 m l of wat er. 3. Put the sock in the hole and cover it w ith soil. 4. Dig two more holes. Put a cotton sock in one hole and a wool sock in the other. 5. After 30 days dig up the socks. 6. Observe and describe the cha nges that occurred.

2. Typical Lab Activity-Friction and Shoes QUESTION

How do shoes differ in frictional resistance?

MATERIALS

©seastar/Shutterstock.com



Books, various th icknesses



Timing device (s)



Pine board, 4 ft (142 cm)





Protractor

Shoes w ith leather, plastic, and rubber soles

PROCEDURE 1. Make a ramp w ith the board and books. 2. Elevate the board to an angle of 45°. 3. Put a shoe w ith a leather sole at the top of the ramp. 4. Release the shoe and time how long it takes for the shoe to slide down the ramp. 5. Do the experiment again with shoes that have rubber and plastic soles. 21

isintegrating Socks ... Friction and Shoes SELF CHECK

EXPERIMENTAL COMPONENT

PEER CHECK

POINT VALUE

QUESTION 1 . Is there a question?

5

2 Does t he question com municate what you want to learn about the interaction of the independent and dependent variables?

10

HYPOTHESIS 3. Is there a hypothesis?

5

4. Does the hypothesis clearly state how changing the independent variable wil l affect the dependent variable? 5. ls a di rectional hypothesis w ritten? If not, is a reason provided for the non-directional hypothesis?

10

5

INDEPENDENT VARIABLE 6. ls there j ust one independent va riable?

10

7. Is the independent va riable operationally defined?

5

8. A re the levels of the independent variable clea rly stated?

10

9. A re the levels of the variable operational ly defined?

5

DEPENDENT VARIABLE 10. ls there one or more dependent variables?

10

11. A re the dependent variable(s) operationally def ined?

5

CONTROLLED VARIABLES 12. Does t he list of controlled variables include the major factors that might impact the experimental outcome?

10

13. ls each of the identif ied controlled variables operationally def ined?

10

TOTAL COMMENTS

22

100

GRADE

Chapter 1 Conducting Experiments

23

EXPLORING STEM CONNECTIONS Science, technology, engineering, and mathematics are intricately connected and interdependent. Digital technology tools, including advanced modeling and simulation techniques, are used in all disciplines. In this section you will use the Rapid Swingers experiment as a prompt for exploring STEM connections.

Science The goal of science is to explain how the natural world works. Over time scientists have investigated many phenomena. These investigations have taken multiple forms-observations, collections, experiments, field studies, and analyses of existing scientific knowledge. Through these investigations scientists have developed increasingly accurate explanations of how the natural world works. The current body of scientific knowledge consists of their findings. Although this chapter focuses on practices used to design and refine an experiment, the purpose of an experiment is to increase understanding of natural phenomena. Whenever you conduct an experiment, it is important to explain the findings and to apply them to multiple scientific disciplines. The questions in Box 1-5 are designed to help you explain and apply scientific concepts related to Rapid Swingers .

Technology and Engineering The goals of technology and engineering are to create products to meet human needs and wants. Engineering has a stronger scientific base and is more analytical than technology. By applying their understanding of the motion of a pendulum, engineers have developed numerous methods for keeping time and for making buildings more earthquake resistant. The questions in Box 1-5 will enable you to make links among engineering, technology, science, and society. Also, you will encounter references to the third part of this book, Engaging in Engineering Design. As you move through this book, you will be referred to engineering activities in Chapter 8. Each activity is designed to increase understanding of engineering and builds upon scientific concepts developed in the chapter experiment. Digital tools are used in all disciplines to enhance productivity, collaboration, and creativity. We encourage you to routinely use word processing software, spreadsheets, media tools, and collaborative tools. In addition, two types of digital tools are widely used in the STEM disciplines--electronic sensors and computer models and simulations. Sensors enhance the accuracy and ease of data collection. Computer models and simulations provide a way to explain scientific phenomena without needing specialized equipment. They also provide an opportunity to explore ideas fully before testing them in an experiment. As part of the STEM connections, we will recommend sensors, computer models, and simulations you can use to improve data collection and virtually investigate variables.

24

Part One

Engaging in Experimentation

Mathematics Mathematics plays two main roles when engaging in STEM investigations. Mathematics as a collection of known relationships can be used at any time as a tool for problem solving. Geometry and Measurement concepts are particularly useful for this purpose. Number Sense, Algebra, and Statistics are useful to describe, analyze, and interpret patterns and relationships. For example, mathematicians have used data from numerous pendulum experiments to write algebraic equations that describe the relationships among various variables. The questions in Box 1-5 are designed to connect and apply mathematics to the experimental data. STEM professionals extensively use Algebra and Statistics. For this reason, you will often be referred to the second volume of this publication. In this volume there are three chapters which support using algebra to describe patterns in data, applying statistics to determine the significance of relationships and implementing an original mathematical investigation. As an alternative you may refer to your mathematics textbook or a source recommended by your teacher. In Box 1-5, STEM Perspective-Rapid Swingers, multiple ways to connect disciplines are described. Depending upon your interests, or the school subject you are studying, you can select from the options or explore a teacher-assigned or self-selected topic.

STEM PERSPECTIVE Rapid Swingers

Science Explaining how the natural world works

1. Forces, interactions, and energy. Explore the fo llowing connections. Then, use key scientific concepts to explain your experimental findings. a. In Rapid Swingers, the pendulum oscillated, that is it moved back and forth around a central point. As the pendulum oscillated, energy moved back and forth between two forms- potential energy and kinetic energy. Construct a diagram to illustrate this system. Wil l a pendulum swing indefinitely? Explain . b. For pendulums, t here are many free on line simulations where you can explore the impact of different variables on the number of swings, e.g., length of st ring, weight of bob, amplitude, and gravitational force. Often, there is application software you can use to graph and analyze your results. To conduct a simulated experiment search for sites such as: Exploriments-Simple Pendulum Math & Science Gizmos-Period of a Pendulum and Pendulum Clock (free trial) Molecular Workbench- Pendulum PhET Interactive Simulations- Pendulum Lab

2. Earth's place in the universe. Assume you are traveling throughout the solar system and plan to visit each planet. How wou ld a pendulum operate on the various planets? During your interplanetary travel? If you did not know which planet you were on would a pendu lum be helpful? Explain . 3. Earth's systems. With a pendu lum, scientists discovered and/or demonstrated some important concepts about Earth. Four of these scientists are listed below. How was the pendu lum involved in their experiments? What experimental evidence led to a key discovery about the Earth? How did their findings lead to other discoveries about the Earth? a. Jean Richer (1672): Relationship between latitude and gravity b. Pierre Bouguer (1737): Relationship between altitude and gravity

25

26

Part One

Engaging in Experimentation

c. George Airy (1824): Relationship between depth beneath surface and gravity

d. n Bernard Leon Foucault (185 1): Why a large free-swing ing pendulum w ill knock down pins arranged in a circula r pattern over time

,

4. Systems and system models. Explore the following connections. a. Met eorologists forecast weather t hrough computer models. How does knowing the El Nino-Southern Osci llation aid meteorologists in weat her forecasting with computer models? b. Many types of oscillations exist. Select one of the examples provided and use reliable resou rces to explain why it is an oscillation. Exa mples include (a) playground swing, (b) t uning fo rk, (c) string on a musica l instrument, (d) human heart , (e) insulin levels, (f) predator-prey population levels, (g) ci rcadian rhythms, (h) geothermal geysers, and (i) El-Nino-Southern Oscillation.

.I..

... ....

..

• · •-a

I

I

Technology and Engineering Modifying the world to meet human needs and wants 5. Engineering design. Go to Chapt er 8 to learn how engineers define an eng ineering problem. Then, apply you r knowledge of oscil lating objects t o meet a human need, making buildings more ea rth quake resist ant. For this engineering activity, see Box 8- 1, Shake It Up. 6. Links among engineering, technology, science, and society. Explore t he fo llowing connections. a. Today's modern clocks range from electrica l clocks to quart z clocks t o atomic clocks. Explain how the concept of oscillat ion is involved in these ti mekeeping methods. b. Many modern technolog ies, such as space t ravel and the Internet, depend on precise time measurements. What institutions are responsible for maintaining a uniform t ime system across t he Earth? How do these institutions maintain accu rate t ime?

\ ''" ,,,,;

':::-'

--

'

,'-

I; / /~

---

Chapter 1 Conducting Experiments

c. Christiaan Huygens invented the pendulum clock in 1656. For almost 300 years the pendulum clock was the most precise method for keeping time. Even though pendulum clocks are now antiques, people continue to adm ire them, and to buy or build replicas. Assume you lived over 200 years ago and were learning to bu ild clocks. A master craftsman gave you the advice below. Use reliable resources to research and explain how each of the factors impacts a pendulum and the accuracy of a timepiece:

0 Use as long a pendu lum rod as possible, make the rod of wood, and be sure to paint or varnish it; 0 Make the pendulum bob heavy, smooth, and sleek; 0 Don't pull the pendulum bob far back from the center-a small displacement from the center works best; 0 Put the pendulum timepiece inside a case; and 0 Check to be sure the t imepiece is level and stationary.

Mathematics Describing, analyzing, and interpreting patterns and relationships

7. Detecting mathematical patterns. Use the data below, or your experimental data, to investigate mathematical relationships. Use the patterns as evidence for supporting or refuting the hypothesis you made earl ier.

a.

Length (cm)

Number of Swings in 30 s

20

31

40

24

60

20

80

16

100

15

Period of Pendulum (s/swing)

Relationship of pendulum length and number of swings. Sketch a graph to represent the data. Use words to describe the relationsh ip between these variables. Do the data support the hypothesis you made about the effect of pendulum length on the number of swings?

27

28

Part One

b.

Engaging in Experimentation

Period of pendulum. The period of a pendulu m is the amou nt of ti me it takes for the pendulu m to complete a f ul l swing. Period

=

t ime in seconds number of swings

The data table shows t he number of swings each pend ulum made in 30 s. You can use the number of counted swings to est imate the period for each of t he pendulums. For example, if t he pendulu m completed 10 swings in 30 s, it t ook 3 s t o com plete each swing . The period of the pendulum is 3 s/swing. Calculate the period for each of the pendulums and enter in the table. c.

Relationship of pendulum length and period of pendulum. Sketch a graph to represent the data. Use words to describe the relationship between these variables.

d.

Comparing relationships. Compare how pendulum length impact s the number of swings and t he period of a pendulum. Explain the differences.

8. Constructing scatter plots. In Chapter 6 learn about scatter plots, trends, and mathemat ical models. Const ruct and interpret scatter plots for your experimental data or t he data in question 7. 9. Using algebra to represent patterns. In Volume 2 (Chapter 15) learn how mathematicians use algebra to develop equat ions that represent mathematical patterns. Then, use your knowledge of linear and non-linear relat ionships to explore relationships among various combinations of variables in question 7 (see data table).

Chapter 1 Conducting Experiments

29

REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Confrey, J., & Krupa, E. E. (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. ExploreLearning. (2015). Math & science gizmos. Charlottesville, VA. Retrieved from https://www. explorelearning.com IL&FS Education & Technology Services. (2010). Exploriments. Retrieved from http://www. exploriments.com Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_Standards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www.apsva.us/cms/lib2NA01000586/Centricity/Domain/29/ CTAE_Committee_Report.pdf The Concord Consortium. (2013). Molecular workbench. Retrieved from http://mw.concord.org University of Colorado Boulder. (2013). PhET interactive simulations. Retrieved from http://phet. colorado.edu/

CHAPTER

2 Refining Experiments

CONTENTS Introduction Learning Objectives Correlations With Nationwide Standards

32 32 32

Conducting an Experiment Box 2-1 Experiment-Floating Eggs

34 35

Adding a Control Group

37

Using Repeated Trials Quantitative Data Qualitative Data Box 2-2 Practice- Control Group and Repeated Trials

38 38 39 41

Changing a Hypothesis to an Explanatory Model

43

Disguishing Between Evidence and Explanations Box 2-3 Practice- Explanatory Hypotheses, Evidence, and Explanations

44 45

Assessing a Refined Experiment Using a Checklist Box 2-4 Checklist- Refin ing an Experiment Box 2-5 Practice- Assessing a Refined Experiment

47 47 48 49

Exploring STEM Connections Box 2-6 STEM Perspective-Floating Eggs

51 53

References

57 31

32

Part One

Engaging in Experimentation

INTRODUCTION Each part of an experiment serves a specific purpose. Previously, you learned that a good experiment begins with a testable question, which enables you to design an experiment, collect data, and provide a real answer to the question. Then, you wrote a hypothesis, which was a prediction of how you thought the independent variable would impact the dependent variable. You identified the controlled variables, which are other variables that need to remain constant. You determined if the data supported or refuted the hypothesis. Now, you will refine the experiment to have greater confidence in the data and its use as evidence to support or refute the hypothesis.

Learning Objectives Specific learning objectives for Chapter 2, Refining Experiments, include: ►

Describe the purpose of a control group;



Distinguish between a no treatment and experimenter selected control group;



Describe how repeated trials increase confidence in experimental findings;



Distinguish between quantitative and qualitative data;



Use the mean or mode to summarize repeated trials;



Develop a hypothesis that can serve as an explanatory model for an experiment;



Distinguish among statements that represent a hypothesis, evidence, and explanation;



Use a checklist to evaluate a refined experiment so better data can be generated to test a hypothesis and answer a scientific question; and



Use argumentation skills to compare assessments of a refined experiment.

Correlations With Nationwide Standards In Table 2-1, the core chapter objectives and STEM concepts are correlated with nationwide learning standards. The correlations for "Exploring STEM connections" are shown in italics. For a synopsis see Appendix A.

Chapter 2

TABLE 2-1

Refining Experiments

33

Correlations With Nationwide Standards

NEXT GENERATION SCIENCE STANDARDS ► Scientific & Engineering Practices:

Developing and using models; Planning and carrying out investigations; Analyzing and interpreting dat a; Constructing explanat ions and designing solutions; Engaging in argument from evidence; Using mathematics and computational thinking; Obtaining, evaluation, and communicating information

► Cross-Cutting Concepts:

Patterns; Cause and effect; Systems and system models;

Structure and function ► Disciplinary Core Ideas:

Motion and stability; Energy; Matter and its interactions; Earth 's systems; Engineering design; Links among engineering, technology, science, and society

COMMON CORE STANDARDS-MATHEMATICS ► Mathematical Practices:

Construct viable arguments and crit ique the reasoning of others

► Mathematical Domains:

Statist ics and probabil ity; Int erpreting categorical and quantitative data; Expressions and equations

COMMON CORE STANDARDS-LITERACY IN SCIENCE AND TECHNICAL SUBJECTS ► Reading:

Cit e textua l evidence; Determ ine key ideas or conclusions; Fol low multi-step procedure; Determine meaning of symbols, key terms, etc., Integrate words and visual representations; Read and comprehend text

► Writing:

Write arguments; Conduct short research projects; Gather relevant information; Draw information from informational texts

ISTE STANDARDS-STUDENTS ► Creativity and innovation:

Identify t rends and forecast possibilit ies; Use models and simulations to explore complex systems and issues

► Research and information fluency:

Process data and report results; Locate . .. use information from a variety of sources; Evaluate and select information sources and digital tools based on the appropriateness to specific tasks

► Critical thinking, problem solving, and decision making:

Collect and analyze data t o

ident ify solutions and/or make informed decisions ► Digital citizenship:

Demonstrate personal responsibi lity for lif elong learning; Advocate and practice safe, legal, and responsible use of technology; Exhibit a positive attitude toward using technology that supports collaboration, learning, and productivity



Technology operations and concepts: Understand and use technology systems

Source: Confrey & Krupa, 20 12, p. 9; M orphew, V. N., 20 11, pp. 299- 300 ; Nat ional Governors Association Cent er fo r Best Practices, 2010, English lang uage & lit eracy, pp. 64- 66; Nation al Governors Association Center for Best Practices, 20 10, M athematics, pp. 6- 8; NGSS Lead St ates, 20 13, Volume 1, p. 1; NGSS Lead States, 20 13, Vo lume 2, pp. 67- 79.

34

Part One

Engaging in Experimentation

CONDUCTING AN EXPERIMENT To begin refining experiments, conduct the investigation in Box 2-1, Floating Eggs. Then, read the following sections where experimental data will be used to introduce additional experimental components.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

EXPERIMENT Floating Eggs

QUESTION

How will the amount of salt impact the height an egg will float?

HYPOTHESIS

Construct your own.

MATERIALS

SAFETY

► Safety gogg les ►

► Wea r safety gogg les and appropriate

Room temperature tap wat er

► Graduat ed cylinder, ► Clear beaker

250 ml

(250 ml) or plastic cup

1 uncooked egg in the shell

► Holding conta iner to keep the egg

from rolling ► Table sa lt, about ►

► Do not taste the salt , egg, or solution. ► Wash hands aft er investigating.

► Follow your teacher's directions for safety,

(400 m l) ►

protective clothing .

clean ing the laboratory, and disposing of the salt solution and egg . ► See Append ix B, Using Safe Procedures

45 ml

Met ric measuring spoon or teaspoon (5 ml)

► Stirrer ► Met ric ruler

► Spoon for getting the egg in/out of

solution

PROCEDURE 1. Place 250 ml of room temperature tap water in a beaker or clear container. 2. Using a spoon carefu lly put the egg into the water. Measure the distance from the bottom of the container to the bottom of t he egg in mil limeters. Record the data. 3 . With a spoon, remove the egg and place it in the holding cont ainer. 4. A dd 10 ml of salt t o the water and st ir until the sa lt is dissolved.

35

5. Gently put the egg in t he salt w ater and measure the distance from the bottom of the conta iner t o t he bottom of the egg in milli met ers. Record the dat a. 6. Repeat steps 4 and 5 using a total of 20, 30, and 40 ml of salt. 7. Remove the egg . Discard the salt solut ion. Rinse the container thoroughly. 8. Repeat steps 1- 7 for a total of four t ries. If you are experimenti ng in class, split into groups and have each group conduct t he experiment once. Then , t he groups can com bi ne data.

DATA TABLE Height Egg Floats (mm) Tries

Total Amount of Salt (ml) 1

2

3

4

0 10 20 30 40

ANALYZING THE EXPERIMENT 1. What were the independent variable, levels of the independent variable, dependent variable, and cont rol led variables?

2. Why did you measure the height of t he egg in 0 ml of salt?

3. Why did you repeat the experiment four times or combine t he data from several groups?

4. How cou ld you mathematically summarize the data across several groups?

5. How does the su mmary dat a provide evidence that t he hypothesis was supported or refuted?

36

Chapter 2

Refining Experiments

37

You just conducted an experiment to answer the question: "Will the amount of salt impact the height an egg will float?" This experiment included components you learned in Chapter 1. The independent variable, total amount of salt, had five different levels-0, 10, 20, 30, and 40 ml. For the dependent variable, you measured the distance from the bottom of the container to the bottom of the egg in millimeters. Controlled variables included the amount of water (250 ml), stirring the salt in the water, and using an uncooked egg. In addition, this experiment includes components which will enable you to have greater confidence in your experimental findings.

ADDING A CONTROL GROUP All of the factors that affect the results must be controlled, or kept constant, except for the independent variable you purposely change. When the independent variable is not changed the dependent variable should not change. If the independent variable is unchanged and the dependent variable changes considerably this means a potential controlled variable is not remaining constant. Experiments need a way to detect hidden variables, which are variables that should be controlled but which change accidentally. In the egg investigation, you needed a way to detect if some factor other than the amount of salt was affecting the results. This is the reason for the tap water in the egg investigation. The trials involving just tap water are called the control group. A control group is used as a standard of comparison. In an experiment, a control group is important because it is used to detect hidden variables which are varying when they should not. In the egg investigation the tap water was used as a standard. The changing heights of the egg in various concentrations of salt water were compared to the egg's height in tap water to determine if the added salt affected the egg's flotation behavior. When salt was added the egg floated higher; therefore, the amount of salt affected flotation. Most experiments include a control group. All other experimental groups are compared with the control group to determine experimental effects. In some experiments the control group is called a no treatment control group. In the egg investigation the tap water was a no treatment control group because zero or no amount of salt was added. In some experiments all trials receive a treatment. The experimenter must then select one level of the independent variable as the control group, or standard of comparison. If you were examining

the effect of water at 0°, 25°, 50°, 75°, and 100°C on the height (cm) of bean plants, what would you use as a control group?You cannot expect plant growth without water. The "no treatment" control group is not an option. Instead, you must select plants watered with certain temperature water as the control group, and then state the reasons for your choice. This type of control group is called an experimenter selected control group. In the bean plant experiment, you could select 25°C as the control group, and justify it as the temperature closest to room temperature. Now you can answer the question: "Why did you measure the height of the egg in 0 ml of salt?" Testing the egg in the 0 ml of salt was needed as a control group or standard of comparison. Before you can determine the effect of putting salt into water, you need to know the answer to questions, such as "Are the eggs in your house fresh enough to sink?" and "Water varies from place to place-how did your egg act in your water?" If the egg acts the same way each time it is put into tap water you can be sure the effect you observed resulted from the different amounts of salt added, and not to something else. Zero milliliters of salt is your no treatment control group or standard of comparison.

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USING REPEATED TRIALS In the egg investigation, you tried the experiment four times or combined your group's data with other groups' data. Despite your best efforts in making measurements chance errors may occur. By chance, no matter how careful you were, some measures of salt were a little larger or a little smaller. You stirred the salt solutions until you thought the salt was totally dissolved, but perhaps some undissolved grains went unnoticed. Sometimes you might have read the ruler differently when you measured the bottom part of the egg. Or, unknowingly you may have changed brands of salt. To reduce the effect of such chance errors, you conducted repeated trials. You put the egg in tap water four times, in water with 10 ml salt four times, in water with 20 ml salt four times, in water with 30 ml salt four times, and in water with 40 ml salt four times. Repeated trials are the number of times each level of the independent variable is tested, not the number of levels of the independent variable-0, 10, 20, 30, and 40 ml of salt. Each level was tested four times (or by four student groups), so there were four repeated trials. Typically, variations in measurements tend to be small and to happen by chance. They are unavoidable. There is no such thing as a perfect measurement or a measurement free of error! Repeated measurements are made assuming some errors make an individual measurement too high and others make an individual measurement too small. "How many repeated trials do I need?" is a common question. The answer is-"It depends on the experiment." There are very few differences among the eggs in a carton. When you investigate nonliving things, such as homemade wood glue, you tend to get similar data. For this reason you can use a smaller number of trials, such as four or five. However, there are many differences among even similar looking groups of plants or animals. Because of these differences in organisms you get a greater variation in your data; therefore, more trials are necessary. With living organisms you should conduct as many trials as time, money, and space will allow. The more repeated trials you conduct the more likely you will reduce the effects of chance errors. The larger the number of repeated trials the more confidence you can place in the data when you say the hypothesis was supported or refuted.

Quantitative Data Raw data are the individual measurements, counts, and observations made during an experiment. Typically, scientists collect quantitative data which involves counting or measuring objects with a standard scale, such as the tools used in the English or metric systems. Although the English system is a standard system, scientists use the metric system because it is used worldwide. One way to summarize quantitative data is to calculate the mean: Sum of measurements Mean= - - - - - - - - - or Number of trials

Sum of counts Number of trials

In Table 2-2 we summarized our quantitative data by calculating the mean. How does your data compare with ours?

Chapter 2

TABLE 2-2

Refining Experiments

39

The Effect of the Amount of Salt on the Height an Egg Floats Height Egg Floats (mm) Trials

Total Salt (ml)

Mean Height of Egg (mm)

1

2

3

4

0

0

0

0

0

0

10

0

0

0

0

0

20

35

37

35

36

35.8

30

44

45

45

46

45.0

40

52

54

50

53

52.3

Qualitative Data You could have collected qualitative data in the Floating Eggs experiment. Qualitative data describe qualities such as the color of leaves, cloudiness of a solution, or position of the egg. After observing how the egg floated in various salt solutions, we made a scale which included a combination of words and diagrams. This scale is shown in Figure 2- 1, Observational Scale for Floating Position of Egg.

FIGURE 2-1

Observational Scale for Floating Position of Egg Top of Solution

00 NF

NF-T

Key for Scale NF

= Not

Floating

NF-T = Not fl oating w ith tilt

... FT

Bottom of Solution

FH

FV

= Floating verti ca lly

FH

= Floatin g ho rizont ally

© Kendall Hunt

When the raw data consist of observations, rather than measurements, you use the mode to summarize the repeated trials for each level of the independent variable. Mode = Most frequency category To find the mode count the number of items falling into each category of the scale. Then, report the most frequent category as the mode. If two or more categories have the same frequency, report all categories with the highest frequency as the mode. Using the scale previously described, we recorded and summarized our data as shown in Table 2-3, The Effect of the Amount of Salt on the Position of an Egg.

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TABLE 2-3

The Effect of the Amount of Salt on the Position of an Egg Floating Position Trials

Total Salt (ml)

Mode

1

2

3

4

0

NF

NF

NF

NF

NF

10

NF

NF-T

NF-T

NF-T

NF-T

20

FV

FV

FV

FV

FV

30

FV

FH

FH

FH

FH

40

FH

FH

FH

FH

FH

Key for Floating Position: NF= Not floating; NF-T = Not floating with tilt; FV = Floating vertical ly; FH = Floating horizontally

Using the data in Table 2-3 what do you observe about the impact of the amount of salt on the tilt of the egg? Can you write a hypothesis for a future experiment using an "if ... , then .. ." sentence structure? If you have trouble writing the hypothesis you need to learn more about the topic. For example, we decided we needed to learn about the structure of an egg and how the structure might be changed by the salt water. Also, we were curious about different aged eggs, and even rotten ones. As you can see, experiments frequently lead to more questions than answers. In this section you learned the purpose of the control group and how to distinguish between a no treatment and experimenter selected control group. To increase confidence in the data, you learned the importance of repeated trials for reducing chance variations in data. Because you needed to mathematically summarize the repeated trials, you learned to calculate the mean of quantitative data and the mode of qualitative data. To check your mastery of these skills, try the questions in Box 2-2, Practice- Control Group and Repeated Trials.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Control Group and Repeated Trials 1. Identify the control group in each of the following experiments. Tel l if the control group is a no treatment or experimenter selected control group. a. Shawnita investigated how wel l different kinds of soap would make oil and water mix. She put 240 ml of water and 5 ml of salad oi l in a zipper-lock bag. She shook the bag 30 t imes in 5 s. Then, she observed t he number and size of the oi l drops. Next, she repeated the experiment using 240 ml of water, 5 ml of salad oi l, and 1 drop of dishwashing liquid . She also tested laundry detergent, shampoo, and liquid hand soap.

b. Marques became interested in objects floating in different liquids. He put vinegar in a jar and measured how high a pencil would float in the jar. He repeated t he experi ment using other kinds of liquids: corn oil, mot or oil, water, soda, and milk.

2. Identify t he kind of data col lected in the fol lowing experiments. Ind icate if the data are measurements, observations, or counts. a. Maria kept her arms st raight in front of her and w iggled her f ingers. She kept looking st raight ahead. She moved her arms to the side until she cou ld no longer see her wiggling fingers. She had her sister measure the distance between her hands in centimeters. Maria repeated the experiment with her right eye covered and then her lef t eye covered.

b. Jerann investigated the effect of microwaving radish seeds on their growth. He exposed four different groups of seeds to 15, 30, 45, and 60 s of microwave radiation. He used a power setting of "3" on the microwave. Seeds were placed in the same type of container and in the same location in the microwave. Jerann planted the seeds. At the end of two weeks he counted the number of seeds that germinated. He also measured the height in centimeters of the plants.

41

3. For each experiment, indicate the most appropriate way to summarize repeated trials (mean or mode): a. The effect of different strengths of bleach on the time for stains to disappear;

b. The abil ity of various metals to conducVnot conduct electricity;

c. The number of roots produced with different concentrations of a rooting hormone;

d. The amount of water (ml) consumed by chickens from red, blue, and yel low bowls;

e. The influence of phosphorous on the color of algae in an aquarium.

4 . After you read each of the following scenarios: (a) identify the independent variable, levels of the independent variable, dependent variable, controlled variables, control group, and number of repeated trials, (b) classify the data collected as measurements, counts, or observations, (c) indicate whether you would use the mean or mode to summarize the data. a. Lillian explored the magnifying power of water drops. She bent the end of a paper clip into a 5 mm wide circle. She f illed the circle with water and looked through the drop at the letter "E". She tried five different drops; each time she described the magnification as none, small, or large. She repeated the experiment using a 10 and 15 mm wire circle fi lled w ith water. Because 1O mm was the middle width, Lil lian decided to use it for comparison.

b. A shopping mall wanted to determine whether the more expensive "Tough Stuff" floor wax was better than the cheaper "Steel Seal" floor wax at protecting its floor t iles against scratches. One liter of each brand of floor wax was applied to each of f ive test sections located in the main hall. The test sections were the same size and were covered w ith the same kind of tiles. Five test sections received no wax. After three weeks the number of scratches in each section was counted .

42

Chapter 2

Refining Experiments

43

CHANGING A HYPOTHESIS TO AN EXPLANATORY MODEL Before you conducted the egg experiment you predicted what would happen. In Chapter 1, you used an "if ... , then .. ." sentence structure to write a hypothesis. General format. If the (independent variable) is (describe how you changed it), then the (dependent variable) will (describe the effect). Hypothesis. If the amount of salt is increased, then the egg's floating height will increase. As you know, a hypothesis is not a wild guess. Initially, a hypothesis may emerge from a mental model that is based upon personal experience. A student might say: "The egg will float higher because I float higher in ocean water." Stating the reason for a hypothesis strengthens the hypothesis. One way to write a stronger hypothesis is to use an "if .. . , then .. . because ..." sentence structure. General format. If the (independent variable) is (describe how you change it), then the (dependent variable) will (describe the effect) because (state the reason). Hypothesis A. If the amount of salt is increased, then the egg's floating height will increase because people float higher in ocean water. Although personal mental models can be helpful in developing an initial hypotheses, additional research is needed to develop a conceptual model which explicitly represents the phenomena being investigated. Conceptual models are based on careful study including observations, previous experimental results, meetings with scientists, and information from science textbooks and other reliable media. You can move from a personal mental model to a conceptual model by learning about salinity, density, buoyancy, and Archimedes' Principle. With this increased knowledge you have a stronger conceptual model and can write an explicit hypothesis. Hypothesis B. If the amount of salt is increased, then the egg's floating height will increase because salt increases the heaviness of the solution. Hypothesis C. If the amount of salt is increased, then the egg's floating height will increase because salty water is denser. Hypothesis D. If the salinity of the solution is increased, then the egg's floating height will increase because the density of the salt solution is related to the amount of dissolved salt. Hypothesis E. If the salinity of the solution is increased, then the egg's floating height will increase because of the greater buoyant force of the salt solution. When written as an "if .. . , then ... because .. ." sentence a hypothesis becomes more than a prediction: It becomes an explanatory model that can be tested, used to determine if the model's inferences are supported by data, and refined through additional experimentation.

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DISTINGUISHING BETWEEN EVIDENCE AND EXPLANATIONS Earlier we made a number of hypotheses based upon the "if ... , then . . . because . . ." sentence structure. For example, Hypothesis E was: If the salinity of the solution is increased, then the egg's floating height will increase because of the greater buoyant force of the salt solution. The first part of the hypothesis was a prediction: "If the salinity of the solution is increased, then the egg's floating height will increase." You collected experimental data on the height of the eggs and summarized it using the mean. These quantitative data are summarized in Table 2-2, The Effect of the Amount of Salt on the Height an Egg Floats. When you state whether a hypothesis is supported or refuted, you need evidence to support the statement. The evidence is the data summarized in Tables 2-2 and 2-3. Using these data, you can write sentences summarizing the evidence: "As the total amount of salt increased from 0 to 40 ml, the mean flotation height increased from 0 to 52.3 mm. With 20 ml of salt the egg floated in a vertical position; at higher salt concentrations it floated in a horizontal position." For the amounts of total salt tested the evidence (data) supported Hypothesis E. What do you think would happen if you used 50 or 60 ml of total salt? Without testing these levels of the independent variable you do not know. You would need to do additional experiments to expand the range of your data (evidence). The second part of the hypothesis gave the reason for the prediction: "because of the greater buoyant force of the salt solution." This reason, or explanation, was based on an interpretation of the current body of scientific knowledge. From the hypothesis one assumes the experimenter knows something about forces, buoyancy, and salt solutions. However, just using the words is insufficient. The experimenter needs to specifically apply these concepts to the floating egg experiment and explain the findings. Can you explain the experimental findings? If not, use science textbooks or other reliable media to learn more about forces, buoyancy, and salt solutions. Throughout this book, you will have multiple opportunities to construct explanatory hypotheses, identify and use evidence to support or refute a hypothesis, and develop explanations for your findings. To assess your current understanding, try the questions in Box 2-3, Practice- Explanatory Hypotheses, Evidence, and Explanations.

44

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Explanatory Hypotheses, Evidence, and Explanations DIRECTIONS Read the scenario about "Temperature and Bean Plants." Then, classify the statement s t hat fo llow as: (a) hypot hesis, (b) evidence, (c) supports or ref utes the hypot hesis, (d) explanation . The statements may not be w ritten in the formal language used by scient ists.

TEMPERATURE AND BEAN PLANTS Linda's grandmother grew African Violet s as a hobby. While visit ing, Linda helped her grandmother water t he plants. The day before watering the plant s her grandmother put a container of water on t he counter; she sa id she wanted the water to be room temperature so the plants would grow better. Linda was confused. In science class she had learned plants grow better in warm weather, so she thought plants would grow better if wat ered with warm water. The warm water would warm t he soi l and make it easier for the plants to take up the fertilizer in the soi l. Linda decided to turn her confusion into a science project. Because African Violets are expensive, she decided t o use a less costly plant , a variety of st ring bean. She planted five bean seeds in identical pots cont aining the same amount and kind of soi l, wh ich contained premixed fert ilizer. She labeled t he pots A, B, C, and D. On Mondays and Fridays she watered each pot with a different type of water. At the end of 30 days she measured the height of the bean plants in centimeters. She used the mean to summarize t he data on plant height.

The Effect of Water Temperature on the Height of Bean Plants Bean Pot

Temperature of Water

Mean Height (cm)

A

Ice water

22.0

B

Room t emperature

24.0

C D

Hot t ap water

18.0

Boiling water

0.0

Linda was surprised. When t he water temperature increased from ice water to room temperature, the mean plant height did increase from 22 to 24 cm. However, the mean height decreased t o 18 cm when hot tap water was used . Wit h boiling water the plants did not grow. Linda said her hypothesis was correct when the water temperat ure was between ice water and room temperature, but not at higher temperatures. Her grandmother was right.

C

=>

I

After learning more about plant s, Linda said very hot water damaged the root hairs so the plants cou ld not take up t he water and nutrients needed for growth. She also thought she needed to do the experiment again using specif ic temperat ures of water between ice water and hot tap water. Th is way she cou ld investigate the temperature at which the wa rmer water began harming, rather than helping, the plants. W ith t his information she would 45

know which temperatures of tap water could be used. She predicted that within a certain temperature range the plant height would increase with warmer water.

STATEMENTS a. She said she wanted the water to be at room temperature so the plants wou ld grow better.

b. She thought plants would grow better if watered with warm water.

c. The warm water would warm the soil and make it easier for the plants to take up the

ferti lizer in the soil.

d. When the water temperature increased from ice water to room temperature, the mean plant height did increase from 22 to 24 cm .

e. However, the mean height decreased to 18 cm when hot tap water was used. With boiling water, the plants did not grow.

f. Linda said her hypothesis was correct when the water temperature was between ice water and room temperature, but not at higher temperatures.

g. Her grandmother was right.

h. Linda said that very hot water damaged the root hairs so the plants could not take up the water and nutrients needed for growth.

1.

She predicted that within a certain temperature range the plant height wou ld increase with warmer water.

IMPROVEMENTS Which of the above statements need to be improved? What changes would you make? Re-draft the statements to show the revisions.

46

Chapter 2

Refining Experiments

47

ASSESSING A REFINED EXPERIMENT In Chapter 1 you used a checklist to assess the quality of the question, hypothesis, independent variable, dependent variable, and controlled variables in an experiment. Through the Floating Eggs experiment you learned the importance of additional components-the control group and repeated trials. Also, you learned to expand your hypothesis from a prediction (if ... , then ... ) to an explanatory model (if ... , then ... because ... ). In Box 2-4, Checklist-Refining an Experiment, the criteria have been expanded to include the new experimental components.

Using a Checklist Review the items in the checklist. All should be familiar. If not, review the information in Chapter 1. Then, use the checklist to assess the experiments included in Box 2-5, Practice- Assessing a Refined Experiment, or an experiment provided by your teacher.

efining an Experiment SELF CHECK

EXPERIMENTAL COMPONENT

PEER CHECK

POINT VALUE

QUESTION 1. Is t here a question?

2

2. Does t he quest ion com municate what you want to learn about the int eract ion of the IV and DV?

3

HYPOTHESIS 3. Is t here a hypot hesis?

5

4. Does t he hypothesis clearly st ate how changing t he IV will affect the DV?

10

5. Does t he hypothesis state t he reason for the pred ict ion?

5

6. Is a directional hypothesis written? If not, is a reason provided for the non-directional hypothesis?

5

INDEPENDENT VARIABLE 7. Is t here j ust one IV?

5

8. Is t he IV operationally def ined? 9. Are the levels of t he IV clearly stat ed?

5 5

10. Are the levels of t he IV operationally defined?

5

DEPENDENT VARIABLE 11. Is there one or more DV(s)?

10

12 . Are the DV(s) operationa lly defined?

5

CONTROLLED VARIABLES 13. Does the list of CV include the major factors that might impact the experi menta l outcome?

10

14. Is each of the ident ified CV operationally def ined?

5

CONTROL GROUP 15. Is t here a cont rol group?

5

16. Is the control group operationa lly defined?

5

REPEATED TRIALS 17. Are t here repeated tria ls?

5

18. Is the number of trials sufficient?

5

TOTAL COMMENTS

48

100

GRADE

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ _ __

PRACTICE Assessing a Refined Experiment DIRECTIONS Use the checklist from Box 2-4 to assess one of t he typical lab activit ies below, or one assigned by your teacher from classroom mat eria ls. For your convenience, a checklist follows. Just enter the name(s) of the activities you are assessing .

1. Typical Lab Activity-Paper and Ink Separation QUESTION

How does paper impact the separation of marker colors?

HYPOTHESIS If the paper is thinner, then the color separation will begin further away because there are fewer fibers to absorb the water and hold the ink. MATERIALS ►

Black marker- water soluble Clear plastic cup ► Tap water ► Graduated cylinder, 100 ml ►



Various types of paper- coffee fi lter, paper towel, t issue paper, computer paper ► Scissors ► Metric ruler

PROCEDURE 1. 2. 3. 4. 5.

Cut a strip of coffee filter paper (15 cm long and 3 cm w ide). Put a dot of marker ink 5 cm from the bottom of the strip. Hang the strip over the edge of the cup . Pour water so that it is just below the ink dot. Allow time for the ink to separate. Then, measure the distance (mm) from the drop to the first color observed. Record the number and type of colors observed. 6. Repeat st eps 1- 5 for the other types of paper.

2.

C

=>

::c

Typical Lab Activity-Do Solutes Impact the Heaping of Water?

QUESTION HYPOTHESIS

Does water heap less when there are dissolved solids? If solids are dissolved in water, then there will be less heaping.

MATERIALS ►







Clear glass votive candle holders- 3 Distilled water ► Salt solut ion (5 ml salt in 100 ml distilled wat er) ► Sugar solution (5 ml sugar in 100 ml distilled water)

Pennies Thermomet er ► Graduated cylinder ► Metric measuring spoon (5 ml)

PROCEDURE 1. 2. 3. 4. 5.

Fill a voti ve with distilled water until you can see the water above the rim of the glass. Carefully drop a penny in the distilled water. Add pennies to the distilled water until it runs over. Record the number of pennies added. Repeat st eps 1- 3 for a tot al of five trials. Using a clean votive repeat steps 1- 4 for th e sugar soluti on. Then, repeat with a salt solution.

49

per and Ink Separation ... Solutes and Heaping Water SELF

EXPERIMENTAL COMPONENT

CHECK

PEER CHECK

POINT VALUE

QUESTION 1. Is there a question?

2

2. Does t he question commun icate what you want to learn about t he interaction of the IV and DV?

3

HYPOTHESIS 3 . Is there a hypothesis?

5

4. Does t he hypothesis clearly state how changing t he IV will affect the DV? 5. Does the hypothesis stat e the reason fo r the predict ion? 6 . Is a directional hypothesis written? If not, is a reason provided for the non-directional hypothesis?

10 5 5

INDEPENDENT VARIABLE 7. Is there just one IV? 8. Is the IV operationa lly defined?

5 5

9. Are the levels of the IV clearly stated?

5

10. Are the levels of the IV operationally defined ?

5

DEPENDENT VARIABLE 11 . Is there one or more DV(s)?

10

12. Are the DV(s) operationa lly def ined?

5

CONTROLLED VARIABLES 13. Does t he list of CV include t he major factors that might impact t he experimental out come? 14. Is each of the identified CV operational ly defined?

10 5

CONTROL GROUP 15. Is there a control group?

5

16. Is the control group operational ly defi ned?

5

REPEATED TRIALS 17. Are there repeated trials?

5

18. Is the number of t rials sufficient?

TOTAL COMMENTS

50

5 100

GRADE

Chapter 2

Refining Experiments

51

EXPLORING STEM CONNECTIONS You know how important we think it is for you to make connections among the various scientific disciplines, mathematics, technology, and engineering. In this section, the Floating Eggs experiment will be used as a prompt for exploring connections. In Box 2-6, STEM Perspective-Floating Eggs, some options are described. As before, select among the options, complete a teacherassigned investigation, or identify a topic you want to research.

52

STEM PERSPECTIVE Floating Eggs

Science Explaining how the natural world works

1. Forces, interactions, energy ... systems and models. Explore the following connections. Then, use key scientific concepts to expla in the experimental findings. a. What is Archimedes Principle? Use this principle to explain the egg's floatation. b. To a scientist, what is a system? Use the concept of a system to explain the floating egg experiment.

c. For floating objects, there are online simulations where you can explore factors affecting buoyancy. To conduct a simu lated experiment, search for sites such as: Exploriments-Archimedes Principle 1, Buoyancy and Floatation 2 and Understanding Buoyancy and Floatation Math & Science Gizmos- Archimedes' Principle, Density Laboratory, and Determining Density via Water Displacement (free trial) PhET Interactive Simulations-Buoyancy

2. Structure and function. What is the structure of an egg? Relate the structure to the function it serves. Use information about an egg's structure to explain the different floating positions. 3. Matter and its interactions. Before refrigeration and "sell-by" dates food markets often kept a bowl of water by the eggs. Customers dropped the eggs in water to see if they would float. If an egg floated the customer di d not buy the egg. Explain the chem ical basis for this test. 4. Earth's systems. How is the experiment related to the flow of rivers into the sea, such as the M ississippi River into the Gulf of Mexico or the A mazon River into the Atlantic Ocean?

53

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Technology and Engineering Modifying the world to meet human needs and wants

5. Engineering design. In Chapter 8 engage in eng ineering. Apply your knowledge of buoyancy to design a floatation device. For t his eng ineering activity, see Box 8-2, Life Savers. 6. Engineering design. In Volume 2 (Chapter 14) brainstorm ideas for designing a solution to eut rophication includ ing stationary and floating marshes. 7. Links among engineering, technology, science, and society. Explore the following connections. a. Commercial egg producers use technology to sort eggs int o various sizes and to be su re the eggs are fresh. How do these technologies work? b. How have commercial egg producers used knowledge of chickens' visual system t o increase egg production? What are t he pros/cons of these techn iques?

Mathematics Describing, analyzing, and interpreting patterns and relationships

8. Detecting mathematical patterns. Use the data below, or your experimental data, to investigate mathematical relationsh ips. Use the pattern as evidence for su pporting or refut ing t he hypothesis you made earlier. Total Salt (ml)

Mean Height Egg Floats (mm)

0

0

10

0

20

35 .8

30

45.0

40

52.3

a. Relationship of amount of salt and egg's floating height. Use words t o describe the relationship between these variables. Sketch a graph to illust rate the features. Do t he data support or refute the hypothesis you made? b. Accuracy of data. Do you th ink the data you collected w as accurate? Explain. How might you use digital technology to improve t he accuracy of the data?

Chapter 2

Refining Experiments

9. Calculating the concentration of solutions. In the experiment, you added 10 ml of salt at a t ime and reported t he total amount of sa lt as the level of the independent variable. Scient ists would use more precise met hods to express the concentration . Use t he information in the table below to learn different ways to express t he concentration of a solution. Levels of Independent Variable (ml of salt)

Mass of Salt (g)

Mass of Water (g)

Mass of Solution (g)

0

0

250

250.0

10

20.1

250

270.1

20

39.6

250

289.6

30

60.3

250

310.3

40

8 1.9

250

33 1.9

Percent Concentration (mass)

Parts per Thousand (mass)

a.

Percent concentration. When a solid solute is dissolved in a liquid solvent, scientists typically commun icate concent rat ion by describing t he mass of the solute in a given mass of solut ion. For exa mple, a 15% salt solut ion consists of 15 g of sa lt and 85 g of water in each 100 g of solut ion. What is the percent concentration of the solution used for each level of the independent variable?

b.

Parts per thousand. Percentages represent the number per hundred or parts per hundred. In other words 15% means 15 out of 100 part s, which can be written as t he fraction, 15/100. To convert from a percentage to part s per thousand (ppt) you need t o f ind the equivalent fraction with a denominator of 1000 which would be: 150/1000. Therefore, 15% is the same as 150 ppt. What is t he concentration of t he solut ions used for each level of t he independent va riable in pa rts per thousand?

55

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Engaging in Experimentation

c. Predicting the egg's floatation in natural environments. Salt concentration is used to classify different types of water, e.g., fresh (< 0 .5 ppt.), brackish (0.5- 29 ppt.), and ocean (30- 50 ppt.). The following table shows the floating position of eggs in the various salt solutions.

Total Amount of Salt (ml)

Mode for Floating Position

0 10 20 30 40

Not floating (NF) Not floating with tilt (NF-T) Floating vertically (FV) Floating horizontally (FH) Floating horizontally (FH)

Based upon the observational data, wou ld a fresh egg float in fresh, brackish, or ocean water? Explain . Use the Web to determine the saltiest natural body of water. What is its salt concentration? Will a fresh egg float in it?

10. Constructing scatter plots. In Chapter 6 learn about scatter plots, trends, and mathematical models. Use this knowledge and the data in question 9 to answer these questions: a. How are the mass of the salt and the mass of the salt solution related ? b. If 1 g of water has a volume of 1 ml what is the volume of the water used in the experiment? How are the mass of the salt and the volume of the water related?

11. Using algebra to represent patterns. In Volume 2 (Chapter 15) learn how mathematicians develop an equation of best f it for linear and non-linear models. Develop and interpret an equation of best fit for the scatter plots in question 10.

Chapter 2

Refining Experiments

57

REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Confrey, J., & Krupa, E. E. (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. ExploreLearning. (2015). Math & science gizmos. Charlottesville, VA. Retrieved from http://www. explorelearning.com/ IL & FS Education & Technology Services. (2010). Exploriments. Retrieved from http://www. exploriments.com Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and techn ical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_Standards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www.apsva.us/cms/lib2NA01000586/Centricity/Domain/29/ CTAE_Committee_Report.pdf University of Colorado Boulder. (2015). PhET interactive simulations-physics. Retrieved from https ://phet.colorado .edu/en/simulations/category/physics

CHAPTER

3 Analyzing an Experimental Design

CONTENTS Introduction Learning Objectives Correlations With Nationwide Standa rds

60 60 60

Constructing an Experimental Design Diagram Box 3-1 Practice-Experimental Design Diagram

62 63

Diagramming an Experiment Box 3-2 Experiment-Huff, Puff, and Slide

65

Assessing an Experimental Design Diagram Using a Checkl ist Box 3-3 Checklist- Experimental Design Diagram Comparing Assessments Box 3-4 Practice-Assessing Experimental Design Diagram

69 69 70 71 73

Designing Experiments With Multiple Independent Variables Repeated Measures Over Time Repeated Treatments of Subjects Two Independent Variables

77 77 78 80

Exploring STEM Connections Box 3-5 STEM Perspective- Huff, Puff, and Slide

81 83

References

87

67

59

60

Part One

Engaging in Experimentation

INTRODUCTION At this point you know the components of an experiment and what they mean. Suppose a scientist conducted an experiment which involved "amount of water." Then the scientist asked you: "Was the amount of water the independent variable, the dependent variable, a controlled variable, or the control group in the experiment?" What would you say? It's a tough question. In fact, it is impossible to answer the question given what you were told. The amount of water could be any of the choices depending on its role in the experiment. In Chapter 3, you will use a diagram to communicate the role of various components in an experiment. Also, you will use an expanded checklist to analyze the experimental design diagram and recommend improvements.

Learning Objectives Specific learning objectives for Chapter 3, Analyzing an Experimental Design, include: ►

Identify the major experimental components in a structured investigation or scenario: independent and dependent variables, question, hypothesis, control group, controlled variables, and number of repeated trials;



Develop an experimental design diagram to communicate the major experimental components;



Respectfully ask questions, provide feedback, and receive critiques; cite relevant evidence;



Use a checklist to evaluate and revise an experimental design diagram so better qualitative and/or quantitative data are generated to test a hypothesis; and



Use argumentation skills to compare assessments of an experimental design diagram.

Correlations With Nationwide Standards In Table 3-1, the core Chapter objectives and STEM concepts are correlated with nationwide learning standards. The correlations for "Exploring STEM connections" are shown in italics. For a synopsis see Appendix A.

Chapter 3 Analyzing an Experimental Design

TABLE 3-1

61

Correlations With Nationwide Standards

NEXT GENERATION SCIENCE STANDARDS ► Scientific & Engineering Practices:

Asking questions and def ining problems; Planning and carrying out investigations; Const ructing explanations and designing solutions; Using mathemat ics and computationa l th inking; Engaging in argument from evidence; Obtaining, evaluating, and communicating information

► Cross-Cutting Concepts:

Patterns; Cause and effect; Systems and system models

► Disciplinary Core Ideas:

Motion and stability; Energy; Heredity; Earth 's systems; Engineering Design; Links among engineering, technology, science, and society

COMMON CORE STANDARDS-MATHEMATICS ► Mathematical Practices:

Const ruct viable arguments and crit ique the reasoning of others; Model with mathematics

► Mathematical Domains:

Interpreting categorical and quant itative data; Expression and equations; Functions; Interpreting functions

COMMON CORE STANDARDS-LITERACY IN SCIENCE AND TECHNICAL SUBJECTS ► Reading:

Cit e textual evidence; Determ ine key ideas or conclusion; Follow mult i-step proced ure; Determine meaning of symbols, key terms, etc.; Integrate words and visual representations; Read and comprehend text

► Writing:

W rite argument s; Conduct short research projects; Gather relevant information; Draw information from informational texts

ISTE STANDARDS-STUDENTS ► Creativity and innovation:

Identify t rends and forecast possibilit ies

► Research and information fluency:

Process data and report results; Locate ... and use information from a variety of sources/media; Evaluate and select information sources and digital tools based on the appropriateness to specific tasks

► Critical thinking, problem solving, and decision making:

Collect and ana lyze data t o

ident ify solutions and/or make informed decisions ► Digital citizenship:

Demonstrate persona l responsibility for lifelong learning; Advocate and practice safe, legal, and responsible use of information and technology; Exhibit a positive attitude toward using technology that supports collaboration, learning, and productivity

► Technology operations and concepts:

Understand and use technology systems

Source: Confrey & Krupa, 2012, p. 9; Morphew, V. N., 20 11, pp. 299- 300; National Governors Association Center fo r Best Practices, 2010, English language & literacy, pp. 64-66; National Governors Associat ion Center for Best Pract ices, 20 10, Mathematics, pp. 6- 8; NGSS Lead St ates, 20 13, Volume 1, p. 1; NGSS Lead States, 20 13, Volume 2, pp. 67- 79.

62

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CONSTRUCTING AN EXPERIMENTAL DESIGN DIAGRAM Although lists can be useful tools of analysis, diagrams are frequently more powerful tools. For example, you can analyze an experiment by listing its components. However, constructing an experimental design diagram of the same experiment is a more effective way to quickly visualize the design of the experiment. To construct an experimental design diagram for an experiment with one independent variable follow these steps. 1. Write a testable question: Communicate what you want to learn about the effect of the independent variable on the dependent variable. 2. State a hypothesis: If the (independent variable) is (describe how you changed it), then the (dependent variable) will (describe the effect) because (state the reason). 3. Draw a rectangle and subdivide it into three rows. In the first row write the independent variable (IV). 4. In the second row, communicate the levels of the independent variable. To do this, subdivide the row into a column for each level of the independent variable. Write the specific levels of the independent variable (IV) above each of the columns. If one of the levels is used as the control group for the experiment, write the words control group under that level. 5. In the third row, communicate the number of repeated trials. Subdivide this third row into the same number of columns as the second row. In each column, write the number of repeated trials conducted for each level of the independent variable. 6. Put the dependent variable (DV) below the rectangle. 7. Write a list of controlled variables (CV). In Figure 3-1, the general format of an experimental design diagram is illustrated. Use Figure 3-1 to construct an experimental design diagram for the scenarios given in Box 3-1, Practice- Experimental Design Diagram. FIGURE 3-1

General Format for an Experimental Design Diagram

WRITE A TESTABLE QUESTION Communicate what you want to learn about the effect of the independent variable on the dependent variable. STATE A HYPOTHESIS If the independent variable is (describe change), then the dependent variable w ill (describe effect) because (state the reason). IV: Write the independent variable. Divide this row, and the one below it into columns, one for each level of the independent variable. Place the words control group below the standard of comparison. In each column, write the number of repeated trials conducted for each level of t he independent variable.

DV

Write the dependent variable.

CV

Write a list of controlled variables.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Experimental Design Diagram DIRECTIONS Read several of the scenarios and const ruct an experimental design diagram . Use the ava ilable information w it hin the scenario. 1. Zelda's friends were always ta lking about how smart their dogs were. Of course Zelda thought her Chihuahua, even though small, was the smartest. For a project , Zelda decided t o see if some breeds of dogs learn behaviors faster t han others. She used her Chihuahua, and asked her neighbors if she cou ld borrow a poodle, a German shepherd, a Saint Bernard, and a Fox Terrier. In the basement of her home, Zelda tried t o teach each dog to sit and shake hands using "Dawg Treats" as a reward. She gave each dog a 30-minute lesson. She repeated the lessons over f ive days. If the dog learned she recorded t he number of lessons required to teach the trick. If the dog never learned t he trick she recorded t hat.

2. Dion moved his trophies from his bedroom to t he basement den of his house. He not iced t he troph ies needed more dusting. Because people often came into t he basement from the yard and tracked dirt on the ca rpet, he thought if he put t he trophies on higher shelves there would be less dust. He cut fo urteen identical pieces of wax pa per, covered t hem all lightly with petroleum jel ly, and attached t he pa per to metal coat hangers. He hung two hangers so the bottom of t he paper was at 0, 0.3, 0.6, 0.9, 1.2, 1.5, and 1.8 m off the fl oor in t he hal lway. A week lat er he took t he hangers down. Holding t he greased wax paper in front of a bright light, he compared the amounts of dust collected at each height, e.g., small, mediu m, and large.

3. When studyi ng fossils in her Earth Science class, Casandra learned different fossils are deposited over t ime. She knew fossils were present in t he cliff behind her house, and thought the fossi ls might change as she went from the top to t he bottom of the bank because of changing lif e over t ime. She marked the bank at f ive positions: 5, 10, 15, 20, and 25 m from t he surface. She removed t hree buckets of soil from each of t he positions and determi ned the kind and number of fossils in each sample. Casandra w as an experienced rock climber and worked with her Dad t o follow saf ety precautions w hen collect ing the soil.

63

4 . Carlos read that seedl ings compete for light, water, and nutrients. This is why gardeners t hin seedlings to have good flowers. Carlos decided to test how close together the seeds could be planted before the plants were harmed. He bought some marigold seeds and potting soil and got 12 paper sa lad bowls of t he same size from his mom . Carlos punched four holes in the bottom of each bowl. Then, he f illed each bowl two-thirds full, wh ich took 350 ml of soil. In the first set of three bowls, he planted one seed in each of the bowls; this wou ld be the comparison. For each set of three bowls, he planted different numbers of seeds, e.g., 2, 4, and 8 seeds per bowl. Carlos placed the bowls in a tray in the w indow so the plants received the same light. Every three days he gave the plants t he same amount of wat er. After 25 days Carlos counted how many plants were in each container. He also measured t he plants' heights (cm) and described the plants as healthy or unhealthy.

5. Amanda wanted to determine if t he color of food affected what kindergarten st udents wou ld select. She put food coloring into four identical bowls of mashed potatoes. The colors were red, green, yellow, and blue. She also had a fift h bowl of natural mashed potatoes. Because an earl ier survey had shown red to be the st udents' favorite color she thought the students would select this color most often . Each st udent indicated their choice. Amanda did the experiment using a total of 100 students. She recorded the number of students choosing each color. (Notice, the students did not eat the potatoes.)

6. Lou read the ju ice of the Aloe vera plant promoted the healing of burned tissue. He decided to investigate the effect of varying the concentration of A. vera on the regeneration of planarian . Lou bisected planarian to obta in 10 parts (5 heads and 5 ta ils). For each experimental group, he applied concent rat ions of 0%, 10%, 20%, and 30% A. vera to the planarian parts. Fifteen milliliters of A. vera solutions were appl ied. Al l planarian were maintained in a growt h chamber w ith identical food, temperatu re, and humidity. Lou thought the higher concentration solutions would promote healing. On Day 15 Lou observed the regeneration of the planarian heads and tails; he categorized regeneration as full, part ial, or none.

64

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Chapter 3 Analyzing an Experimental Design

65

DIAGRAMMING AN EXPERIMENT Knowing how to construct an experimental design diagram is of little use unless you can apply these skills to an experiment you are conducting, whether in class or of your own design. To test your application skills conduct the investigation in Box 3-2, Experiment-Huff, Puff, and Slide.

66

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

EXPERIMENT Huff, Puff, and Slide

QUESTION

How far can I blow a cup?

HYPOTHESIS

Construct your own.

MATERIALS ►

Safety goggles



Long, flat , smooth surface (about 2 m)



Meter st ick



Plastic cont ainer, about 250 ml (8 oz)



Pennies, 1O

SAFETY ►

Wea r safety goggles and appropriate protective equipment.



If you have respiratory problems do not conduct th is experiment.



Wash hands aft er investigating.



Follow your teacher's directions for safety, clean ing the laborat ory area, and disposing of materials.



See Append ix B, Using Safe Procedures

PROCEDURE 1. Place two pennies in t he container. 2. Place you r ch in on one end of the smooth su rface. Place the container 15 cm from your ch in. 3. Blow as hard as you can on the side of the container. Measure how far the container sl ides in centimeters. Record you r data. 4. Repeat steps 1- 3 with 4, 6, and 10 pennies in the container.

67

DATA TABLE Number of Pennies

Distance Moved (cm)

2 4 6

10

ANALYZING THE EXPERIMENT 1. Const ruct an experimental design diag ram fo r Huff, Puff, and Slide.

2. Describe ways you ca n improve t he experiment.

3. What is your conf idence in the experimenta l data? How could you mod ify t he experimental design to im prove confidence in the data?

68

Chapter 3 Analyzing an Experimental Design

69

ASSESSING AN EXPERIMENTAL DESIGN DIAGRAM In your analysis of the Huff, Puff, and Slide investigation, you constructed an experimental design diagram. How does your experimental design diagram compare with ours, which is shown in Figure 3-2? FIGURE 3-2

QUESTION

Experimental Design Diagram for Huff, Puff, and Slide How far can I blow a cup?

HYPOTHESIS If the number of pennies is increased, then the distance the cup will slide will decrease because it has a greater mass. IV: Number of Pennies 2 Pennies 1 Trial

4 Pennies 1 Trial

6 Pennies 1 Tria l

10 Pennies 1 Trial

DV Distance conta iner sl ides (cm) CV Size of container Shape of container Slide surface

Using a Checklist From the experimental design diagram you can spot the missing parts quickly and easily. For example, there is no control group designated in the experiment. Other components may be present, but of poor quality. To assess the quality of experimental components it is helpful to use a checklist. In Box 3-3, the checklist from Chapter 2 was expanded to include questions about the experimental design diagram, creativity, and complexity of the proposed experiment. Use the checklist in Box 3-3 to review the Huff, Puff, and Slide experiment. Then, compare your analysis with ours.

xperimental Design Diagram SELF CHECK

EXPERIMENTAL COMPONENT

PEER CHECK

POINT VALUE

QUESTION 1 . Is there a question?

3

2. Does the question communicate what you want to learn about the interaction of the IV and DV?

6

HYPOTHESIS 3. Is there a hypothesis?

3

4. Does t he hypot hesis clearly st ate how changing the IV will affect the DV?

6

5. Does t he hypot hesis state the reason for the prediction?

3

6. Is a direct ional hypothesis written? If not, is a reason provided for t he non-directional hypothesis?

6

INDEPENDENT VARIABLE 7. Is there just one IV? Operationally defined?

9

8. Are the levels of the IV clearly stated ? Operationally defined?

9

DEPENDENT VARIABLE 9. Is there one or more DV? Operationally defined?

9

CONTROLLED VARIABLES 10. Does t he list of CV include the major factors t hat might impact the experimental out come?

6

11. ls each of the identified CV operat ionally defined?

3

CONTROL GROUP 12. ls t here a control group? Operationally defined?

9

REPEATED TRAILS 13. A re there repeated trials?

6

14. Are there a sufficient number of repeated trials?

3

EXPERIMENTAL DESIGN DIAGRAM 15. Are the components placed in the proper place?

6

16. A re any components missing?

3

CREATIVITY AND COMPLEXITY 17. ls t he experimental design creative?

5

18. ls the experimental design at an appropriate level of complexity?

5

TOTAL COMMENTS

70

100

GRADE

Chapter 3 Analyzing an Experimental Design

71

Comparing Assessments With the checklist you identified strengths and weaknesses of the experiment, which may be different from ours. By comparing assessments you can develop a stronger set of recommendations for improving the Huff, Puff, and Slide experiment. Question. The question-"How far can I blow a cup?"-is too general. The question needs to focus on the variables being investigated, e.g., "How does the number of pennies impact the distance a cup will slide?" Hypothesis. The hypothesis is already stated in an "if . . ., then ... because . . ." format and

requires no change. Independent Variable. The independent variable, number of pennies, is correct. The unit of mass in this experiment is the mass of a U.S. penny which is approximately the same for all pennies. To be more precise you could measure the mass of the pennies using units such as grams. The levels are clearly stated, but the sequence of 2-4-6-10 pennies is missing the level of 8 pennies. The levels of the independent variable are usually set at equal intervals or multiples, such as 2-46-8-10 pennies. Dependent Variable. This variable is the distance traveled (cm). Using the metric unit (cm)

to operationally define distance is appropriate. One improvement would be to state which path you measured: a straight line or the actual path the container took. Controlled Variables. The controlled variables could be stated more clearly. You could

describe the type of smooth surface, perhaps a polished wooden table, stone countertop, or a linoleum floor. Likewise, describe the type of container, such as a clear plastic cup (250 ml) or a specific brand and size of margarine container (Golden Glow, 250 ml). Tell where to aim the air stream, at the base or the middle of the container. Indicate if the container was covered or uncovered. Control Group. A zero (0) pennies level of the independent variable should be added and

labeled as the control group. This would be a no treatment control group. Repeated Trials. There is a problem here! Only one trial was done. When you conduct repeated

trials you test each level of the independent variable several times. A major way to improve this experiment would be to add around five trials. Remember, repeated trials are used to reduce the effects of chance errors and to increase confidence in the findings. Because the data are quantitative calculate the mean. Experimental Design Diagram. The control group is missing. The other components are shown in the appropriate place (see Figure 3-1). Creativity and Complexity. Deciding upon creativity and appropriateness are "judgment calls" on your part. Creativity means novel and appropriate outcomes are presented. These could

be a novel topic for the experiment, an unusual hypothesis, or unique ways the independent, dependent, and controlled variables are defined. In the following chapters, we will discuss how creativity can be demonstrated in various experimental components.

72

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For an experiment to be appropriate, it should address a question whose answer is unknown to the investigator. Determining the effect of different colors of ground covers on plant growth is an appropriate experiment, whereas determining the effect of light versus no light on plant growth is not. Almost everyone knows plants will die without light. In determining appropriateness consider the experimenter's background knowledge. An appropriate experiment for a sixth grader is not an appropriate experiment for a high school senior. Huff, Puff, and Slide may be an appropriate experiment for a middle school student who needs to better understand the relationships among force, mass, and distance traveled. However, an older student would need to explore more complex relationships, including derived dependent variables such as velocity, acceleration, and kinetic energy. For the independent variable, older students could investigate factors such as the position of the mass in the cup or the direction of the force on the cup. As you can see, using a combination of an experimental design diagram and checklist is an effective way to analyze and improve an experiment. Use the checklist to assess the experiments in Box 3-4, Practice-Assessing Experimental Design Diagram.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Assessing Experimental Design Diagram DIRECTIONS Use the checkl ist from Box 3-3 to assess several of the experimental design diagrams below, or ones assigned by your teacher. For your conven ience, a checklist follows the designs. For each scena rio summarize ways t o improve t he experimental design.

Scenario 1: QUESTION

Compost and Bean Plants

Does age impact the nutrient content of compost?

HYPOTHESIS If older compost is applied, then the bean plants will grow taller because more nutrients are available. IV: Age of Compost

3-Month-old Compost 6-Month-old Compost 25 plants 25 plants

No Compost (control group) 25 plants

DV Height of plants (cm) CV Type of compost-g rass Bean plants Amount of compost-450 g Same sunl ight conditions Same water every 2 days Time to grow-30 days WAYS TO IMPROVE

Scenario 2: QUESTION

Depth and Water Pressure

How does depth impact water pressure?

HYPOTHESIS If the depth of the hole is increased, then the distance squirted will increase. IV: Depth of hole below surface (cm)

5cm 3 cartons

10 cm 3 cartons

15cm 3 cartons

20 cm 3 cartons

DV Distance liquid squirted (cm) CV Identical paper milk cart ons Height of liquid in conta iner-30 cm Liquid- water WAYS TO IMPROVE

73

74

Part One

Engaging in Experimentation

Scenario 3: QUESTION

Effectiveness of Insulation

l

Does brand impact the effectiveness of insulation?

HYPOTHESIS If jars of water are wrapped with different brands of insulation, then the temperature of the water in the jars will change by different amounts.

~

0 I

'

IV: Brand of Insulation Lowes TM

Home Depot TM

Smith Builders

Discount Building Supplies

Green Contracting Company

1 jar

1 jar

1 jar

1 jar

1 jar

DV Temperat ure of water in jar

CV Jars all ½ f ull Jars placed in direct sunlight fo r 4 hr Jars fitted w ith plastic lids

WAYS TO IMPROVE

Scenario 4: Metals and Rusting Iron QUESTION

How do active metals impact the rusting of iron?

HYPOTHESIS If the chemical activity of the metallic wrapper is increased, then less rusting will occur because the acid will react with the wrapper.

IV: Type of Metallic Wrapping Strip Iron Nail with No Metal (control group)

Iron Nail with Magnesium

Iron Nail with Aluminum

Iron Nail with Lead

6 nails

6 na ils

6 nails

6 nails

DV Amount of rusting (small, moderate, large) Color of water

CV Plastic cup-250 ml Amount of water-200 ml Type of na il-galvanized iron nail, 15.2 cm Dimensions of metal lic w rapper-5 cm x 22 cm Length of experiment-2 weeks

WAYS TO IMPROVE

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Chapter 3 Analyzing an Experimental Design

75

Scenario 5: Dropping Magnets QUESTION

Does dropping harm a magnet?

HYPOTHESIS The more times a magnet is dropped the fewer iron filings it will pick up because my teacher said dropping harms magnets. IV: Number of Times Magnet Dropped 5 drops

10 drops

15 drops

10 magnets

10 magnets

10 magnets

DV Mass of iron filings picked up (g) CV Craft bar magnets, 30 of same brand Height dropped- 1.5 m Type of floor- cement WAYS TO IMPROVE

Scenario 6: Perfumed Bees QUESTION

c'

j ~

Do perfumes worry bees?

HYPOTHESIS If the perfume contains an ester, then the bees will fly more around the hive because they are agitated by the chemical. IV: Type of Perfume Perfume 1 (Wooden Glade) 4 trials

Ff]•~~

Perfume 2 (Meadow)

Perfume 3 (Eastern Spice)

4 trials

4 tria ls

DV

Time to emerge from hive (min) Flight pattern observed over 15 min

CV

Amount of perfume- 10 ml Distance from the hive- 3 m Container for perfume- clear plastic plate Placement of container- grass Same weather conditions-air temperature and wind Recovery time between tria ls-30 min WAYS TO IMPROVE

~E

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~ SSESSMENT Scenarios of Experimental Designs SELF CHECK

EXPERIMENTAL COMPONENT

PEER CHECK

POINT VALUE

QUESTION 1. Is there a question?

3

2 . Does t he quest ion communicate what you want to learn about t he interaction of t he IV and DV?

6

HYPOTHESIS 3. Is there a hypothesis?

3

4. Does t he hypothesis clearly state how changing the IV wil l affect the DV?

6

5. Does t he hypothesis state the reason for t he prediction?

3

6. Is a directional hypothesis written? If not, is a reason provided for t he non-directional hypothesis?

6

INDEPENDENT VARIABLE 7. Is there just one IV? Operationa lly defined?

9

8. A re the levels of the IV clea rly st ated? Operat ionally defined?

9

DEPENDENT VARIABLE 9. Is there one or more DV? Operationa lly def ined?

9

CONTROLLED VARIABLES 10. Does t he list of CV include t he major factors that might impact the experimental out come?

6

11 . Is each of the identified CV operationa lly defined?

3

CONTROL GROUP 12. Is there a cont rol group? Operationa lly defined?

9

REPEATED TRAILS 13. Are there repeat ed t rials?

6

14. Are there a sufficient number of repeated trials?

3

EXPERIMENTAL DESIGN DIAGRAM 15.A re the components placed in the proper place?

6

16. A re any components missing?

3

CREATIVITY AND COMPLEXITY 17. Is the experimental design creative?

5

18. ls the experimental design at an appropriate level of complexity?

5

TOTAL COMMENTS

76

100

GRADE

Chapter 3 Analyzing an Experimental Design

77

DESIGNING EXPERIMENTS WITH MULTIPLE INDEPENDENT VARIABLES The first part of this chapter focused on experiments involving one independent variable. However, scientists do not always confine themselves to one independent variable. Experiments may include repeated measurements and two or more variables. Once you have experimented with one independent variable, you may find you need to design a more complex experiment to test a hypothesis. This chapter component will provide a basis for designing and diagramming more complex experiments.

Repeated Measures Over Time A typical change to experiments with one independent variable is to obtain multiple measures of the dependent variable over time. An experiment to determine the influence of earthworms on soil quality would be enhanced by reporting results weekly, rather than at the end of a twomonth period. Similarly, the influence of aerobic exercise on resting pulse rate can be more accurately assessed with monthly measurements, rather than one measurement at the end of the year. This design is particularly effective when different effects over time are hypothesized. One fertilizer may act more quickly than another to promote plant growth, yet they may produce equivalent growth at six weeks. To understand how an experimental design diagram would be produced for an experiment involving repeated measures over time, look at a scenario involving crickets. Scenario. Juan read bees were attracted to certain colors and wondered whether crickets also had a color preference. He hypothesized crickets would be attracted to the brightest color, red. He divided an aquarium into four sections; the sections contained a red, blue, green, and no plate. Juan put 2 g of mustard seeds in each dish. Then, he put 30 crickets into the aquarium. He observed the number of crickets in each section at the end of 30, 60, 90, and 120 min. Also, Juan recorded the mass of mustard seeds (g) consumed at the end of 120 min. He repeated the experiment on five different days and was careful to keep the amount of light the same. In this experiment there are two independent variables-color of dish and time. Also, there are two dependent variables: the number of crickets, which is recorded at specific times, and the mass of mustard seeds consumed, which is measured only at the end of the experiment. In this experimental design, one independent variable is shown on the side and the second independent variable across the top (see Figure 3-3). Although these variables can be switched, we prefer to put time across the top. This preference is related to how graphs are constructed, which will be discussed in Chapter 6. In this experiment, a graph would typically have time on the x-axis, the number of crickets on the y-axis, and multiple trends to represent the number of crickets in each section of the container.

78

Part One

Engaging in Experimentation

FIGURE 3-3

QUESTION

Attraction of Crickets to Color

Are crickets attracted to different colors?

HYPOTHESIS If crickets are fed from different colored plates, then they will be more attracted to a red plate, which is brighter. IV: Color of dish

IV: Time (min) 30 min

60 min

90 min

120 min

None (control group)

5 t rials

5 t rials

5 trials

5 t rials

Red

5 t rials

5 t rials

5 trials

5 t rials

Blue

5 t rials

5 t rials

5 trials

5 t rials

Green

5 t rials

5 trials

5 trials

5 t rials

DV Number of crickets in each section at 30, 60, 90, 120 min Tota l mass of mustard seeds (g) eaten from each plate at 120 min

CV Kind of seeds-mustard Amount of seeds-2 g Number of crickets put in aquarium- 30 Same aquarium Same amount of light

Repeated Treatments of Subjects As discussed earlier, substantial variation exists among living organisms, especially humans. By exposing the same subjects to different treatments you can minimize experimental errors resulting from variations within subjects. Repeated treatment designs are particularly effective in psychological and biological studies involving higher organisms. For example, the most effective time for learning could be investigated by determining sixty subjects' rate of learning of nonsense syllables at three different times during the day. With a repeated treatments design each subject serves as his or her own control. Thus, genetic and environmental factors are minimized. Because nonliving matter exhibits less variation, repeated treatment designs are less common in the physical and earth sciences. Any time humans or other vertebrates are used in an experiment the researcher must follow specific guidelines, which are generally described in Chapter 9, Analyzing and Addressing Safety Risks. To understand how an experimental design diagram would be constructed for repeated treatments over subjects, analyze a scenario involving performance on mathematics tests. Scenario. Although Sienna's classmates learned the advantages of studying in a quiet place and focusing on the task, the majority of students continued to complete homework while listening to music or watching television. Sienna hypothesized that the ability to

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solve mathematical problems would decrease with increased stimuli in the environment. Sienna taped a 30-min segment of a television program which included a mix of conversation, music, and screen action. She developed four equivalent mathematics tests (20 items) on decimals and percentages. Fifteen students were randomly selected from her class and appropriate permissions were secured for each student. Students completed a mathematics tests while exposed to no stimuli, to a sound tape of the program, to a video with no sound, and to a complete tape of the program. The form of the mathematics test, type of stimuli, and order of presentation of the stimuli were randomized. The time for completion (min) and the number of correct items were recorded. The tests were administered over four days, at the same time of day, and in identical test sites. The sound level of the auditory stimuli and the screen size of the visual stimuli remained constant. This design looks similar to the ones constructed previously for one independent variable. The independent variable, type of stimuli, is placed across the top. However, on the side you communicate the number of subjects, which is the number of repeated trials. Because each subject is tested four times with different stimuli there are four repeated measures. This diagram is shown in Figure 3-4, External Stimuli and Problem Solving.

FIGURE 3-4 QUESTION

External Stimuli and Problem Solving

How do different stimuli affect mathematical problem solving?

HYPOTHESIS If the number of stimuli increases, then performance on a mathematics test will decrease because of reduced focus on the task. IV: Type of Stimuli Subjects

None (control group)

Sound

Video Without Sound

2 3

15 DV Time to complete test (min) Number of test items correct

CV Length and difficulty of test Length of st imul i Presentation of stimuli- sa me sound level and screen size Time and place of test administration

Video With Sound

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Two Independent Variables When physicians prescribe medication they give specific directions for talcing the medicine. These directions reflect numerous experiments over the years which have shown certain medicines are more effective at specific times of day, taking a medicine with food will minimize side effects, and certain foods will interfere with medical effects. For example, people who take cholesterollowering drugs are generally directed not to eat grapefruit. When two variables influence an outcome, scientists say the variables are interacting. If you take a drug at the recommended time, then a lower dosage may be used. However, if you take the drug at another time, a higher dosage may be required to achieve the same effect. Both the time of day and the dosage interact to impact the drug's effectiveness. If you were interested in the impact of thermal and acid rain pollution on the respiratory rate of

fish, you could conduct two different experiments. For the first experiment, you could investigate the impact of acid rain pollution by using simulated acid rain with different pH values such as 4.5, 5.5, and 6.5. Then, you could conduct a second experiment to investigate the impact of different temperatures of water (10°, 20°, 30°, 40° C) on respiratory rate. These multiple or serial experiments would enable you to learn the impact of acid rain and thermal pollution separately. However, they would not enable you to investigate the potential interaction of these variables. That is, does one variable interact with a second variable to reduce or increase the impact? To see how interaction works, analyze an experiment involving the impact of two independent variables-UV light and acid rain-on the durability of paint.

Scenario. Larry read that acid rain and sunlight cause paint to fade faster. Larry wanted to learn how these variables impacted the fading of Chromo-Sure yellow paint (color 216). In the experiment, he exposed five samples of painted wood to a combination of different amounts of ultraviolet light (5, 10, 15 units) and different strengths of simulated acid rain (pH= 3, 5, 7). For each combination he used five samples (3 cm x 3 cm) of wood, which he had painted with one coat of the yellow paint. For the different UV exposures he used three lamps of the same brand. He used 20 ml of the acid rain solution. After two weeks of exposure, he estimated the amount of fading by comparing the paint samples with an original sample. He described the fading as none, small, medium, or large. When there are two independent variables, one independent variable is shown across the top and the second independent variable along the side. Because time is not involved, as with the cricket experiment, there is no convention regarding the placement of the variables. The number of repeated trials is shown within each of the resulting boxes. Larry's experimental design diagram is shown in Figure 3-5, Fading of Paint.

Chapter 3 Analyzing an Experimental Design

FIGURE 3-5 QUESTION paint?

81

Fading of Paint Do acid rain and ultraviolet radiation interact to impact the fading of house

HYPOTHESIS If paint is exposed to higher acidic rain and ultraviolet radiation, then the variables will interact to produce a great amount of fading. UV Light Strength (units)

pH of Simulated Acid Rain 3

5

7

5

5 t rials

5 tria ls

5 trials

10

5 t rials

5 tria ls

5 trials

15

5 t rials

5 tria ls

5 trials

DV Amount of fad ing (rating scale of none, sma ll, medium, large)

CV Brand and color of pa int-Chroma-Sure yel low, #216 Size of samples-3 cm x 3 cm Same brand of UV lamp Amount of acid rain-20 ml 2 weeks of exposure

EXPLORING STEM CONNECTIONS You know how important we think it is for you to make connections among various scientific disciplines, mathematics, technology, and engineering. In Box 3-5, STEM Perspective- Huff, Puff, and Slide, some options are described. As before, select among the options, complete a teacher assigned investigation, or identify a topic you want to explore.

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STEM PERSPECTIVE Huff, Puff, and Slide

Science Explaining how the natural world works

1. Forces, interactions, and energy. Explore the following connections. Then, use key scient if ic concept s to explain t he experimental findings. a. Make a diagram to communicate t he energy changes occu rring in the Huff, Puff, and Slide experiment. b. What is Newton's Second Law of Motion? How does t he law relat e to the experiment? c. For Newton's Second Law of M otion, t here are on line si mulations where you can

explore the effect of changing the variables of force, mass, and accelerat ion. To conduct a simulated experiment, search for sit es such as: Exploriments-Newton's Second Law; Mat h & Science Gizmos- Fan Physics (free trial); and PhET Interactive Simulations-Forces and Motion and Forces and Motion: Basic.

2. Planning investigations. Was the air flow well controlled in the experiment? Explain. What tools might you use to provide the air fl ow? What instru ments might you use to measure the air flow? (Hint: think how meteorologists measure w ind speed) 3. Systems and system models. W hat are t he major components of the respiratory system? How were these component s involved when you blew on the cup? 4. Heredity: Inheritance and variation of traits. What genetic and environmental factors impact a person's lung capacity? How do these factors interact? 5. Earth's systems. Meteorologist s report wind measurements. Explain why knowledge of the w ind is important.

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Technology and Engineering Modifying the world to meet human needs and wants 6. Engineering design. In Chapter 8, apply your knowledge of force and motion to design ing a wind operated device. See Box 8-4, Wind Power. 7. Links among engineering, technology, science, and society. Explore the following connections. a. Wind farms are a form of renewable energy. How does the use of wind energy in the United States compare w ith its usage in other parts of the world? What geographical and societal factors underlie these differences? b. For disabled people devices exist they can operate with their breath . What are some recent innovations?

Chapter 3 Analyzing an Experimental Design

Mathematics Describing, analyzing, and interpreting patterns and relationships

8. Collecting additional data. In Huff, Puff, and Slide, you experimented with blowing a container wit h various numbers of pennies to see how far the container wou ld slide. a. Finding the control group value. When analyzing t his experiment you found you did not col lect information for t he control group. Using t he same container collect t his dat a. To maintain the controlled variables, be sure to use t he same su rface and blowing technique. b. Finding the missing level of the independent variable. It is better t o use set intervals fo r increment ing t he levels of the independent variable. When ana lyzing the experiment you found the level of eight pennies was missing. Using the same controlled variables collect th is dat a.

9. Detecting mathematical patterns. In t he t able below, record your new dat a from quest ion 8, as well as the original data from the Huff, Puff, and Slide experiment. Number of Pennies

Distance Moved (cm)

0

2 4 6

8 10 a. Relationship of pennies and distance traveled. Use words to describe the relationship between these variables. Sket ch a graph to illustrat e the features. Do the data support or refute the hypothesis you made? b. Use a graph to make a prediction. What do you think w ill happen if you continue to increase the number of pennies in the conta iner? What value wi ll the distance (cm) approach as you add more and more pennies to the container?

c. One more level of the independent variable. Use your graph to predict how many pennies you w ill need to place in the container for the conta iner to no longer move when you blow on it. Collect data to test your prediction. Remember to keep the controlled variables the same. How do the pred iction and data compare?

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10. Constructing scatter plots. In Chapter 6 learn about scatter plots, trends, and mathematical models. Construct and interpret scatter plots for your experimental data or the data in question 9. 11.Using algebra to represent patterns. In Volume 2 (Chapter 15) learn about linear and non-linear mathematical models. Use what you learn to explore the relationship between the number of pennies (or mass) and the distance moved. 12.Adding time as a dependent variable. In the experiment you measured the distance traveled. By col lecting another variable- time- you can explore other aspects of motion such as the velocity and acceleration of the cup when it contained different numbers of pennies. How cou ld you use the capabi lities of digital technology to measure time? Once you have this data how can you calculate the cup's average velocity? Acceleration?.

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REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Confrey, J., & Krupa, E. E. (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. ExploreLearning. (2015). Math & science gizmos. Charlottesville, VA. Retrieved from http://www. explorelearning.com/ IL & FS Education & Technology Services. (2010). Exploriments. Retrieved from http://www. exploriments.com Morphew, V. N. (2011 ). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_Standards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www.apsva.us/cms/lib2NA01000586/Centricity/Domain/29/ CTAE_Committee_Report.pdf University of Colorado Boulder. (2015). PhET interactive simulations-physics. Retrieved from https ://phet.colorado .edu/en/simulations/category/physics

CHAPTER

4 Experimenting Precisely

CONTENTS Introduction Learning Objectives Correlations With Nationwide Standards

90 90 90

Writing a Procedure for a Task

92

Writing an Experimental Procedure Box 4-1 Experiment-Sudsational Experience Adding Details to a General Procedure Box 4-2 Practice-Writing a Precise Procedure

93 95 97 99

Moving From Experimental Design Diagram to Procedure Box 4-3 Practice-Experimental Designs and Procedures

101

Assessing a Procedure Box 4-4 Checklist-Procedure Comparing Assessments

107 108 110

Exploring STEM Connections Box 4-5 STEM Perspective-Sudsationa/ Experience

111 113

References

117

105

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INTRODUCTION Every day you follow procedures. However, you probably do not use the term procedure. Instead, you say you followed the teacher's instructions for submitting homework online, your coach's directions for completing a drill, or your mom's recipe for making spaghetti. Regardless of the term you use-instructions, directions, or recipe-you were following a procedure, which is simply a precise set of steps for completing a task. When details, however obvious, are left from a procedure a person will substitute their own way of doing the omitted step. Even minor variations can have drastic effects on the outcome. For example, substituting eggs from the refrigerator for room temperature eggs can impact the outcome of a cupcake recipe. In Chapters 1 to 3, the experiments included a procedure. In this chapter you will learn to write and improve procedures through discussions with your classmates.

Learning Objectives Specific learning objectives for Chapter 4, Experimenting Precisely, include: ►

Write a clear and precise description of steps-a procedure-for completing a task;



Improve a general procedure from a science text or other media by adding detailed information from a list of available materials;



Write a clear, precise procedure for an experiment using an experimental design diagram and a list of available materials and tools;



Respectfully ask questions, provide feedback, and receive critiques about one's experimental procedures by citing relevant evidence;



Use a checklist to evaluate and improve experimental procedures for clarity, precision, safety, and accuracy of data; and



Use argumentation skills to compare assessments of a procedure.

Correlations With Nationwide Standards In Table 4-1, the core chapter objectives and STEM components are correlated with nationwide learning standards. The correlations for "Exploring STEM Connections" are shown in italics. For a synopsis see Appendix A.

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TABLE 4-1

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Correlations With Nationwide Standards

NEXT GENERATION SCIENCE STANDARDS ► Scientific & Engineering Practices:

Aski ng questions and defining problems; Planning and carrying out investigations; Engaging in argumentation from evidence; Analyzing and interpreting data; Using mathematics and computational thinking; Constructing explanations and designing solutions; Obtaining, evaluating, and communicating information ► Cross-Cutting Concepts: Patterns; Cause and effect; Structure and function ► Disciplinary Core Ideas: Matter and its interactions; From molecules to organismsstructures and processes; Earth's systems; Engineering design; Links among engineering, technology, science, and society

COMMON CORE STANDARDS-MATHEMATICS ► Mathematical Practices:

Construct viable arguments and critique the reasoning of others; Attend to precision ► Mathematical Domains: Interpreting categorical and quantitative data; Ratios and proportional reasoning

COMMON CORE STANDARDS-LITERACY IN SCIENCE AND TECHNICAL SUBJECTS ► Reading:

Cite textual evidence; Determine key ideas or conclusion; Follow multi-step procedure; Determine meaning of symbols, key terms, etc.; Read and comprehend text; Compare and contrast information from known sources ► Writing: Write argu ments; Write information/explanatory texts; Produce clear and coherent writing; Develop and strengthen writing; Gather relevant information; Write routinely over extended time frame; Conduct short research projects; Draw information from information texts

ISTE STANDARDS-STUDENTS ► Creativity and innovation:

Apply existing knowledge to generate new ideas, products, or processes; Create orig inal works as means of personal or group expression; Identify trends and forecast possibilities ► Communication and collaboration: Contribute to project teams to produce original works or solve problems ► Research and information fluency: Plan strategies to guide inquiry; Process data and report resu lts; Locate . .. use information from a variety of sources; Evaluate and select informational sources and digital tools based on the appropriateness to specific tasks ► Critical thinking, problem solving, and decision making: Plan and manage activities to develop a solution or complete a project; Collect and analyze dat a to identify solutions and/or make informed decisions ► Digital citizenship: Demonstrate persona l responsibility for lifelong learning; Advocate and practice safe, legal, and responsible use of technology; Exhibit a positive attitude toward using technology that supports collaboration, learning, and productivity Source: Confrey & Krupa, 2012, p . 9; Morphew, V. N., 20 11, pp. 299- 300; National Governors Associatio n Center for Best Pract ices, 20 10, Eng lish language & literacy, pp. 64- 66; National Governors Associat io n Center for Best Pract ices, 20 10, Mathemat ics, pp. 6- 8; NGSS Lead States, 2013, Volume 1, p. 1; NGSS Lead States, 20 13, Volume 2, pp . 67- 79.

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WRITING A PROCEDURE FOR A TASK In school you have used a variety of scientific tools to observe, measure, and conduct investigations. Initially, the teacher may have given you directions-a procedure-to follow. Assume a new student has entered your class and your teacher has asked your lab group to teach the student a familiar task such as: ►

Measure a specific volume of a liquid, such as 35 ml of water, with a graduated cylinder;



Measure 15.5 g of a solid, such as sand, with a triple-beam balance (non-electronic);



Determine the volume of a regular object, such as a block of wood;



Determine the volume of an irregular object, such as a rock or mineral;



Use a microscope to look at a prepared slide, such as purple onion cells;



Make a microscope slide, such as one of Elodea cells;



Measure the length of a crooked plant stem in centimeters;



Use a temperature probe to measure changes over a 30 min interval; and



Use a common set of objects to determine the approximate hardness of a mineral, e.g., fingernail, penny, iron nail, glass slide, steel file, bathroom tile (unglazed back side), and piece of quartz.

Your task is to write a procedure the new student can follow. To begin, assume you can use words only to communicate how to perform the task. No diagrams, photos, or videos allowed at this time. Appropriate use of images will be discussed later. Divide into a group of two to four students. If you are working at home, a family member or friend can be part of your group. Select a task to communicate to the new student-either one of the above examples or another task, even a non-science one, your team members know how to do. Are you ready to start writing? Probably not! The fear of the blank page or computer screen has paralyzed many writers. So, we will take a different approach which involves several steps where you work alone, as well as with a group, to develop a strong procedure. The time required to go through these steps will depend upon the complexity of the task-select a simple task initially. 1. Working alone, visualize doing the task. Yes, "mind pictures" are allowed. Then, write bullet points of the major steps. 2. Working in pairs, compare your bullet points. Through discussion you may find missing steps. If so, add bullet points to your lists. 3. Working alone, write a list of steps-a procedure-for the task. Use sentences, but do not be over-concerned about spelling and punctuation. You can revise later. Your current focus is to communicate the procedure precisely. 4. Working in pairs, compare your written procedures. Do they include all steps? All materials? Are safety procedures included? Help each other identify needed improvements.

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5. Working alone, edit your procedures including spelling and grammar. 6. Share your procedure with a larger group-perhaps another lab group or the class-and receive feedback. Respectfully answer questions the reviewers may have. In some cases, the reviewers may have missed a detail you provided. If so, be sure to clarify where it is included in your procedure. In other cases, you may have made inferences and need to be more precise.

Now that you have written a procedure, you have a better understanding of the value of clear and precise directions. Also, we hope you realize the benefits of discussing and sharing ideas. The more feedback you receive, and incorporate, the more effective a procedure will be.

WRITING AN EXPERIMENTAL PROCEDURE There are lots of different cleaning products around your home-one for the dishwasher, one for washing your clothes, one for washing dishes by hand, and, of course, many different products for washing your body. Sophia's chore was to load the dishwasher each night. One night, the box of Super Dishwasher Detergent was empty and Sophia thought, "OK, what difference does it makedirty dishes, dirty clothes? I'll just put some Bright Clothes Cleaner in the dishwasher." Later, she had a surprise-suds all over the floor. Is there a reason why different cleaners are recommended for different uses? Is suds formation a factor? To answer these questions, conduct the investigation in Box 4-1, Sudsational Experience.

94

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

EXPERIMENT Sudsational Experience QUESTION

Do different cleaning products produce different amounts of suds?

HYPOTHESIS

Construct your own.

MATERIALS ►

5 graduated cyl inders, 100 ml

SAFETY ► Wea r chem ical splash saf ety goggles and

appropriate protective clothing.

► Plastic wrap ► Rubber bands ►

Met ric measuring spoon

► Eyedropper ►

Tap water



Different liquid cleaners such as dishwashing, dishwasher, clothes cleaning, body wash, ca rpet cleaner



Met ric ruler



Scissors



Do not taste solutions.



Wash hands aft er investigating.



Follow you r instructor's direct ions for safety, clean ing the laborat ory, and disposing of materials.



See Append ix B, Using Safe Procedures

PROCEDURE 1. Get five graduat ed cylinders. Put water in each cylinder. 2. Add a different cleaner to each of the graduated cylinders 3. Seal the top of each graduated cylinder w ith a piece of plastic wrap and put a rubber band around the plastic wrap to hold it tight. 4 . Shake each graduated cylinder. 5. Measure t he amount of suds produced above the water line. 6. Record t he data. 7. Ana lyze the data.

95

DATA TABLE Cleaner

Height of Suds

Dishwasher Dish washing Clot hes Body Ca rpet

ANALYZING THE EXPERIMENT 1. To conduct the experiment you made a nu mber of decisions-t he amount of water and soap, the number of shakes, and how to measure the amount of suds. Revise t he procedure to include decisions you made when conducting the experiment.

2. Compare your group's procedure wi t h another grou p's procedu re. How can you use the com parison to develop a clearer, safer, and more precise procedure?

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Adding Details to a General Procedure Earlier you wrote a procedure for a task, such as measuring the volume of a liquid with a graduated cylinder. You began by visualizing or making a mental image of how you would complete the task. For the Sudsational experiment, we did the visualization for you and gave you a general sequence of steps to follow. As you conducted the experiment, you realized details were missing. You had to make inferences and decisions. As we read each step of the general procedure, we asked questions and made decisions.

Step 1: What size graduated cylinders are available? What amount of water will we use? What type of water will we use? We used a JOO ml graduated cylinder and 50 ml of tap water.

Step 2: What specific brands of the various cleaners are available? How much of each cleaner will we use? We used one drop of each of the following types and brands of cleaners: dish washing (Palmolive), dishwasher (Crystal Gel), clothes (Tide), body wash (Suave), and carpet (Hoover).

Step 3: How large a piece of plastic wrap will we use? Where will we put the rubber band? We decided to use a 15 cm x 15 cm piece of plastic wrap and to wrap the rubber band at the 100 ml mark. We did not know the brand of the plastic wrap.

Step 4: How will we shake the cylinder? How long will we shake? We decided to shake the cylinder up and down over a distance of about 15 cm for 30 s.

Step 5: What unit will we use to measure the height of the suds. We decided to measure the height in millimeters.

Step 6: Will we do more than one trial? If so, how do we modify the data table? We decided to use three trials and to modify the data table by adding two columns and a unit of measurement (mm)for the height of the suds.

Step 7: Will we use the mean or mode? We will calculate the mean because height (mm) is quantitative data. You may have made different decisions. That is fine. The important thing is to revise the procedure so it is clear to other experimenters. Using the decisions we made, here is how we modified the procedure. 1. Get five graduated cylinders ( 100 ml). Put 50 ml of tap water in each cylinder. 2. Add 1 drop of the dishwashing liquid (Palmolive) to a graduated cylinder. Then, add one drop of each cleaner to each of the other graduated cylinders, e.g., dishwasher (Crystal Gel), clothes (Tide), body wash (Suave), and carpet (Hoover).

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3. Use a piece of plastic wrap (15 cm x 15 cm) to cover the top of the beaker. Wind a rubber band at the 100 ml mark to hold the plastic wrap. 4. Shake each cylinder up and down for 30 s. Shake the cylinder over a distance of 15 cm. 5. Measure the amount of suds above the water line in millimeters. 6. Repeat steps 1-5 two more times for a total of three trials. Record the data. 7. Calculate the mean height of suds (mm) for each of the four cleaners. Of course, the above procedure can always be improved. There may be missing details, or we may not have written clearly. Just because a procedure is in a science text, library text, or other media does not mean it will be clear and precise. Look at the examples in Box 4-2, Practice- Writing a Precise Procedure. Revise each procedure to increase clarity and precision.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Writing a Precise Procedure DIRECTIONS Read the genera l procedure and the list of available materials and equipment. Revise each procedure to increase clarity and precision. 1.

Does the size of a magnifying glass affect water temperature? Available Materials & Equipment

General Procedure



Clear plastic cups, 300 ml



Water



Penn ies



Celsius thermometers

2. Use one of the magnifying glasses to focus sun light on the penny for 5 min. Take the temperature of the water.



Magnifying glasses-10, 15, and 20 cm diameter

3. Repeat steps 1-2 for the other two magnifying glasses.

1. Put water in a cup. Put a penny in each cup.

4. As a comparison, put a penny and water in a cup . Aft er 5 min measure t he temperature of the water. 5. Record and analyze the data .

PROCEDURE

99

2. How do hard surfaces impact plant growth?

Available Materials & Equipment ► ► ►

► ►



► ► ► ►

3 flower pots, 1 L Potting soil Bean seeds Flour Water Metric ruler Graduated cyl inder Metric measuring cup, 250 ml Spoon 2 mixing containers

General Procedure 1. Put soil in each of the flower pots. 2. Plant six bean seeds in each pot. Water the soil. 3. M ix flour and water until the mixture is very thick. Pour this mixture on top of the soil in the f irst pot. 4. M ix more flour and water; this time make the mixture about half as thick . Pour this mixture on top of the soil in the second pot. E E 5. For the th ird pot do not put anything on :s top of the soil. - 6. Put t he pots by a sunny inside w indow. 7. Water the plant s every week. 8. At the end of four weeks observe and [email protected] measure t he bean plants. 9. Record and analyze the data.

j

l r

PROCEDURE

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MOVING FROM EXPERIMENTAL DESIGN DIAGRAM TO PROCEDURE By now, you are probably saying: "What about the experimental design diagram? Wouldn't it be easier to make an experimental design diagram, check it, and then write the procedure?" Yes, it would be easier because you have made decisions about the variables, control group, and repeated trials. After visualizing the general steps you can add details from the experimental design diagram. You can also streamline the procedure by writing directions for one level of the independent variable and directing the experimenter to repeat these steps for other levels of the independent variable and for repeated trials. Does your favorite jawbreaker change colors and flavors as it dissolves? Some jawbreakers have several layers dissolving one after another. What affects how long the candies last? What could you do to increase or decrease the dissolving time? An experimental design to answer one of these questions is displayed in Figure 4-1, Making the Flavors Last.

FIGURE 4-1

Making the Flavors Last

QUESTION Will water temperature affect the time it takes to dissolve the outer layer of a Gobstopper? HYPOTHESIS If the temperature of the water is increased, then the outer layer of a Gobstopper will dissolve faster because the water molecules will hit the outer layer faster and more often. IV: Temperature of the Water (°C) 25°( 5°C (control group)

5 trials

4s c 0

5 trials

5 tria ls

DV Time (sec) for the outer layer of the Gobstopper to dissolve

CV Gobstoppers-green, 1.2 cm, room temperature, new box Water-150 ml, tap water Method-drop from surface of water Stirring-none Containers-clear plastic cups, 250 ml © Kendall Hunt

~~

After reviewing the experimental design diagram in Figure 4.1 , we drafted a procedure: 1. Put 5°C water in the cup. 2. Place a Gobstopper in the cup. 3. Time how long it takes for the outer layer to disappear completely. Record the data. 4. Repeat steps 1-3 using 25° and 45°C water. 5. Repeat steps 1-4 four more times for a total of five repeated trials. 6. Analyze the data.

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This procedure looks different than our prior procedures. In steps 1 to 3 we described the process for one level of the independent variable (5°C). In step 4 we directed the experimenter to repeat steps 1-3 for the other levels of the independent variable (25° and 45°C). Likewise, we eliminated steps by directing the experimenter to repeat steps 1-4 for the repeated trials. As we move forward in this book, we will use this technique to shorten the procedure. We refined the general procedure by adding details from the experimental design diagram in Figure 4-1, Making the Flavors Last. 1. Put 150 ml of 5°C tap water in a clear plastic cup (250 ml).

2. Carefully drop a new, green, room temperature Gobstopper into the water. 3. Time, in seconds, how long it takes for the outer color/layer to disappear. 4. Repeat steps 1-3 using 25° and 45°C water. 5. Repeat steps 1-4 four more times for a total of five repeated trials. 6. Analyze the data using the mean. In a procedure you do not need to specify common laboratory tools. The reader assumes you have access to equipment used to measure metric volume, mass, length, and temperature. Many classroom labs contain a list of materials, a list of safety precautions, and a list of steps. This is the format used in this book. In formal papers the procedure is written as a paragraph which includes the materials and safety precautions. Even if the final product is a paragraph it is easier to begin with a list. After you draft the list you can change it to a paragraph. Two examples of procedures for the Gobstopperexperiment are provided in Figure 4-2.

Chapter 4

FIGURE 4-2

Experimenting Precisely

103

Examples of Procedures for 'Making the Flavors Last' List of Materials and Steps

MATERIALS ►

15 clear plastic cups (300 ml)

► 2.25 L of tap water ►

15 new, green Gobstoppers (1.2 cm)



Timer (seconds)



Graduated cylinder (2 50 ml)



Thermometer (°C)



3 L containers

► Heating device (microwave oven) to heat 0.75 L of water to 45°C ►

Cooling device (refrigerator) to cool 0. 75 L of water to 5°C

PROCEDURE 1. Put 150 ml of 5°C tap water in a clear plastic cup (250 ml). 2. Carefully drop a new, green, room temperature Gobstopper into the water. 3. Time in seconds how long it takes for the outer color/layer to disappear. 4. Repeat steps 1-3 using 25° and 45°C water. 5. Repeat steps 1-4 four more times for a total of five repeated trials. 6. Analyze t he data using t he mean.

Paragraph That Includes Materials Put 150 ml of 5°C ta p water in a clear plastic cup (300 ml). Carefully drop a new, green, room temperature Gobstopper into the water. Time in seconds how long it takes for the outer color/layer to disappear. Repeat the procedure using water at 25° and 45°C. Then, repeat the experiment four more t imes for a tota l of f ive repeated t rials. Analyze the data using the mean.

To practice writing a procedure from an experimental design diagram use the examples in Box 4-3. Use the style required by your teacher, e.g., list of materials and steps, a stepwise list which includes materials, or a paragraph which includes materials.

104

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Experimental Designs and Procedures DIRECTIONS Read and analyze the experimental design diagram. Then, write a procedure for t he experiment. Assume you have typical measuring and laboratory tools available. For the procedu re, use the format requ ired by your teacher. If the controlled variables are not well defined you can write operational defin it ions for them.

1.

Experimental Design Diagram-The Great Tomato Race

QUESTION

Does temperature affect ketchup flow?

HYPOTHESIS If the temperature of ketchup is increased, then it will flow faster because the heat reduces the attraction between the ketchup particles. IV: Location of Ketchup Packets Kitchen Counter Refrigerator (control group) 3 t rials 3 trials

Outside Picnic Table in Summer 3 trials

DV Distance (cm) that the front edge of the ketchup blob flows in 30 sec CV Surface put blobs on-paper plate Size of blob- contents of ketchup packet Starting point- a line drawn 5 cm from the top of the plate Angle of tilted plate-45°

PROCEDURE

105

2.

Experimental Design Diagram-Corn Seed Germination

QUESTION

Will the direction a seed is planted affect growth?

HYPOTHESIS If the direction a corn seed is germinated is changed, then the directions the roots and stems grow will change because of gravity IV: Direction the Tip of the Corn Seed Points Up

5 t rials

Down (control group)

5 tria ls

Right

5 trials

DV Diagrams showing the direction the stems grew Diagrams showing the direction the roots grew

CV Clea r plastic cup-500 ml Amount of potting soil- 300 ml per cup Amount of water used at planting- 40 ml per cup Type of seeds-yellow corn Number of seeds in cup-4 Depth of seeds- 5 cm Posit ion of seeds- between cup and soil Covering for cup-p lastic wrap Location-dark hall closet Time- 1 week PROCEDURE

106

Left

5 trials

Chapter 4

Experimenting Precisely

107

ASSESSING A PROCEDURE Using a Checklist In Chapters 1 to 3, you learned the value of using a checklist to spot weak or missing parts of an experimental design. Similarly, a checklist is a valuable tool for developing clear, precise, and safe experimental procedures. For a checklist focused on procedures, see Box 4-4, ChecklistProcedure.

SELF CHECK

EXPERIMENTAL COMPONENT

PEER CHECK

POINT VALUE

CORE PROCEDURE 1. Is the procedure written for one level of the IV?

6

2. Does the procedure for one level of the IV contain all the

8

steps? 3 . Does the procedure for one level of the IV contain specific information about t he materials and equipment used?

8

4. If appropriate, are d iagrams or phot ographs of a unique experimental tool or a set-up included?

4

REPETITIONS 5. Does the procedure include repetitions for other levels of the IV?

8

6. Are the levels of the IV specifical ly described?

4

7 . Does the procedure include repetitions for repeated trials?

8

8 . Is the number of trials specifical ly described?

4

DATA ANALYSIS 9. Does the procedure describe how the data wil l be analyzed?

8

10. ls the method of data analysis correct for the type of data collected?

6

SAFETY 11.Does the procedure include general safety precautions?

8

12. If applicable, does the procedure reference specific guidelines followed, e.g., use of vertebrates, human subjects, chemicals, m icroorganisms, electromagnetic radiation, projectiles, field st udies, etc.?

8

FORMAT 13. ls the procedure w ritten in the required format, e.g ., a list of materials and steps, a stepwise list w hich includes materials, or a paragraph which includes the materials?

8

14.Are the spelling and grammar correct?

6

15.A re the sentences and/or paragraph structure correct?

6

TOTAL COMMENTS

108

100

GRADE

Chapter 4

Experimenting Precisely

109

The checklist in Box 4-4 focuses on five components: core procedure, repetitions, data analysis, safety, and format. Review each of the questions in Box 4-4 carefully. Then, use the checklist to analyze an experiment entitled An Experiment to Cry Over (see Figure 4-3). Once you have completed your assessment, read the following section to see how your analysis compares with ours.

FIGURE 4-3

QUESTION

An Experiment to Cry Over Which type of onion has the strongest odor?

MATERIALS ►

Pu rple onion



Hand-operated onion chopper



Red onion



Paper plates

► Yellow onion

► Meter stick

► Sweet wh ite onions

► Kitchen knife

PROCEDURE 1. Remove the skin from a room t emperat ure yel low on ion. Cut t he onion into sma ller pieces and put the pieces into a hand-operated onion chopper. Chop the onion until it is f ine. 2. Using a metric measuring cup, measure 100 ml of chopped onion onto a pa per plate. Spread the onion evenly. Cover the plate of on ion with a paper plate of t he same size. 3. Have a female friend, aged 14 years, wa it ing at the entrance to an empty garage. 4. Go the front of the garage and put the plate w ith the chopped yellow on ion on a table. Uncover t he plate. Immediately, inst ruct your friend to wa lk toward the table and to stop when she f irst smells t he onion. 5. When she has stopped, cover the chopped on ion. Measure the dist ance (cm) from the table to where she stopped. 6. Clean all equipment and dispose of the onion. Do not let your friend in the kitchen area. 7. After a 30-min wait, repeat steps 1-6 using a purple onion. Similarly, repeat for the red onion and the sweet wh ite onion . Always wa it 30 min between the t rials. 8. On four other days, repeat the experiment with five different female frien ds who are also 14 years old. 9. Com pile the data and analyze it.

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Part One

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Comparing Assessments Using the checklist in Box 4-4, we identified problems and made suggestions for improving the procedure for An Experiment to Cry Over. Core Procedure. The procedure is written for one type of onion, the yellow onion. Although the general steps are listed additional details would be helpful. The procedure says to remove the skin from the onion and the experimental design states the skin is peeled. The method used is important. When the onion flesh is broken it begins emitting an odor. Typically, hand peeling is the best technique to prevent breakage. "Chopping the onion until it is fine" is not a good description. It would be better to state the length of time chopped or the number of times chopped. The brand of the onion chopper could be given.

The size of the paper plate needs to be stated, e.g., 25 cm diameter. The thickness of the onion layer is important because only the top layer is in contact with the air. If the onion formed a single layer more of the odor-producing chemical would be disseminated. Stating the gender and age of the subject are strong points. Both gender and age may impact one's ability to smell. To ensure the onion was the only odor, the experimenter could state the subject did not wear fragrances and the garage was aired. For humans, it is important to provide recovery time between trials. Over time one can lose the ability to detect odors. Using a stated recovery time of 30 min is a strength of the experiment. The procedure stated the experiment was repeated on four different days but did not describe the weather. Using days with similar weather conditions is important because temperature and wind can impact the distance an onion is smelled. Repetitions. The seventh step says to repeats steps 1-6 for the various levels of the inde-

pendent variable, e.g., the purple onion, red onion, and sweet white onion. In the eighth step, the procedure says to repeat the prior steps on four other days. For clarity, it would be better to specify repeating steps 1-7. Although one infers a total of six trials are used, it would be better to add this information to step 8. Data Analysis. The procedure states "compile the data and analyze it." Because the data are

quantitative, the experimenter should state the mean will be used to analyze the data. Safety. In the first four experiments- Rapid Swingers; Floating Egg; Huff, Puff, and Slide; and Sudsational Experience- there were lists of safety guidelines. These general guidelines probably resemble those used in your science classroom: Wear safety goggles, do not eat or taste experimental materials, wash your hands after investigating, and follow your instructor's directions for cleaning the laboratory and disposing of experimental materials.

To emphasize safety, most science text and lab books have a prominent list of safety guidelines. General safety guidelines are taught at the beginning of a science class, and students are not allowed to conduct laboratory experiments until they demonstrate they know the guidelines, perhaps by passing a safety test. In many science labs there is a posted list of general safety guidelines. Science text and lab books may state specific guidelines for working with chemicals, equipment, or living organisms.

Chapter 4

Experimenting Precisely

111

Because An Experiment to Cry Over contains common materials, you may have thought safety guidelines were not needed. Regardless of where you conduct the experiment, you need to identify safety precautions and include them in the procedure. Onions contain a substance which irritates the human eye and causes it to tear. When you touch an onion you get the substance on your hands and can easily transfer it to your eye. Therefore, you should add a statement about wearing chemical splash safety goggles, disposable plastic gloves, and even an apron. Likewise, you should show concern for your subjects' safety by having them wear chemical splash safety goggles. Before taking the onion container to the garage, you should remove and dispose of your gloves, wash your hands, and put on a new pair of disposable gloves. By removing the old gloves you eliminate odor from chopping the onions. Because a knife was necessary to cut the onion, you should describe the kind of knife and the method used to cut safely. When you use human subjects in an experiment specific guidelines must be followed. Nothing may be done to humans which is likely to cause them harm. Eating, drinking, or smelling substances pose a risk to subjects. Even though a common onion presents a minimal risk, you must comply with the guidelines for working with human subjects. Scientists who wish to do experiments on humans must have their research plans approved by a committee of fellow scientists. In Chapter 9, Analyzing and Addressing Safety Risks, information is provided about the requirements for working with human subjects. Format. The procedure is written correctly as a list which includes materials and equipment.

The spelling and grammar are correct. The sentences included in the list are correct. However, a scientist would use the term "subject" rather than "friend." Although you have experienced several methods for writing procedures, you can always improve an experimental procedure by answering the questions included in Box 4-4, Checklist- Procedure. For detailed safety information, see Chapter 9, Analyzing and Addressing Safety Risks.

EXPLORING STEM CONNECTIONS Now, it is time to make connections among various scientific disciplines, mathematics, technology, and engineering. In Box 4-5, STEM Perspective- Sudsational Experience, some options for investigation are described. As before, select among the options, complete a teacher-assigned investigation, or identify a question you want to investigate.

112

STEM PERSPECTIVE Sudsational Experience

Science Explaining how the natural world works 1. Matter and its interactions. Explore the following connections. Then, use key scientific concepts to explain the experimental findings. a. Water is characterized by strong surface tension . How does surface tension inhibit the cleaning process? How do surfactants- soaps and detergentsimprove cleaning? b. What is soap? How was soap made originally? What properties of early soaps made them less effective than today's products? c. What are suds? What is the relationship between suds and cleaning effectiveness?

d. What properties need to be included in a product designed for (a) an automatic dishwasher, (b) hand washing dishes, (c) a traditional washing machine, (d) washing your body, and (e) cleaning carpet? How have product formulations been adjusted to achieve these properties? In which products are suds desirable? Explain.

2. Structure and function. The skin is one of the body's organs. What is the skin's structure and function? How is the skin impacted by soaps and detergents? What are potential health consequences, both short- and long-term?

113

114

Part One

Engaging in Experimentation

Technology and Engineering Modifying the world to meet human needs and wants

3. Engineering design. Although you probably purchase cleaners, many " do-ityourself" sites contain directions for making home-made cleaners. Research various cleaners. Then, write an engineering design brief to guide creation of an environmentally friendly product. Develop the product and test its effectiveness. Be sure to follow safety precautions and to get your teacher's approval for the project. For engineering tips, see Chapter 8. 4. Links among engineering, technology, science, and society. Explore the following connections. a. In the 1940s, chemical engineers succeeded in creating a "built detergent" which included a surfactant and a "builder" made of phosphate compounds. What were the positive and negative consequences of "built detergents"? b. Many "green advocates" recommend using soap nuts. What are the potential positive and negative consequences of using soap nuts and product s made from them, such as liquid and powdered soap nuts? c. A recent invention is the High Efficiency (HE) washing machine. What challenges

did it present for existing detergents? How have chemica l engineers addressed these challenges?

Mathematics Describing, analyzing, and interpreting patterns and relationships

5. Representing the data. Sophia used laundry detergent in the automatic dishwasher and had a surprise-suds all over the floor. In Sudsational Experience you measured the height of the suds above the water line. Create a graph you could use to explain the results of the experiment to Sophia so she w ill understand why she had such a mess in her kitchen . Use your experimental data, or the data from question 6. 6. Comparing with ratios. If the container had not been empty, Sophia would have washed her dishes in the automatic dishwasher wit h the dishwasher detergent. Use your Sudsational data, or the data on the following page, to create ratios of comparison between each of the cleaners and the dishwasher detergent. Use the ratios to explain t o Sophia how each of the cleaners compares to the dishwasher detergent. In the example, the dish wash ing detergent made suds which were 20 times higher than the automatic dishwasher detergent.

Chapter 4

Experimenting Precisely

Type of Cleaner

Mean Height of Suds (mm)

Ratio of Cleaner to Dishwasher Detergent

Equivalent Unit Ratio

Dishwasher

6

6:6

1:1

Dish wash ing

120

120:6

20:1

Clot hes

45

Body

90

Carpet

7

115

7. Comparing with percentages. In t he experiment you began wit h 50 ml of water, w hich had a height of 92 mm. Aft er adding a drop of cleaner and shaking the cyli nder you measured the height (mm) of t he suds above the wat er line. A group decided t hat percentages, rat her t han rat ios, would be a better way to display t he data. They decided to calcu late t he percent change in height using the following form ula: . h . h _ height of suds above water line Percent c hange in e1g t . . h . ht f t angina1 e1g o wa er

Type of Cleaner

Mean Original Height of Water (mm)

Mean Height of Suds Above Waterline (mm)

Dishwasher

92

6

Dish washing

92

120

Clothes

92

45

Body

92

90

Carpet

92

7

Percent Change

(%)

a. Use t he formula proposed by the group to calcu late the percent change in height and enter into the table. b. Use the percentages to explain to Sophia how each of the cleaners compa red with the dishwasher detergent. c. Do you th ink the group's formula is a va lid way to ca lcu late t he percent change

in height? What experi menta l observat ions can you use to support (or not support) this formula?

116

Part One Engaging in Experimentation

8. Calculating percentages of suds and water. For Sudsational Experience, a group decided they wanted to use a larger graduated cyl inder (2 50 ml) and 100 ml of water. They also wanted to measure two dependent variables-the height of the water column and the height of the suds above the water column. Below are the data they collected.

Type of Cleaner

Mean Height of Suds Above Water Column (mm)

Mean Height of Water Column (mm)

Mean Total Height of Column (mm)

Dishwasher

6

110

116

Dish washing

140

100

240

Clothes

51

106

157

Body

106

102

208

Carpet

8

110

118

a. The group decided to calculate the percentage of suds in the column and the percentage of water in the column . Below are the formulas they used. Do you think these formulas are appropriate? Explain. Height of suds Percentage of suds = - - - - - - - Total height of column Height of water Percentage of water = - - - - - - - Total height of column b. Use these formulas, or modifictions, to calculate the percentages of suds and water in the total column.

Type of Cleaner

Percentage of Suds(%)

Percentage of Water(%)

Dishwasher Dish washing Clothes Body Carpet

c. Is it advantageous to know the percentage of suds and water in the column? Explain. d. How might you use the imaging capa bilities of digital technology to improve the precision of the data collection?

Chapter 4

Experimenting Precisely

117

REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Confrey, J., & Krupa, E. E. (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_Standards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www.apsva.us/cms/lib2N A01000586/Centricity/Domain/29/ CTAE_Committee_Report. pdf

1:00 Im 01 ,0 t :) O-

~

~

Chapter 6

FIGURE 6-8

Selecting and Constructing Graphs

185

Graphical Display for Two Independent Variables The Effect of Herbicide Concentration and Time of Day Applied on Number of Dead Plants Time of Day

Concentration

8a.m.

10 a.m.

12 p.m.

2 p.m.

4p.m.

20%

92

86

60

55

45

40%

99

92

80

75

77

Impact of Herbicide Concentration and Time of Day Applied on Death of Grass Plants

100

.."' C

"' ii:

80

"Cl

"'

♦ 20%

~

Q

15 ...

60

40%

~

.J:I

E ::I

z

40

20

0 -8a .m .

10 a.m .

12 p.m .

2 p.m .

4p.m.

Time of Day Applied

EXPLORING STEM CONNECTIONS You will be surprised how many scientific concepts and innovations are related to elastic objects, such as the rubber bands you investigated in Stretching to the Max. As before, select among the options, complete a teacher-assigned investigation, or identify a topic you want to investigate.

186

STEM Perspective Stretching to the Max

Science Explaining how the natural world works

1. Energy .. . Matter and its interactions. Explore the fol lowing connections. Then use key scient ific concept s to explain t he experiment al f indi ngs. a. What energy changes occurred in t he shooting, t ravel ing, and landing of the rubber band? Use these energy transformations to explain differences in t he behavior of rubber bands stretched different amounts. b. Rubber is a polymer and its molecules consist of long chains of atoms. How do the chains change as you stretch a rubber band and when the band returns to its original shape?

2. Energy. Human impacts. About 30% of t he ru bber used on Ea rth is derived from the rubber tree. Natural rubber is highly valued even though synthet ic products exist. Where is natural rubber produced? What are t he environmenta l impacts of large-scale ru bber plantations? How might they be minimized? 3. Natural selection and adaptation. Many plants produce sap including the ru bber producing trees in the genus Hevera . A Hevera tree produces t he latex sap in special cells called laticifers. What selective advant age does t he latex sap provide Hevera t rees? W hat trees in your area produce sap? How is the sap advantageous to these trees? 4. Structure and properties of matter. Explore one or more of t he following : a. What are the propert ies of natural rubber? How does the process of vulcanization change the properties? How do the properties of vulcanized rubber change over time? Explain. b. Rubber bands are classified as elast omers, w hich are solids t hat can be st retched a great dist ance and then retu rn t o t he original form. How does temperature impact the properties of rubber? Use changes in properties to explain the Cha llenger Explosion .

©David Koloechter/Shutterstock.com

187

188

Part Two Analyzing and Interpreting Experimental Data

Technology and Engineering Modifying the world to meet human needs and wants

5. Engineering design. In Chapter 13 learn how engineers use data to improve an engineering design. Apply your knowledge of elasticity and wind power to design and test a vehicle. See Box 13-2, Air Car.

6. Links among engineering, technology, science, and society. Explore t he following connections. a. Major t ire companies have formed part nerships w ith genetic engineering companies . The goal is to make "green tires" from pla nt byproducts rather t han natural or synthetic rubber. How do t he companies int end to produce the plant byproduct s and convert the byproducts into synthetic rubber? W hat is t he stat us of this research on "green ti res?" b. The United St ates does not have climate suitable for rubber plantations based upon Hevera brasiliensis, a native tree of Brazil which is t he most com mon t ree in rubber plant ations. However, Guayule (Parthenium argentatum) is a nat ive plant in the sout hwestern United States that produces a sap simila r to Hevera. A re Guayule plantations a realistic option for meeting the United States' rubber needs? What are potent ial environmental impact s? Wou ld you recommend t hese plant ations? Why?

c. Throughout its life cycle a ti re has an environmental impact. What are these impact s? How have ti re manufacturers minimized the impact? W hat recycling industries have emerged from the need to dispose of tires? How successfu l are they?

Mathematics Describing, analyzing, and interpreting patterns and relationships

7. Analyzing data with a two-way frequency table. Two-way frequency tables ca n be used to represent the data in an experiment when you have two categorical va riables. A student created a two-way frequency t able t o represent the number of st rai ght and cu rved worms when they were dry and wet.

Curved

Dry

Straight 7

Wet

2

Total

9

5 5

0

Total 7 7 14

Percentage a. W hat percent of the wet worms were straight? b. What percent of the straight worms were wet?

Percentage

Chapter 6

Selecting and Constructing Graphs

8. Constructing a contingency table. A student group wanted to make a contingency table for t he landing behavior of t he rubber band when the rubber band was stretched different distances. Because t here were four levels of the independent variable and three levels of the dependent variable a larger contingency table was const ructed.

0cm

1 cm

2cm

3cm

N:3, S:2, R:0

N:0, S:3, R:2

N:0, S:2, R:3

N:0, S:1, R:4

Stretch (cm)

None

Slide

Roll

Total

Percentage

0 1 2 3 Total Percentage

a. What percentage of the rubber bands stretched 3 cm showed rolling behavior when they landed? b. What percentage of the rubber bands that rolled were stretched 3 cm? c. What are t he advantages of a contingency table?

9. Stacked bar graph with percentages. Make a stacked bar graph fo r the various percentages of landing behaviors at each stretching distance. What is the advantage of using percent ages rather t han numbers in a stacked bar graph? 10. Interpreting data from an experiment with two independent variables. A lab group t hought the rubber band experiment wou ld be more interesting if they collected data to answer the follow ing question: "How does the thickness of a rubber band and the stretching distance impact the distance a rubber band travels?" The group's data are summarized in the table. Type of Rubber Band

Mean Stretching Distance Beyond Length (cm) 0

1

2

3

Thin

15.7

59.2

146.7

280.7

Medium

6.4

42.6

132 .8

233.7

Th ick

2.9

15.1

109.6

126.4

189

190

Part Two Analyzing and Interpreting Experimental Data

a. Constructing a graph of the data. Create a graph to represent the data. Which variables are independent variable(s)? Which variable(s) are dependent variables? How did you represent more than one independent variable on the graph? b. Analyzing the graph. How would you describe the relationship between the stretching distance and the distance t raveled by t he rubber band? Does th is relationship hold true for all three types of rubber bands? Compare the relationsh ip between the stretching distance and the distance traveled for each type of rubber band. Use evidence from the graph to support your analysis.

11. Using statistics to detect the significance of relationships. In Volume 2 (Chapter 16) learn how statisticians construct histograms, interpret normal distributions, and use the standard deviation to communicate the variability within the data. Use the information to interpret another experiment on rubber bands. For this statistical activity, see Box 16-2, Stat Extension-Rubber Bands. 12. Using algebra to represent data. In Volume 2 (Chapter 15) learn about linear models and apply the information to the Bluegill data depicted in Figure 6-7 (See Box 15-1). 13. Developing mathematical models. In Volume 2 (Chapter 15) learn about various mathematical models. Determine which mathematical models best fit the data collected in Stretching to the Max and/or in the experiment described in question 10.

Chapter 6

Selecting and Constructing Graphs

191

REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Confrey, J., & Krupa, E. E. (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-conten t/up Ioads/Math_S tandards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www.apsva.us/cms/lib2NA01000586/Centricity/Domain/29/ CTAE_Committee_Report.pdf

CHAPTER

7 Making Sense of Experiments

CONTENTS Introduction Learning Objectives Correlations With Nationwide Standards

194 194 194

Collecting Experimental Data Box 7-1 Experiment- Fresh Water Pearls

196 197

Interpreting Experimental Evidence-The Results Quantitative Evidence: Mass Qualitative Evidence: Shape Qualitative Evidence: Surface Bra iding Box 7-2 Practice- Experimental Results

199 199 201 202 205

Preparing an Experimental Conclusion Researching the Topic Writing the Conclusion Box 7-3 Practice- Experimental Conclusion

207 207 208 211

Communicating an Experiment Box 7-4 Experiment- Pearly Environments Box 7-5 Checklist- Experimental Report

213 215 217

Exploring STEM Connections Box 7-6 STEM Perspective- Water Pearls

219 221

References

225

193

194

Part Two Analyzing and Interpreting Experimental Data

INTRODUCTION The current body of scientific knowledge was developed by investigating natural phenomena. Future investigations, such as ones you may do, will expand and improve understanding of the natural world. In Chapter 7 you will focus on making sense of an experiment and explaining the results. You will analyze the data by comparing descriptive statistics and interpreting graphs. You will determine if the data support the hypothesis. You will develop a conclusion for the experiment. In the conclusion you will argue the validity of the hypothesis. Your argument will include the hypothesis, evidence to support or refute the hypothesis, an explanation of the findings, and an experimental critique.

Learning Objectives Specific learning objectives for Chapter 7, Making Sense of Experiments, include: ►

Analyze, interpret, and compare experimental data;



Make quantitative and qualitative claims about the relationship between independent and dependent variables;



Use experimental data as evidence to support or refute the hypothesis (claim);



Use the scientific literature to understand scientific concepts and to explain the experimental findings;



Write an experimental conclusion which includes the hypothesis, evidence to support or refute the hypothesis, an explanation of the findings, and an experimental critique;



Write an experimental report which summarizes the chain of scientific reasoning followed, i.e., experimental design diagram, procedure, results, and conclusion;



Ask questions about the experimenter's interpretation of the data and the conclusions drawn;



Use a checklist to assess the quality of an experimental report; and



Use argumentation skills to compare assessments.

Correlations With Nationwide Standards In Table 7-1, the chapter learning objectives and STEM concepts are correlated with nationwide learning standards. The correlations for "Exploring STEM Connections" are shown in italics. For a synopsis see Appendix A.

Chapter 7

TABLE 7-1

Making Sense of Experiments

195

Correlations With Nationwide Standards

NEXT GENERATION SCIENCE STANDARDS ►

Scientific & Engineering Practices: Analyzing and int erpretin g data; Using mathematics and computat ional thinking; Const ruct ing explanat ions and designing solutions; Engaging in argument from evidence; Obt aining, evaluating, and commun icatin g informat ion



Cross-Cutting Concepts: Patterns; Cause and effect; Structure and function; Stability and change



Disciplinary Core Ideas: M atter and its interactions; Ecosystems; Earth and human activity; Engineering design; Links among engineering, technology, science, and society

COMMON CORE STANDARDS-MATHEMATICS ►

Mathematical Practices: Const ruct viable arguments and crit ique the reasoni ng of others; M odel w ith mat hemat ics



M athematical Domains: St atist ics and probability; Interp reting categorica l and quant itative data; Ratios and proportional reasoning; Expressions and equations; Functions; Geometry; Interpreting functions; Geometric measurement and dimension

COMMON CORE STANDARDS-LITERACY IN SCIENCE AND TECHNICAL SUBJECTS ►

Reading: Cite textual evidence; Determine key ideas or conclusion; Follow mult i-step procedure; Det ermine meaning of symbols; Integrate words and visual representation, key terms, etc.; Distinguish among fact s, reasoned judgment , and speculation; Compare and cont rast information from known sources; Read and comprehend text



Writing: W rite arg uments; W rite informat ion/explanat ory texts; Produce clear and coherent writ ing; Develop and strengthen writing; Use technology t o prod uce and distri bute w rit ing; Gather relevant information; Draw information from informational texts; W rite rout inely over extended time frame; Conduct short research projects

ISTE STANDARDS-STUDENTS ►

Creativity and innovation: Ident ify trends and forecast possibilities



Communication and collaboration: Communicate information and ideas effect ively t o multiple audiences using a variety of media and formats



Research and information fluency: Evaluate and seek information sources and digital tools based on t he appropriateness for specific tasks; Process data and report result s; Locate . .. use information from a variety of sources/media



Critical thinking, problem solving, and decision making: Collect and analyze dat a t o ident ify solut ions and/or make informed decisions



Digital citizenship: Demonst rat e personal responsibility for .. . learn ing; Advocate and practice safe, legal, and responsible use of information and technology; Exhibit a positive attitude toward using technology that supports collaboration, learning, and productivity



Technology operations and concepts: Underst and and use technology systems; Select and use applications effectively and productively

Source: Confrey & Krupa, 2012, p . 9; Morphew, V. N., 201 1, pp. 299- 300; National Governors Association Center for Best Pract ices, 20 10, Eng lish language & literacy, pp. 64- 66; National Governors Association Center for Best Practices, 2010, Mathemat ics, pp. 6- 8; NGSS Lead States, 2013, Volume 1, p.1; NGSS Lead States, 2013, Volume 2, pp . 67- 79.

196

Part Two Analyzing and Interpreting Experimental Data

COLLECTING EXPERIMENTAL DATA In this chapter we will analyze and report data from an experiment, Fresh Water Pearls (see Box 7-1). In the experiment you will use water pearls, which are readily available at craft and floral stores. You will soak the pearls for seven different times, i.e., 0, 30, 60, 90, 120, 150, and 180 min. You will measure the mass (g) of ten different water pearls. You will take a photograph and use it to categorize the shape and braiding of the water pearls. To save time, you may divide soaking times among different laboratory groups or classes and combine the data. An early class could set up the experiment and later classes could collect the data.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

EXPERIMENT Fresh Water Pearls QUESTION

How do water pearls change over time when soaked in distilled water?

HYPOTHESIS If water pearls are soaked longer, then they will become larger, more spherical, and smoother because this is how they look in my mom's flower arrangements.

MATERIALS

SAFETY



Wat er pearls, 70 or more





Room temperature distilled water, about 250 ml

Wear side vented chemical splash goggles and appropriate protective clot hing.



Do not ingest the water pearls or any of the solutions.



Do not put the water pearls in a drain.



Wash hands after investigat ing.



Follow your teacher's direct ions for safety, cleaning the laboratory, and disposing of the water pearls and solutions.



See Chapter 9, Analyzing and Addressing Safety Risks.



Graduated cylinder, 100 ml



Small plastic cont ainer w ith lid, such as used fo r individual servings of salad dressing, 7 or more



Triple beam or elect ronic balance



Timer



St rainer with small holes, such as a mesh kitchen strainer



Container to catch wat er from strainer



Paper towels

► Dark surf ace C



:r: "

Camera

PROCEDURE 1. Use a triple beam or electronic balance to determine the mass of a water pearl in grams. Repeat for nine other water pearls. In a data table, record these measurements (0 min). The balance used wil l determine the precision of your measurements. For example, if the balance measures to 1 g , then you can estimate to 0. 1 g. If the ba lance measures to 0. 1 g, then you can estimate to 0.01 g. 2. Place the ten wat er pea rls on a dark surface and photograph them. Put the un-soaked pearls in a closed container. 3. Put ten water pearls in a salad dressing container. Add 30 ml of dist illed water at room temperat ure. Close the lid. Label the conta iner- 30 min. After 30 min pour the contents of the container into a strainer. Remove the water pearls from the strainer and put t hem on a paper towel. When excess wat er is absorbed return the soaked pearls to t he cont ainer. 4. Put the water pearls on a dark surface and photograph them . Return the pearls to the container. 5. Measure the mass of each of the ten water pearls in grams. Record the data. 197

6. Retu rn the water pearls to the salad dressing container and close it t ightly. Be sure the conta iner is correctly labeled, e.g., 30 min. 7. Repeat steps 2-5 for wat er pearls soaked for 60, 90, 120, 150, and 180 min.

ANALYZING THE EXPERIMENT 1. Construct a data table to record t he mass (g) of t he wat er pearls soaked for the various t imes, i.e., 0, 30, 60, 90, 120, 150, and 180 mi n. Construct a data table and graphs (see Chapters 5 and 6). 2. Using photographs we developed a sca le to describe the roug h shape of the water pearls:

0

cJ FC-P

C

Key: C

= Circular;

FC-P

00 E

0

= Fat circle w ith protrusion; E = Egg shaped; 0 = Ova l

a. Use t he scale and you r photographs to categorize t he shapes . Record the raw data. You may find it useful to trace the general outline of the shape. b. Construct a data table and graph for t he data. 3. From the photographs we developed a sca le to describe the su rface braiding of the water pearls. Bra iding ref ers to a surface similar to hair bra ids.

N

s

Key: N = No bra iding; S = Slight braiding; M

M

H

= Moderate bra iding; H = Heavy braiding

a. Use t he scale and you r photographs to categorize t he surfaces. Record t he dat a. You may f ind it useful to trace the surface pattern in the photos. b. Construct a data table and graph for t he data . 4 . Observe the water pearls one day after completing the experiment. How do the observations relate to t he experimental hypothesis? Explain the observations.

198

Chapter 7

Making Sense of Experiments

199

INTERPRETING EXPERIMENTAL EVIDENCE-THE RESULTS You have constructed data tables and graphs. Now it is time to analyze and make sense of the data. You will determine if there is sufficient evidence to support or refute the hypothesis, which is the claim you made initially. We have found the following approach useful when analyzing data: ►

Compare the measures of central tendency;



Compare the variability and describe implications;



Identify trends on the graph and describe implications; and



Determine if the data (evidence) support or refute the hypothesis (claim).

Use this approach to analyze your experimental data on the mass, shape, and surface braiding of the water pearls. Then compare your analysis with ours.

Quantitative Evidence: Mass Data table. Because the mass of the water pearls was continuous quantitative data we calculated the mean and range of each experiment group. The analysis is shown in Table 7-2.

TABLE 7-2

Impact of Soaking Time on Mass of Water Pearls

Mass (g)

Mean Range

I Maximum I Minimum I

Number of Trials

Time Soaked (min)

0

30

60

90

120

150

180

0.15

0.58

0 .82

1.05

1.24

1.45

1.50

0.05 0.20 0.15 10

I I I

0.10 0.60 0.50 10

I I I

0.20 0.90 0.70 10

I I I

0.25 1.20 0.95 10

I I I

0.40 1.45 1.05 10

I I I

0.30 1.55 1.25 10

I I I

0.50 1.75 1.25 10

200

Part Two Analyzing and Interpreting Experimental Data

Graph. Because both variables were continuous quantitative data we constructed a scatter plot and fit a non-linear trend as shown in Figure 7-1.

FIGURE 7-1

Impact of Soaking Time on Mass of Water Pearls

1.6 1.4 + - - - - - - - - - - - - - - - - - - - - - =~ ~:::::__ __:__ __

-

~

1.21 1- - - - - - -

::l 0 .8

----

IV

~ 0 .6

0.4 - - - ~ - - - - - - - - - - - - - - - - - - - - - - - - -

0.2 --.------.-- - - - - - -

0 0

20

40

60

80

- - , - - - ---.--

100

120

- - - - - - - - - --, 140

160

180

200

Soaking Time (min)

Interpretation. We summarized the changes occurring in the mass of the water pearls as soaking time increased from O to 180 min. ►

The mean mass of the water pearls increased from 0.15 g to 150 g.



The range increased with soaking time. The range at 180 min was ten times greater than at O min.



Increased variability may result from crowding. As size increased some pearls touched and had less contact with the water.



From Oto 120 min the mean mass increased steadily. From 120 to 180 min the mean mass began to level off. The data fit a non-linear model.



To confirm the non-linear pattern longer soaking times are needed.



The data partially supported the hypothesis that the size of the water pearls would increase with time.

Chapter 7

201

Making Sense of Experiments

Qualitative Evidence: Shape Data table. The shapes of the water pearls were categorized as circular, flat circle with protrusion, egg shaped, and oval. Because these categories are nominal qualitative data, we calculated the mode and frequency distribution for each experimental group as shown in Table 7-3.

Impact of Soaking Time on Shape of Water Pearls

TABLE 7-3

Time Soaked (min)

Shape

0

30

60

90

120

150

180

C

C

C

E

C

C

E

10 0 0 0 10

7

5

3

6

5

3

3

3

1

0

0

0 0 10

0

6

0 1

4

4

2

0 10

1 10

3

Mode Frequency Distribution Circular (C) Flat Circle-Protrude (FC-P) Egg Shaped (E) Ova l (0) Number of Trials

10

3

10

10

Key: C = Circular; FC-P = Flat circle with a Protrusion; E = Egg Shaped; 0 = Oval

Graph. The levels of the independent variable were continuous quantitative data. The dependent variable was the number of water pearls falling into the four categories by shape. To display the frequency distributions we used a stacked bar graph (see Figure 7-2).

FIGURE 7-2

Impact of Soaking Time on Shapes of Water Pearls

12 10

...

Key:

Oval (0)

8

Q.J

t

:::,

z

Egg Shaped (E)

6

4

-

Flat Circle - Protude (FC-P)

2

-

Circular (C)

0 0

30

60

90

120

Soaking Time (min)

150

180

202

Part Two Analyzing and Interpreting Experimental Data

Interpretation. We summarized the changes in shape as the soaking time increased. ►

From O to 60 min, the mode for shape was circular. At higher soaking times the most common shapes were circular and egg shaped.



The variability of the shapes increased over time. Initially all water beads were circular. From Oto 60 min, fiat circles with protrusions appeared and then ovals. At 90 min and above most of the water pearls were egg or circular shaped. Crowding could have impacted the shapes.



The stacked bar graph shows that fiat circles with protrusions occurred early, and probably represented a transition to the other shapes.



The data do not fully support the hypothesis that the water pearls would become more spherical-appear circular in a 2-D photograph. Even though the mode was circular at five of the seven soaking times, there was greater variability at the higher soaking times.

Qualitative Evidence: Surface Braiding Data table. Surface braiding was categorized as none, slight, moderate, or heavy. Because this is ordinal qualitative data, the median and frequency distribution were calculated for each soaking time. For the analysis see Table 7-4.

TABLE 7-4

Impact of Soaking Time on Surface Braiding Time Soaked (min)

Shape Mode

0

30

60

90

120

150

180

N

H

H

M

M

M

s

10 0 0 0 10

0 0 0 10 10

0 0 0 10 10

0 0 10 0 10

0 1

0

0

4

8

9

6

2

0 10

0 10

0 10

Frequency Distribution None Slight Moderate Heavy Number of Trials

Key: N= None; S = Slight ; M = Moderate; H = Heavy.

Chapter 7 Making Sense of Experiments

203

Graph. A stacked bar graph was used to display the data as shown in Figure 7-3.

FIGURE 7-3

Impact of Soaking Time on Surface Braiding

12 10

Key: Heavy

8

-

Moderate

4

-

Slight

2

-None

0 0

30

60

90

120

150

180

Soaking Time (min)

Interpretation. We summarized the changes in surface braiding as soaking increased. ►

Before soaking the water pearls showed no braiding. When first immersed in water, the pearls became heavily braided. Over time the median braiding changed from moderate to slight.



No variability existed in surface braiding at 0 min (none), 30-60 min (heavy), and 90 min (moderate). Between 90 and 180 min, the mix of moderate to slight braiding changed and ended with a median of slight braiding.



The stacked bar graph clearly shows the decrease in surface braiding over time.



The data generally supported the hypothesis that water pearls would become smoother over time. At 180 min most water pearls showed slight braiding. Longer soaking times are needed to determine if the braiding will disappear.

Now it is time to apply your interpretation skills to a different experiment, Gardener's Weed Killer (see Box 7-2). Remember to compare the measures of central tendency, the variability, and the trends on the graphs. Determine if the data (evidence) support the hypothesis (claim).

204

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Experimental Results DIRECTIONS results.

Read the scenario, interpret t he data table and graph, and su mmarize t he

Scenario. Mary's family raised a garden surrounded by a grassy lawn. Mary's father sprayed t he lawn with Gardener's Weed Killer. Mary noticed the tomat o plants on t he edge of the garden were not as healthy as those in the center of the garden. Mary wondered if the herbicide was harming the t omato plants. Mary hypot hesized: If higher concentrations of Gardener's Weed Killer are used, then the plants will be less healthy because the chemical interferes with photosynt hesis. Mary collected data on the heig ht, health, and leaf quality of t omato plants sprayed with various concentrations.

DATA SET 1

Impact of Concentration on Height Concentration of Gardener's Weed Killer(%)

Height of Plants (cm)

0

10

20

30

Mean

18. 1

15.3

10.5

6.0

Range

7.0

6.0

6.0

4.0

Maximum

19/0

20.0

14.0

8.0

M inimum

12.0

14.0

8.0

4.0

10

10

10

10

Number

20

I...

15

~

·? 10 ::c C

:

~

5

0

-~~-~-~-~~-~

-1

0

5

10

15

20

25

30

35

Concentration (%}

205

DATA SET 2

Impact of Concentrations on Plant Health Concentration of Gardener's Weed Killer{%)

Health of Plants Mode

0

10

20

30

Healthy

Healthy

Unhealthy

Unhealthy

10

8

4

2

0

2

6

8

10

10

10

10

Frequency Distribution Healthy (H) Unhealthy (UH) Number

Key: H = Healthy; UN= Unhealthy J!l 15 C

ra ii: 10

....0 lii .c

5

E ::s

z

0

Fl Kr - 0

10

D

,.......,

20

30

Key: Unhealthy (UH) -

Healthy (H)

Concentration(%)

DATA SET 3

Impact of Concentration on Leaf Quality Concentration of Gardener's Weed Killer{%)

Leaf Quality

0

10

20

30

4

4

2

1

Quality 4

10

6

0

0

Quality 3

0

3

3

0

Quality 2

0

1

7

3

Quality 1

0

0

0

7

10

10

10

10

Median Frequency Distribution

Number J!l 15

Key:

C:

ra

....ii:0

10

ai .c

5

Quality 1

E ::s

z

0 0

10

20

Concentration (%)

206

30

-

Quality2

-

Quality3

- Q uality 4

Key: 4 = Black, firm, no curled leaves; 3 = Dark gray color, firm, no curled leaves; 2 = Gray colo r, limp, curled edges; 1 = Light gray color, limp, curled leaves.

Chapter 7

Making Sense of Experiments

207

PREPARING AN EXPERIMENTAL CONCLUSION Because science seeks to explain how the natural world works, investigations are designed to improve explanations of phenomena. "Making sense of experiments" involves more than interpreting the data and stating how the evidence supports or refutes the hypothesis. The most important part of "sense making" is using the experimental evidence to explain the natural phenomena. In developing an explanation, it is important to read the scientific literature to learn about the experimental materials and prior experiments conducted. With this increased understanding you can do a better job of explaining the results of an experiment.

Researching the Topic To explain the results of Fresh Water Pearls, we used the library and Internet to learn about the chemical composition of water pearls, and how the substance changes when soaked in water. Below are some important concepts we learned. ►

Water pearls are made of sodium polyacrylate, which is a polymer. A polymer is a long chain of molecules made of repeating units. Each unit has the same chemical composition (Polymer Science Learning Center Foundation, 1995-2012).

I

COONa COONa C= O COOH

COONa

0)

~ o-i( 0

0

I COONa COONa C=O COOH

COONa



Sodium polyacrylate is an example of a superabsorber, which is a substance that can absorb at least twenty times its weight in water. In distilled water, sodium polyacrylate can absorb about 800 times its own weight (Polymer Science Learning Center Foundation, 1995- 2012).



When sodium polyacrylate is placed in distilled water, some of the Na+ ions go into solution within the long polymer chain. The resulting negative carboxyl groups (COO-) cause the chains to repel each other and uncoil (Helmenstine, 2014; Schiller & Yezierski, 2009, p. 21).



Water is a polar molecule. The hydrogen end has a slight positive charge and the oxygen end a slight negative charge.

Part Two Analyzing and Interpreting Experimental Data

208



The positive end of a water molecule bonds to the negative carboxyl group (COO-). The water is trapped within the chain of molecules forming a hydrogel (Brockway, Libera, & Welner, 2011, p. 52; Schiller & Yezierski, 2009, p. 21).



Because the Na+concentration is higher inside the polymer, water diffuses into the hydrogel until the Na+ concentrations are equal inside and outside the gel, or until no negative carboxyl groups remain (COO-) (Laposta & Brown).



Sodium polyacrylate was first introduced in the 1960s for agricultural use and then in the 1970s for personal care products. Decorative water pearls are a fairly recent innovation (Milner-Bolotin, 2012, p. 339).

With this increased understanding of the "science of water pearls" you are better prepared to explain the findings. The explanation will become part of the experimental conclusion.

Writing the Conclusion In the experimental conclusion you will argue the validity of the hypothesis (claim). Your argument will include the hypothesis, evidence to support or refute the hypothesis, an explanation of the findings, and an experimental critique. In the conclusion you will demonstrate the chain of reasoning you followed throughout the experiment. Although there is no specific way to approach the conclusion, we have found the following strategy useful: 1. State the initial hypothesis (claim);

2. Summarize how the hypothesis (claim) is supported or refuted by the experimental evidence (results); 3. Explain the experimental findings using the results and related scientific concepts; 4. Critique the experimental design, procedures, and adequacy of the data collection and analysis; recommend improvements; and 5. Recommend future experiments that will increase understanding of the phenomena. As with the results, we will use a bulleted list of phrases or short sentences to communicate the analysis. In Table 7-5, key elements to include in a conclusion are listed. For each element some sample statements are provided. Of course, your conclusion will differ because you had different experimental findings.

Chapter 7

TABLE 7-5

Making Sense of Experiments

209

Key Elements to Include in the Conclusion

Elements

Example

1. State the initial hypothesis (claim).

► If water pearls are soaked longer, then they will become larger,

2. Summarize how

► Dat a on t he mean mass of water pearls over time partially

the hypothesis (claim) is supported or refuted by the experimental evidence (results).

more spherical, and smoother because this is how they look in my mom's flower arrangements. supported t he hypothesis that mass would increase. The mass increased at fi rst and t hen leveled off. ► At 180 min of soaking time, only three of the water pearls had a

circular shape; t hus, t he hypothesis about shape was ref ut ed. ► The data on the water pearls' surface braiding generally supported

the hypot hesis that the surface wou ld become smoother, alt hough a totally smooth surface did not occur.

3. Explain the experimental findings using the results and related scientific concepts.

► The chemical name for water pearls is sodium polyacrylate, w hich

is a polymer. The polymer contains positive sodium ions (Na+) and negative carboxylate ions (COO-). ► When water pearls soak in distilled water some of the Na+ ions go

int o solut ion inside the polymer. Beca use t he number of negative carboxylate ions (COO-) increases, the chains repel each other and begin uncoiling . This creat es t he braided surface. ►

The positive ends of water molecules attach to the negative carboxylate ions (COO-). This causes the hydrogel to swell and reduces the braiding. The swelling ca uses the shapes to change.



Water w ill move int o the hydrogel as long as the Na+concent ratio n is higher inside and sites rema in. Longer soaking times are needed to maximize water absorption and to determine if shape and braiding w ill support the original hypothesis.

coo-

4. Critique the experimental design, procedure, and adequacy of the data collection and analysis; recommend improvements.



5. Recommend future experiments that will increase understanding of the phenomena.



Investigate a greater range of soaking times, perhaps using 1 hr as the interval.



Investigate if the variability in shapes was related t o crowding in the container.

Crowding may have impact ed t he shape and bra iding. A smaller number of pearls should be placed in a cont ainer, or larger containers used.

► Because of the variability in t he data a larger number of trials are

needed. The procedure needs t o be improved by keeping t he draining t ime constant. To minimize handling, the water pearls could be dried on a dark cloth surface and photographed on it.

210

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Experimental Conclusion DIRECTIONS Hunter investigated the mass needed to sink a cup in various concentrations of salt water. An experimental design diagram, procedure, data table, and graph are provided below. Analyze t he data, summarize the results, and prepare a conclusion. You may f ind it helpf ul to review concepts learned from t he experiment, Floating Eggs, which was conducted in Chapter 2.

EXPERIMENTAL DESIGN DIAGRAM QUESTION

How does the saltiness of water impact the mass needed to sink a cup?

HYPOTHESIS If the saltiness of the water is increased, then more mass will be needed to sink a cup because the buoyant force will be greater.

IV

Amount of Dissolved Salt (ml) 0 (Control)

60

120

180

5 trials

5 t rials

5 t rials

5 trials

DV Number of pennies required to sink cup

CV Water- t emperat ure, amount Salt-brand, type Container- plastic cup; same size, shape, and color

PROCEDURE 1. Hold t he plastic cup firmly on the bottom of the bowl. Fi ll the bowl w ith water until the water rises almost to the rim of the plastic cu p. Remove t he cup. 2. Place the plastic cup in the water. Put penn ies in t he cup until it rests firmly on the bottom of the bowl. Count and record t he number of pennies. Remove the cu p. Repeat with four ot her cups. 3. Totally dissolve 60 ml of sa lt in t he water. Put the plastic cup into the salt water. Add just enough penn ies to make the cup rest fi rmly on the bottom. Remove the cup and repeat with four ot her cups. 4. Repeat step 3 using a tota l of 120 ml of salt. 5. Repeat step 4 using a t ota l of 180 ml of salt.

211

Impact of Dissolved Salt on Pennies Needed to Sink a Cup Number of Pennies Mean Range Maxim um Minimu m Number of Tria ls

Amount of Salt Added (ml) 0

60

120

180

71 4 73 69 5

77 5 79 74 5

84 4 85 81 5

95 6 99 93 5

Effect of Dissolved Salt on Number of Pennies Needed to Sink a Cup 100

"' GI

·2

C GI Cl.

80

i=







'S 60 1

.. GI

.c

40

:::J

20

E

z

J

0 0

so

100

150

Amount of Salt (ml)

Source: Cothron et al, Teacher's Guide: Science Experiments by the Hundreds, Kendall Hunt Publishing Company, 2008, pp. 243, 244.

212

200

Chapter 7

Making Sense of Experiments

213

COMMUNICATING AN EXPERIMENT In Chapters 1-6 you learned to design an experiment, write a procedure, and construct data tables and graphs. In this chapter you focused on making sense of an experiment. You analyzed and interpreted the data. You developed a conclusion to summarize, explain, and critique your findings. You have the skills to write an experimental report which consists of: ►

Experimental Design Diagram;



Procedure-Methods/Materials;



Results-Data Tables, Graphs, and Interpretation; and



Conclusion.

Conduct the experiment in Box 7-4, Pearly Environments. Write an experimental report. Assess the experimental report using the information in Box 7-5, Checklist-Experimental Report.

] 15 u

0

iii'

e

5

. . . ."""""..........______________.;;...___........;.,.....................,;..;...;.,....__ _.......;_ _ _ _ _ _..,;___.:..:..,_.;..........,;...;:.;[email protected]

214

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

EXPERIMENT Pearly Environments QUESTION

How do different liquids impact the size, shape, and surface braiding of water pearls?

HYPOTHESIS

Construct your own.

MATERIALS

SAFETY



► Wea r side vented chemical

Wat er pearls, 50 or more

splash goggles and appropriat e prot ective clot hing.

► Various liquids such as:

• Distilled water • Tap water



• 5% sa lt solut ion-mix 5 g of salt w ith 95 m l of distilled water

Do not ingest t he wat er pearls or any of the solutions.



• 5% white vinegar, which is t he typical concentration sold

Do not put t he wat er pearls in a water drain.

► Wash hands af t er

• 5% baki ng soda solution-mix 5 g of baki ng soda wit h 95 ml of distilled water ►

Graduated cylinder, 100 ml



Small plastic cont ainers w ith lids, such as used for individual servings of salad dressing, 5 or more



Timer



St rainer with small holes, such as a mesh kitchen stra iner



Container to catch wat er



Pa per towels

investigating . ►

Follow your teacher's direct ions for saf ety, clean ing t he laboratory, and disposing of t he water pea rls and solutions.

► See Appendix B, Using Safe

Procedures

► Dark surface ►

Camera

215

PROCEDURE 1. Determine the mass of water pearl in grams. Repeat for additional trials. 2. Put water pearls in a container with a lid. Add the first liquid . Close the lid. Label the container with the soaking time. Use the data from Fresh Water Pearls to decide on the soaking time. 3. After the designated time strain the liquid from the pearls. Use a paper towel to absorb excess liquid. 4. Photograph the water pearls. 5. Determ ine the mass (g) of the water pearls. Return the pearls to the container. 6. Repeat steps 2-5 for other liquids.

ANALYZING, EXPLAINING, AND COMMUNICATING THE EXPERIMENT 1. Prepare a report that includes an experimental design diagram, procedure, results, and conclusion. 2. Use the checklist in Box 7-5 to assess and improve the report.

216

:J/J-1

i\_1 ..S

ECKLIST xperimental Report

EXPERIMENTAL COMPONENT

SELF CHECK

PEER CHECK

POINT VALUE

GRADE

EXPERIMENTAL DESIGN DIAGRAM 1. Is there a testable question that communicates what you want to learn about the interaction of the IV and DV?

2

2. Is there a hypothesis that clearly states how changing the IV will impact the DV? Is the reason stated?

2

3. Is an IV identified? Are the levels of the IV identified? Are the IV and its levels operationally defined?

4

4 . Is a control group identified? Justified?

2

5. Are one or more DV identified? Operationally defined?

4

6. Are the controlled variables (constants) identified? Operational ly defined?

4

7. Are sufficient repeated trials included?

2

8. Does the experimenta l design diagram correctly commun icate the experimental components?

4

PROCEDURE- METHODS/MATERIALS 9. Does the procedure contain specific details about the materials and equipment and how they were used?

4

1O. ls the procedure sufficiently precise to be repeated by others?

8

11 . Does the procedure state how the data wil l be collected? Analyzed?

4

12. Does the procedure include appropriate safety precautions?

4

RESULTS-DATA TABLES, GRAPHS, & INTERPRETATION 13. Are correct measures of central tendency selected? Are they correct ly calculated? Rounded?

3

14. ls the variability w ithin the data described? Is the variabi lity correctly calculated? Rounded ?

3 217

Does the interpretation of the data: 15. Com pare t he measures of cent ral tendency? Describe implications?

4

16. Compare t he variabil ity? Describe impl ications?

4

17. Discuss major trends? Describe implications.

6

18. State if the hypot hesis is support ed or refuted?

4

19. Include correct spelling and g rammar?

4

CONCLUSION Does the conclusion: 20. State the init ial hypothesis (claim)?

2

21. Summarize how the hypothesis (clai m) is supported or refuted?

6

22. Explain the experiment al f indings?

6

23. Critique the experiment? Recommend improvements?

6

24. Recommend future experiments?

2

25. Include correct spelling and g rammar?

6

TOTAL COMMENTS

218

100

Chapter 7

Making Sense of Experiments

219

EXPLORING STEM CONNECTIONS Many scientific concepts and innovations are related to the two experiments, Fresh Water Pearls and Pearly Environments. Explain the science of sodium polyacrylates and the many ways they are used to meet human needs related to agriculture and personal care products. Use your knowledge of percent and rate to explain changes in the surface area and volume of the water pearls. As before, select among the options or explore a teacher-assigned or self-selected topic.

220

STEM PERSPECTIVE Water Pearls

Science Explaining how the natural world works 1. Ecosystems: Interactions, energy, and dynamics. Sodium polyacrylate has been used in growing nursery plants, enhancing water avai lable to planted trees, and improving the general soil. Research these uses of non-soluble hydrogels. Which do you recommend? Explain. 2. Matter and its interactions. What is an intelligent gel? What are some products that incorporate an intelligent gel? Select a product and research how the gel functions. 3. Structure and function. Harvard scientists are experimenting w ith hydrogels, and using them as "muscles" to move tiny structures. What inspired th is research? What is the current status of the research? Implications for future technologies? (Sciencenter, 2011) 4. Earth and human activity. Explore the fol lowing connections. a. The first disposable diaper, Pampers, was manufactured in 1961. Environmentalists criticize the use of disposable diapers. Why do "green advocates" recommend cloth diapers? b. Polymers are used to clean and control oil spills. How do these polymers work? Compare these polymers w ith the sodium polyacrylate used in the experiment.

221

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Technology and Engineering Modifying the world to meet human needs and wants 5. Engineering design. In Chapter 14 apply your knowledge of hydrogels to brainstorming solutions to engineering problems (see Box 14-1 ). 6. Links among engineering, technology, science, and society. Choose from the following examples. a. Many personal care products contain hydrogels. What are some products that contain hydrogels? What are the pros/cons of using hydrogels in these products? You r recommendations? b. Soluble sodium polyacrylate gels dissolve in water. These gels have weak cross-l inks between the polymer chains. These soluble gels are used in arid areas which are heavily irrigated. What are the pros/cons of this usage? Your recommendations?

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Mathematics Describing, analyzing, and interpreting patterns and relationships

7. Exploring surface area and volume. A student measured the diameter of a water pearl before and after soaking the pearl for 150 min in distilled water. Calculate the surface area and volume of the pearl. Because the pearl is spherical use the volume and surface area formulas for a sphere. Volume = 1TTd3 6

Surface Area = TTd2

Time (min) Diameter (mm)

0

150

0.33

1.34

Surface Area Volume a. Focus on units. Since the d iameter of t he water pearl was measured in mm, what units should be used for the surface area? The volume? b. Exploring surface area and volume relationships. After 150 mi n, how many times larger is t he diameter of water pearl? The surface area? The volume? c. Using these relationships to make predictions. If a water pea rl with an original diameter of 0.23 grew five times larger, predict how many times larger the surface area would be. Also predict t he change in volume .

8. Percent increase. Use your Fresh Water Pearls data, or the data below, to calculate the percentage increase in the mass of the water pea rls for each 30-min t ime interval. Time (min) Mass (g)

0

30

60

90

120

150

180

0.15

0.58

0.82

1.05

1.24

1.45

1.50

%Change a. What does it mean when the percent change is greater than 100%? b. What does it mean when the change is less t han 100%?

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9. Average rate of change in mass. Determine the average rate of change for each 30-min t ime interval. Time (min)

0

30

60

90

120

150

180

Mass (g)

0.15

0.58

0.82

1.05

1.24

1.45

1.50

Average Rate of Change

--

a. Is the average rate of change the same for each 30 min? b. What does th is tell you about the increase in t he mass of the pearls over the entire 180 min? c. Is this data linear? How do you know?

10. Developing mathematical models. In Volume 2 (Chapter 15) learn about various mathematical models. Determine which mathematical models best fit the data collected in Fresh Water Pearls and/or Pearly Environments..

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REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Brockway, D., Libera, M ., & Welner, H. (20 11). Hydrogel beads: The new slime lab. The Science Teacher(78) (5),50-55. Confrey, J., & Krupa, E. E. (20 12). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G. Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. Harris, M . E. (2002). Slurper balls. Science Scope (25) (4), 22-27. Helmenstine, A . M . (2014, December). How do disposable diapers work? Why do they leak? Retrieved from http://chemistry.about.com/od/howthingsworkfaqs/f/diapers.htm Laposta, M., & Brown, T. Wonderful waterlock-teacher notes. Technology-Enhanced Activity Modules for Science (TEAMS). Retrieved from http://teams.kennesaw.edu/waterlock/wlock-docs/ waterlock-teacher-notes.pdf Milner-Bolotin, M . (2012). Growing water pearls. The Science Teacher (79) (5), 338--41. Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_S tandards. pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Polymer Science Learning Center Foundation (1995-2012). Polyacrylates. Macrogalleria: A Cyberwonderland of Polymer Fun. Retrieved from http://pslc.ws/macrog/leve13.htm Salinger (2008, January 9). Definition of STEM. In Arlington County Public Schools. Career, technical and adult education advisory committee report. Arlington, VA: Arlington County Public Schools. Retrieved from http://www.apsva.us/cms/lib2NA01000586/Centricity/Domain/29/ CTAE_Committee_Report.pdf Schiller, E., & Yezierski, E. (2009). No more leaks! Science Scope (32) (2), 16-21. Sciencenter (2011). Exploring Materials- Hydrogel. NanoDays. Retrieved from http://www.nisenet. org/sites/default/files/catalog/uploads/8882/materialshydrogel_guide_3 l oct 11.pdf

T Engaging in Engineering Design

CHAPTER 8 Designing, Building, and Testing a Model

J,

CHAPTER

8 ---------Des ignin g, Building,

0

anti Testing a Model

CONTENTS Introduction Learning Objectives Correlations Wit h Nationwide Standa rds

230 230 230

Designing a Device to Solve a Problem Box 8-1 Engineer-Shake It Up

232 235

Engineering Design Process Ident ify t he Problem Determi ne Criteria and Constraints Brainst orm a Solution Plan and Select a Design Bu ild a Model Test, Eva luate, and Redesign Sha re the Resu lts

237 237 237 237 238 238 239 239

Using Brainstorming and Argumentation Effectively Brainstorming Argumentation Box 8-2 Engineer- Life Savers

239 239 240 241

Using a Rubric to Assess a Design Box 8-3 Rubric-Engineering Design

242 243

Focusing on Design Box 8-4 Engineer-Wind Power

244 245

Assessing and Improving a Design Brief Box 8-5 Checklist- Design Brief Comparing Assessments Box 8-6 Pract ice- Writ ing a Design Brief

247 248 249 251

References

253 229

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INTRODUCTION Scientists use investigations to discover and explain natural phenomena. Engineers design humanmade objects which have a purpose for humanity and solve a problem. In creating designs engineers use information that scientists and mathematicians have discovered about the natural world, patterns, and relationships. As engineers design and create models they constantly test and refine their solutions. In Chapter 8, you will learn about an engineering design process and engage in engineering several devices-an earthquake resistant building, a floatation device, and a low-cost windmill for under-developed areas.

Learning Objectives Specific learning objectives for Chapter 8 , Engaging in Engineering Design, include: ►

Apply the engineering design process to create a device to meet a need: 0

Identify the problem;

0

Determine the criteria and constraints;

0

Brainstorm solutions;

0

Plan and select a design;

0

Build a model;

0

Test and evaluate the model;

0

Redesign the model; and

0

Share the results.

0

Use the STEM literature to research scientific and mathematical concepts and prior engineering designs;



Write a clear and precise procedure for constructing a model from a design including costs and materials;



Use brainstorming skills throughout the design process;



Use argumentation skills throughout the design process;



Use a rubric to assess and improve an engineering design;



Write an engineering design brief; and



Use a checklist to assess and strengthen an engineering design brief.

Correlations With Nationwide Standards For correlations of the chapter learning objectives and STEM concepts with nationwide learning standards, see Table 8-1 and Appendix A.

Chapter 8

TABLE 8-1

Designing, Building, and Testing a Model

231

Correlations With Nationwide Standards

NEXT GENERATION SCIENCE STANDARDS ► Scientific & Engineeri ng Practices: Asking questions and defining problems; Developing

and using models; Planning and carrying out investigations; Analyzing and Interpreting data; Using mathematics and computation t hinking; Constructing explanations and designing solut ions; Engaging in argument from evidence; Obtain ing, evaluat ing, and communicating information ► Cross-Cutting Concepts: Syst ems and system's models; Energy and matter: Flows, cycles, and conservation; Stability and change ► Disciplinary Core Ideas: Matter and its interaction; Energy; Earth's Systems; Eart h and human activity; Engineering Design; Links among engineering, technology, science, and society

COMMON CORE STANDARDS-MATHEMATICS ►

Mathematical Practices: Make sense of problems and persevere in solving; Construct viable arguments and critique the reasoning of others

COMMON CORE STANDARDS-LITERACY IN SCIENCE AND TECHNICAL SUBJECTS ►

Reading: Determine key ideas or conclusion; Follow mult i-step procedure; Distinguish among facts, reasoned judgment , and speculation ► Writing: W rite information/explanatory t exts; Produce clear and coherent w rit ing; Use technology to produce and distribute w rit ing; Gather relevant information; Draw information from informational t ext s

ISTE STANDARDS-STUDENTS ►











Creativity and innovation: Apply existing knowledge to generat e new ideas, products, or processes; Use models and simulations to explore complex syst ems and issues; Create original w orks as means of personal or group expression Communication and collaboration: Interact, collaborat e, and publish ... employing a variety of digital environment s and media; Communicate information and ideas effectively to mult iple audiences using a variety of media and formats; Cont ri but e to project teams to produce ori ginal works or solve problems Research and information fluency: Plan strateg ies to gu ide inqu iry; Locate ... use information from a variety of sources/media; Evaluate and select information sources and digital tools based on the appropriateness to specif ic tasks; Process data and report results Critical thinking, problem solving, and decision making: Ident ify and define aut hentic problems and significant questions for investigations; Plan and manage activities t o develop a solution or complete a project ; Collect and ana lyze data to identify solutions and/or make informed decisions; Use multiple processes and diverse perspectives to explore alternative solut ions Digital citizenship: Advocate and pract ice safe, lega l, and responsible use of information and technology; Exh ibit a positive attitude toward using technology that supports collaboration, learning, and product ivity; Demonstrate personal responsibility for ... learning Technology operations and concepts: Underst and and use technology syst ems; Select and use applications eff ect ively and productively

Source: Confrey & Krupa, 2012, p. 9; Morphew, V. N., 20 11, pp. 299- 300; Nationa l Governors Association Center for Best Practices, 20 10, English language & literacy, pp. 64-66; National Governors Association Center for Best Practices, 2010, Mathemat ics, pp. 6- 8; NGSS Lead States, 20 13, Volume 1, p.1; NGSS Lead States, 201 3, Volume 2, pp. 67- 79.

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DESIGNING A DEVICE TO SOLVE A PROBLEM Engineers create solutions to problems. To solve an engineering problem, you first need to understand the problem you are trying to solve. You also need to understand the scientific and mathematical concepts necessary to solve the problem. Engineers use a design process to help them solve a problem. Just as there is no one scientific method, there is no one engineering design process. However, there are general strategies that engineers use. Figure 8-1 shows the major strategies used by engineers when designing and building an object.

FIGURE 8-1

Engineering Design Process

©courtesy of Cothron

Just reading the diagram is not an effective way to learn about engineering. Instead, you will apply the process to meet a human need--designing an earthquake resistant building. To design the building you will use scientific concepts related to the pendulum experiment in Chapter 1.

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233

In Table 8-2, elements of a scientific experiment and an engineering project are shown. As you can see there are similarities and differences in the processes, and different terms are used. Just as the best way to learn about experimentation was to "do an experiment," the best way to learn about engineering is to "design, build, and test a model." An engineering design brief for an earthquake resistant building is found in Box 8-1, Shake It Up.

TABLE 8-2

Scientific Experimentation Versus Engineering Design and Build

Science Explaining how the natural world works

Engineering Modifying the world to meet human needs and wants

Experimental Topic

Problem

Brainstorm Ideas

Brainstorm Ideas

State the Problem

State a Potential Solution

Testable question and hypothesis

Must meet criteria and constraints

Experimental Design Diagram

Plan and Design the Solution

Procedure-Methods & Materials

Procedure-Build & Test the Model

Conduct the Experiment

Test the Model

Results

Results

Tables, Graphs, & Interpretation

Test Data & Pros/Cons of Model Redesign and Testing of Model

Discussion & Conclusion

Discussion & Conclusion

Support for hypothesis, explanation, and critique including limitations and recommendations for future experiments

Description (working model), how met constraints, results of testing, success, or areas for future modifications

Future Experiments

Future Engineering Designs

234

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

ENGINEER Shake It Up BACKGROUND Tall buildings are especially susceptible to damage during earthquakes. Pendulums have been found to help counter the effect of seismic action and reduce damage to tall buildings. These special pendulums are called "tuned mass dampers." PROBLEM Design a build ing wh ich uses pendulum(s) to counter the effect of an earthquake.

CRITERIA AND CONSTRAINTS ►

Model must be between 30 and 50 cm tall.



Model must be mounted on the same type of platform for testing.



Quantitative data must be used to determine the success of the model.

MATERIALS

SAFETY



Drinking straws





Tape

Wear shock-resistant safety goggles and appropriate protective equipment.



Follow your teacher's directions for safety, clean ing the work area, and disposing of materials.



See Appendix B, Using Safe Procedures.

► Popsicle sticks ►

Cardboard



String



Washers of varying weights

► Glue

. , --: r- ..

,



Metric ruler



Protractor



Timer

► Shaking device for testing ►

--

·~~

.

.._

t......,..

-~ -

&



( .,1

Safety goggles

BRAINSTORM IDEAS ►

Understand the science behind how a pendulum works . Understand how earthquakes affect human-made structures.



Learn what has been done previously to make buildings more earthquake resistant.



Determine how the criteria and constraints w ill affect your solution.



Brainstorm various solutions and select one to design . 235

PLAN AND SELECT A DESIGN ►

Make a sketch of the design.

BUILD A MODEL ►

Build the model using the sketch as a guide.

TEST AND EVALUATE THE MODEL ►

Determine how you will test the model and what outcomes you wi ll use to measure the model's success.

► Test the model and collect the data. ►

Determine if the design was successful or if modifications are needed.

REDESIGN ►

If the model was not successful re-design and re-test.

SHARE ►

Demonstrate the model.

NOTES

236

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237

ENGINEERING DESIGN PROCESS Identify the Problem Engineers design solutions to problems. Often this involves designing a particular device which will be used to solve a specific problem. Engineers use scientific and mathematical concepts to fully understand a problem before they begin. Before designing a device to solve a problem you must understand exactly what the problem involves. A design brief is used to describe the problem and the solution required. In Shake It Up the problem was related to science concepts from Chapter 1 where you conducted an experiment involving pendulums (see Box 1-1 ). You experimented to learn how pendulums work and to build your knowledge of pendulums. In the STEM extensions you used mathematics to detect and explain patterns in the experimental data. These experiences provided background information to help you design a model to meet a human need-an earthquake resistance building.

Determine Criteria and Constraints The criteria and constraints tell you the parameters you must work within to solve the problem. The criteria are conditions which must be followed in constructing the model; they tell you what must be included in the design. It is very important to follow the criteria and constraints, which are often included in the same category. The constraints describe the restrictions of the design. The constraints may keep the design from being the best you could build. In Shake It Up one of the constraints was the size of the building. Often financial constraints are a major factor in trying to solve a problem. In your research about earthquake resistant buildings you may have learned that a pendulum is one of the most effective ways to minimize earthquake damage to large skyscrapers. However, it is very expensive to incorporate "tuned mass dampers" into a building. If the system is not required builders may not include it because it will affect their ability to recoup their investment. The same financial constraints happen in classroom or home projects. You may think it would be more effective to construct your building from a commercial product; however, your teacher may not have classroom materials because they are too costly. Even at home you will have constraints on what is available for you to use or to purchase. It is important to realize that the best solution may not be possible given the constraints of the problem. It is the engineer's job to create an effective way to solve the problem within the constraints.

Brainstorm a Solution After you determine what the problem is and identify the criteria and constraints, the next step is choosing a design to solve the problem. However, before choosing a design you must brainstorm potential solutions to the problem. Brainstorming a solution includes conducting research about the problem. This can be research about any aspect of the problem. In Shake It Up you needed to learn about earthquakes-why they happen, where they occur, and the damage they cause. You also may have researched how tall buildings react to seismic waves caused by earthquakes.

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Because understanding how a pendulum operates was important, you may have researched pendulums and why they are useful in a building during an earthquake. A very important component of brainstorming solutions is learning how the problem has been solved in the past. There may be a solution you can build upon and improve instead of starting from scratch. All the information you collect will help you brainstorm a better solution for the problem.

Plan and Select a Design While conducting the research for Shake It Up you probably started thinking about designs that would solve the problem. The next step is to select a design and make a sketch of the design. You can make this sketch by hand or use computer-aided design software to make the designs. The sketch should include the dimensions of the model and, when possible, different visual perspectives of the design. There are many software programs and computer tools that help engineers make a design of their solution. These programs can often create 3-D images of the design which help engineers envision all angles of the design before it is constructed or manufactured. You may know of some free tools online to help you create a 3-D image of your design. An example of a few of these tools is included in Table 8-3.

TABLE 8-3

3-D Design Modeling Applications

Tinkercad-https ://www.tinkercad.com 3D Crafter-http://amabilis.com Sketchup-http://www.sketchup.com/products/sketchup-make Blender- http://www.blender.org

When selecting a design you must keep in mind the materials that are available to create the design. The design plan should include the exact materials needed to create a model or prototype of the design and their cost.

Build a Model Once the design is completed it is time to build a model or prototype of the design. Just as you need a procedure for conducting an experiment, you need a procedure- or set of directions- for building a model. The procedure must be sufficiently clear to replicate the model. As you write the procedure you need to reference the design diagram. Detailed procedures are necessary for you to replicate and improve designs or for others to modify the design. Often you will find that building the model does not go as planned, and you will need to refine the procedures. For instance, you may have planned to use a certain substance to hold the model to the Shake It Up platform. But once you built the model and tried to attach it to the platform, the substance was not as strong as you anticipated. The model fell down! Do not worry if you need to revise at this point. Continuous revision is a critical part of the engineering design process and will help to create the best solution to the problem!

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239

Test, Evaluate, and Redesign To determine if a design is effective it is critical to simulate real conditions. Testing and evaluating the model you created are similar to the methods used to perform scientific investigations. In advance of testing you will need to determine the outcome(s) you will measure to determine the success of the model, and operationally define them. You might measure the time the building stands or its angle of deviation from the perpendicular. You must keep the testing conditions the same each time you test a model. You can think of the testing process as a form of an experiment. The model is a version (level) of the independent variable, the outcomes are the dependent variables, and the testing conditions are the controlled variables (or constants). Each model you test is another "version (level) of the independent variable" and your task is to select the best version. If the model does not perform as expected then you need to redesign the model, test again, and

continue the process until you have a model that works as it should. You can learn more about procedures for testing, evaluating, and redesigning a model in Volume 2 (Chapter 13).

Share the Results In sharing the results it is important to describe the design and model, and if possible demonstrate the model in action. You also need to describe how the model meets the criteria and constraints. Critique the design and describe modifications which need to be tested. As with a science experiment, use the STEM literature to support and explain decisions you made. You can learn more about writing formal engineering papers and presenting at conferences in Volume 2 (Chapters 14 and 18)

USING BRAINSTORMING AND ARGUMENTATION EFFECTIVELY Brainstorming Brainstorming is an activity to help you come up with ideas about a particular topic. Brainstorming is a very important part of the engineering design process. It is often done as a group activity and is very helpful in coming up with as many solutions as possible to a problem. While brainstorming can appear to be disorganized, the following pointers will strengthen brainstorming with a group or even by you. ►

Quantity. Brainstorm as many ideas as possible. Do not limit yourself. More ideas will help you make connections and might pose a solution down the road if your original solution does not work out.



Be positive. Do not criticize your teammates (or your own) ideas while brainstorming. The purpose is to get many ideas out.



Be open. Allow wild ideas while you are brainstorming. You never know when there might be something in a wild idea that just might work, or make you think of something else that could be a solution.

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Write everything down. No matter how crazy an idea might seem, write it down.



Combine ideas. As you brainstorm, ideas might naturally start to come together. Combine these ideas and write them down too.



Stay on topic. It is very easy to go off topic with brainstorming. Stay focused on the problem you are trying to solve (Cooper, Zarske, & Carlson, 2008; Cornell University, 2015; Science Buddies, 2002- 2015).

During the brainstorming process you will generate lots of ideas. It is important to review the STEM literature and to use the findings to revise a brainstormed list of experimental ideas. Similarly, you should use the STEM literature to better understand potential solutions to the problem. Some useful questions to guide your research are: ►

What products solve a similar problem?



What are the strengths and weaknesses of products that solve a similar problem?



What are key must-have features of products that solve a similar problem?



Why did the engineers that built these products design them the way they did?

Sometimes you may only be able to find information from print or electronic resources about the solution, but if you have the opportunity to see the solution in person, it will greatly help in understanding the engineering design and what you might change in the design. After researching products, review the brainstormed list and see what needs to be added or removed as potential solutions.

Argumentation Argumentation and brainstorming serve different purposes. Brainstorming enables you to come up with many ideas. Argumentation enables you to compare ideas and to reach an evidence-based conclusion. Each time you discussed options for the earthquake resistant building you engaged in argumentation. Evidence-not opinion- is required for a good argument. The Next Generation Science Standards identify "engaging in argument from evidence" as a practice used by engineers as they design solutions to problems. Specific argumentation skills include: ►

Construct and/or support an argument with evidence;



Distinguish between evidence and opinions in one's own and others' arguments;



Listen actively to arguments to indicate agreement or disagreement, based on evidence; and



Respectfully provide and receive critiques from peers by citing relevant evidence and posing specific questions to clarify information provided by a peer (NGSS, 2013, pp. 76- 77).

In the next engineering activity, Life Savers, focus on using brainstorming and argumentation skills effectively. This engineering challenge involves designing a floating device for humans (Moyer & Everett, 2012). In Chapter 2 you experimented with the buoyancy of an egg in various saltwater solutions. In Box 8-2 you will apply this scientific concept to designing a lifesaving flotation device.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

ENGINEER Life Savers

BACKGROUND

Personal flotation devices (PFDs), also com monly ca lled life jacket s, save many lives in t he wat er each year. PFDs are designed to provide extra buoyancy for a person in order to float in t he water. PFDs are not one-size-f its-all devices and are carefu lly designed to be effective based on the size and weight of the person wearing it. They are also designed in such a manner t hey keep t he user from being face-down while floati ng in t he water.

PROBLEM Design a PFD for a smal l action f igure t hat wi ll enable it to float in the wat er so its face is not immersed in t he wat er. CRITERIA AND CONSTRAINTS ► Action figure must float. ►

Action figure must not be face down while fl oati ng.

► Density of action figu re with and without PFD shoul d be

determined .

MATERIALS

SAFETY



Plastic action f igure that is 4-5 cm tall and will sink

► Wea r safety goggles and appropriate

Graduat ed cylinder (big enough to f it the action figure) with water



Use caution w hen using scissors.



Use caution when using hot glue gun.



Follow you r teacher's directions for safety, clean ing the work area , and disposing of materials.



See Appendix B, Using Safe Procedures.

► ►

Electronic or Triple Beam Balance



Plastic shoebox (or similar container) with water



Flexible foa m material



Scissors



Hot glue gun



Safety gogg les

protective clothing.

241

BRAINSTORMING IDEAS 1. Brainstorm potential solutions to the problem . 2. Use the following questions to guide your research: ►

What products solve a simi lar problem?



What are the strengths and weaknesses of products that solve a similar problem?



What are key must-have features of products that solve a similar problem?



Why did the engineers that built these products design them the way they did?

3. Use the research to revise the brainstormed list. 4. Review the bra instormed list against the criteria and constraints. 5. Use argumentation skills to select a design to pursue.

DESIGN, BUILD, TEST, AND REDESIGN Use your brainstorming and argumentation ski lls to effectively achieve these components of the design process.

SHARE YOUR FINDINGS Use your argumentation skil ls to plan and deliver a presentation and to respond appropriately to questions and input from your peers.

USING A RUBRIC TO ASSESS A DESIGN 1. Use the rubric in Box 8-3 to access your solution for a personal flotation device. Just as a checklist, the rubric communicates the expectations for success. 2. Based upon the rubric, what were the strengths and weaknesses of your design? 3. How cou ld you make your solution more consistent with the design criteria and constraints?

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RUBRIC Engineering Design Category

Below Expectations

Meets Expectations

Exceeds Expectations

Defining the Problem

Rephrases the problem w ith limited clarity.

Rephrases the problem clearly.

Rephrases the problem clearly and precisely.

Brainstorming Ideas

Contributes few or implausible ideas.

Contributes a plausi ble idea.

Contributes multiple plausible ideas.

Contributes ideas, but without documented research or experimental design.

Contributes one plausi ble idea based on docu mented research and includes experimental design of research conducted.

Contributes multiple plausible ideas based on documented research includes multiple experimenta l designs of research conducted.

Plan and Design

Building a Model

Test and Evaluate

Redesign

Sharing

Produces incomplete sketches. Does not present a concept.

Produces marginally accurate pictorial and orthog raph ic sket ches of design concepts.

Produces accurate pictorial and orthographic sketches of design concepts.

Model meets the task criteria to a limited extent.

M odel meets the task criteria.

Model meets and exceeds criteria in insightful ways.

Testing and evaluation processes are inadequate.

Testing and evaluation processes are adequate for refining the problem solution.

Testing processes are innovative.

Redesign based on testing and evaluation is not evident.

Redesign is based on t esting and evaluation.

Significant improvement is made to the design based on testing and eva luat ion.

Solution is presented w ith limited detail to the process and how model meets t ask criteria.

Solution is present ed accurately with some detail about the design process and addresses how t he solution meets task criteria.

Solution is presented accurat ely w ith great detail about process and includes supporting evidence as to how the solution meets task criteria. 243

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FOCUSING ON DESIGN You have designed two devices to meet human needs-an earthquake resistant building and a personal flotation device. In both cases you completed the full engineering design process. When the cost of developing and testing models is high, engineers may submit a proposal which consists of the design, the procedure for building and testing the model, and projected costs. A committee of engineering experts will review submitted proposals and select one or more to fund . Once a proposal is chosen, the engineers will build a model, test it, and redesign to develop a final solution. In Box 8-4, Wind Power, you will focus on designing a low-cost windmill to use in a sparsely populated area of an under-developed region or country. This engineering challenge is based upon a proven design, the windmill. In Chapter 3 you conducted an experiment, Huff, Puff, and Slide, which used a person's breath (wind) to move a cup containing pennies. Although this experiment provides some background for the engineering challenge, you need to fully understand how windmills operate. The following questions will help you acquire essential knowledge: ►

Who invented ____?



How does a ____ work?



What are different parts of a ____ ?



What are important characteristics of a ____ ?



How is performance measured for a ____ ?



What is ____ made of?



Why is ____ made from or using ____ ?



What are the best materials, components, or algorithms for building ____?

Once you understand the device, you will use your brainstorming and argumentation skills to brainstorm modifications, decide on an approach, write a procedure for building and testing a model, and estimate the cost of the full-scale windmill.

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

ENGINEER Wind Power BACKGROUND Wi nd power has been harnessed for cent uries. Old windmills converted the kinetic energy of wind to the mechanical energy needed to run mills and pu mps. Today's w indmills work similarly in harnessing the w ind's energy which is converted into mechanical energy and t hen electrical energy. In sparsely populated undeveloped areas, small-scale lowcost windm il ls are needed to pump water, grind grain, lift objects, and produce small amount of electricity for home use. PROBLEM

Design a windmi ll which can meet one or more needs in a sparsely populated under-developed area .

CRITERIA AND CONSTRAINTS 1. Must be constructed from locally ava ilable mat erials, including recycled materials. 2. Must be constructed in a short time frame. 3. Must meet one or more of t he designated needs in t he region or country selected. Must be effective w ithin the typical w inds available in t he area. 4. Must be cost-effect ive. 5. Must be highly durable and easy to maintain.

BRAINSTORM, PLAN, & DESIGN 1. Acquire fun dament al knowledge of how windmills function. ►

Who invented _ _ _ 7



How does a _ _ _ work?



What are different parts of a _ _ _ ?



What are important characteristics of a _ _ _ ?



How is performance measured for a _ _ _ ?



What is _ _ _ made of ?



Why is _ _ _ made from or using _ _ _ ?



What are t he best materials, components, or algorithms for building _ _ _ ?

2. Select an area where w indmills are needed and investigate its resources, climate, and winds. Determine what the greatest needs are that a w indmill cou ld meet.

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3. Brainstorm modifications needed for the targeted need and location . ►

What products solve a similar problem?



What are the strengths and weaknesses of products that solve a similar problem?



What are key must-have features of products that solve a similar problem?



Why did the engineers that built these products design them the way they did?

4 . Decide on an approach . 5. Develop a detailed design and procedure for constructing and testing a model. Include materials, cost, time to construct, and how you wi ll test under conditions sim ilar to the targeted area.

SHARE Prepare an oral presentation w ith visua ls which you can give to the selection committee.

NOTES

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ASSESSING AND IMPROVING A DESIGN BRIEF A design brief is used to describe the problem and the solution required. Just as a good experimental design is essential for a quality experiment so is a good design brief essential for a quality engineering solution. The checklist in Box 8-5 is similar to the ones you used in Chapters 1 and 2 to assess an experiment. Use the questions to assess the components of the Shake It Up design brief. In the checklist you will check if the components are included. Just put a mark by the included components.

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, esign Brief SELF CHECK BACKGROUND 1. Is there background information to set the stage for the problem?

PROBLEM 2. Is there a problem statement? 3. Does the problem statement clea rly convey what should be developed?

CRITERIA AND CONSTRAINTS 4. A re there criteria and constraints? 5. Are the criteria clearly defined to indicate the parameters of the solution? 6. A re the constraints well-def ined? 7. Is informat ion about the timeline and allowable costs included?

MATERIALS 8. Is there a materials list ? 9. Can the materia ls be reasonably obtained?

BRAINSTORM IDEAS 10. Does t he brief contain examples of research which might be helpful t o t he engineer?

PLAN AND DESIGN 11 . Is there a statement that describes the type of design plan required?

BUILD A MODEL 12. Is a w ritten procedure required ? 13. ls the proced ure linked to the design? 14. A re safety risks addressed?

TEST AND EVALUATE 15. Are specific outcomes stated in t he criteria? Operationally def ined? 16. ls the met hod for t esting the model stated in t he criteria?

REDESIGN 17. Is a timel ine or the number of redesigns included as pa rt of the crit eria/constraints?

SHARE RESULTS 18. ls it clear how the results w ill be shared, e.g., face-to-face presentation, w ritten paper, Web present ation? 19. ls a demonstration requi red? W ill a video suffice?

TOTAL COMMENTS

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PEER CHECK

PEER CHECK

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249

Comparing Assessments Using your completed checklist for the Shake It Up design brief, let's compare assessments. Background. Yes, the design brief includes information to set the stage for the problem state-

ment. It may be helpful to have more information, but this could depend on the audience and their knowledge of the problem. Problem. The problem is clearly stated and enables someone to understand the task to be

accomplished. Criteria and constraints. While this section is included, it could be improved by having more specific information about how the model will be tested and the criteria for success. Leaving these factors open may lead to misinterpretation of the intent of the design. Materials. There is a materials list included. It is not clear if these are the only materials that

can be used. More specific information is needed about materials, such as tape and glue. Brainstorm ideas. A list of topics for research is included that may be helpful in solving this

problem. Plan and design. The design brief says to include a sketch. One would assume either a hand-

drawn or computer-aided design is acceptable, but it would be helpful to have this clearly stated. There is not an indication that cost is a factor for either the model or the final product. Build a model. The brief does not state that a written procedure is required. To enable the

engineer, or others, to recreate the model a clear precise procedure should be required. The procedure should reference the design. Safety risks are addressed. Test and evaluate the model. No outcomes for the model are stated. The engineer must

decide upon the outcomes and how they will be measured. No specific testing method is described. The engineer must determine how to test the model. The design brief would be stronger if these conditions had been stated in the "Criteria and Constraints." Redesign. No time limit is stated. Generally a design brief includes a time limit in the "Cri-

teria and Constraints." The number of redesigns is not stated. Often the number of redesigns is constricted by funding and it is up to the engineering design team to decide what is possible. Share results. It is not clear how the results should be shared. Is a written report required? Is

a face-to-face or Web presentation required? How did your analysis compare to our analysis? By adding details, the engineering design brief for Shake It Up could be made stronger. It is a careful balance to provide enough details for an engineer to solve a problem, but not so much information that you bias the engineer's approach. When you design an original engineering project you will need to write a design brief to guide your work. For practice, write a design brief for one of the problems in Box 8-6. Use the checklist to assess and improve the design.

250

Name _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ Date _ _ __

PRACTICE Writing a Design Brief DIRECTIONS ►

Write a design brief for an engineering problem. You may use one of the examples below, a problem assigned by you r t eacher, or a self-select ed problem.



Include the following components in the design brief: backg round, problem, criteria and constraints, mat erials, resources for brainstorming, requ irements for plan/design, requirements fo r model, method of t esting and evaluat ing model, limitations on redesign, how results w ill be shared.



Use the checklist to assess and improve t he design brief (see Box 8-5).

1. Select a t opic and write a design brief: a. Design a structure to reduce erosion on river-front property. b. Design a hydropon ic system wh ich can be used to grow lettuce on a deck.

c. Design a reusable cold pack which will keep a chicken sandwich cool for six hours. d. Design a safe and environmentally friendly cleaner fo r vehicle w indows. e. Design a helmet wh ich reduces collision injuries. f. Design a system for producing ethanol from animal waste. g. Design a brace to reduce carpel tunnel syndrome among com puter data processers. 2. In t he twentiet h century eng ineering achieved grand accomplishments. Many of these accomplishments are unavailable in under-developed regions or cou ntries. Research major accompl ishments at the National Academy of Engineering (http:// great ach ievements.org/). As a team, or class, write a design brief to gu ide modification of a product fo r use in an under-developed region or country. 3. Grand eng ineering challenges have been identified for t he twenty-first cent ury. As a t eam, or class, select a challenge of interest , identify a specific problem, and write a design brief t o guide development of a solution. For the challenges see the National Academy of Eng ineering (http://www.eng ineeringchallenges.org/cms/challenges.aspx)

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REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. American Wind Energy Association. (1996-2015). Wind 101: the basics of wind energy. Retrieved from http://www.awea.org/Resources/Content.aspx?ItemN umber=900 Archibald, L., & Christen, R. (1988). Blow them away. Science Scope, Nov/Dec, 30-31. Bailey, A., Podlager, M., Zarske, J. S., & Carlson, D. W. (2007). Lesson: the science of swinging. Teach engineering: curriculum for K-12 teachers. Retrieved from https://www.teachengineering. org/view_lesson.php ?url=collection/cub_/lessons/cub_pend/cub_pend_lesson0 l .xml Barnawi, W. , Dyke, S., Truman, K., Taylor, E ., & Johnson, L. (2007). Earthquake engineering modules for K-12 education. Retrieved from https://nees.org/resources/928/download/ Earthquake_engineering_modules_for_k- l 2_education. pdf Confrey, J., & Krupa, E. E. (2012). The common core state standards for mathematics: How did we get here, and what needs to happen next? In C. Hirsh, G . Lappon, & B. Rey (Eds). Curriculum issues in an era of common core state standards for mathematics (pp. 3-16). Reston, VA: The National Council of Teachers of Mathematics. Cooper, L., Zarske, M . S., & Carlson, D. W., (2008). Hands-on activity: design step 3: brainstorm possible solutions. Teach Engineering: Curriculumfor K-12 Teachers. Retrieved from https:// www.teachengineering.org/view_activity. php ?url=col lection/cub_/activities/cub_ creative/cub_ creative_activity3.xml Cornell University. (2015). Brainstorming. Cornell Engineering. Retrieved from https://www. engineering.cornell.edu/academics/undergraduate/special_programs/student_teams/resources/ research/brainstorming.cfm Lloyd, J. (2011, June 23). NEES Teaching demonstration: earthquake-proof K ' nex buildings. NEEShub. Retrieved from https://nees.org/resources/2933 Morphew, V. N. (2011). A constructivist approach to the national educational technology standards for teachers. Washington, DC: International Society for Technology in Education. Moyer, R.H., & Everett, S. A. (2012). Life preservers-increase your v to lower your D. In Horak, J., Cooke, A., Rubin, W. , & Hannigan, A. (Eds.), Everyday engineering (pp. 95-102). Arlington, VA: NSTA Press. National Academy of Engineering. (2008). 14 grand challenges for engineering. Retrieved from http://www.engineeringchallenges.org/cms/challenges.aspx National Academy of Engineering. (2015). Greatest engineering achievements of the 20th century. Retrieved from http://greatachievements.org/ National Governors Association Center for Best Practices, Council of Chief State School Officers. (2010). Common core state standards for English language & literacy in history/social studies, science, and technical subjects. Retrieved from http://www.corestandards.org/wp-content/ uploads/ELA_Standards.pdf National Governors Association Center for Best Practices, Council of Chief State School Officers. (20 10). Common core state standards for mathematics. Retrieved from http://www.corestandards. org/wp-content/uploads/Math_Standards.pdf NGSS Lead States. (2013). Volume 1: The standards. Next generation science standards: For states, by states. Washington, DC: The National Academies Press.

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NGSS Lead States. (2013). Volume 2: The appendixes. Next generation science standards: For states, by states. Washington, DC: The National Academies Press. Science Buddies. (2002-2015). Brainstorm multiple solutions. Retrieved from http:// www.sciencebuddies.org/engineering-design-process/alternative-solutions. shtml#howtocreatemultiplesolutions Todd, J., Straten, M., Zarske, M. S., & Yowell, J. (2004). Hands-on activity: earthquake in the classroom. Teach Engineering: Curriculum for K-12 teachers. Retrieved from https://www. teachengineering. org/view_ activity.php ?url=collection/cub_/activities/cub_natdis/cub_natdis_ lesson03 _activity l .xml United States Coast Guard. (2014). PFD selection, use, wear, & care. Retrieved from http://www. uscg.mil/hq/cg5/cg5214/pfdselection.asp Watson, D. (2010). Wind turbines and the energy in wind. FT exploring science and technology. Retrieved from http://www.ftexploring.com/energy/wind-enrgy.html

APPENDIX

A Correlations With Nationwide Learning S1:anclards

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8. Obtaining, evaluating, and communicating information

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APPENDIX

B Using Safe Procedures

Although every proposed experiment has a unique risk assessment, you will find that generalizations can be made across categories of experimental materials. Typical categories include: ►

Chemicals;



Electricity, radiation, and projectiles;



Mold, bacteria, and other microbes;



Invertebrates, non-human vertebrates, and human subjects;



Environmental field studies.

Below are general safety precautions for these categories of experimental materials. For detailed safety information see Volume 2, Chapter 10, Analyzing and Addressing Safety Risks, or the safety references provided in this appendix.

CHEMICALS Cleaners, fertilizers, and other chemicals serve many useful purposes, but all of them can be dangerous if improperly used. Never mix chemicals, not even household cleaners, without advice from an adult. In addition, you should: ►

Always wear indirectly vented chemical splash goggles. Depending on the chemical you may need gloves, an apron, or a face mask.



Wash your hands after handling any chemical.



Know the potential dangers of the chemical you are using. Some chemicals can irritate your skin, while others are poisonous. Do not breathe vapors from chemicals. Be sure the area in which you are working is well ventilated. For some chemicals a fume hood is required.

261

262

Appendix B Using Safe Procedures



Know how and where to store chemicals safely. A special kind of container might be needed, or maybe the chemical should be stored in a glass container, rather than a plastic container.



Never work alone, know what to do in case of an accident, and have safety equipment accessible.



Know the procedure for safely disposing of your chemicals.



Use Safety Data Sheets (also known as Material Safety Data Sheets) to find answers to safety questions.

ELECTRICITY, RADIATION, AND PROJECTILES Experiments that use electricity should always be supervised by an adult who knows how to work safely with electricity and to take proper precautions to prevent an accident. When conducting experiments involving electricity, you should: ►

Use as little voltage as possible.



Avoid using current from household outlets; use batteries instead.



Watch for leaky batteries. The chemicals inside can be harmful.



Make sure electrical appliances and tools are insulated and grounded; use UL/CAS-approved devices.



Never work alone and know what to do in case of an accident.

Experiments involving microwave ovens, lasers, radon, and some types of smoke detectors can be very dangerous. Even in small amounts radiation can be harmful to living tissues. Appropriate safety equipment must be worn when conducting an experiment involving projectiles. Potentially hazardous projectiles include flying rubber bands, model rockets, and potato and paint ball guns. For detailed information consult the references.

MOLD, BACTERIA, AND OTHER MICROBES Because mold spores are all around, you have probably seen mold growing on bread and other foods. Bacteria and other microbes also abound in the environment; these include viruses, viroids, prions, rickettsia, and other parasites. Although many common microbes are harmless, others are harmful. For this reason, research involving microorganisms must always involve caution. ►

Keep the mold and microorganism containers sealed, e.g., tape them shut.



Do not touch the microorganisms.



Wash your hands frequently.



Never smell by inhaling close to the containers.



Do not re-use containers.

Appendix B Using Safe Procedures

263



Dispose of your organisms and sealed containers properly.



Wear appropriate safety equipment such as goggles, disposable gloves, disposable facemasks, and aprons.

INVERTEBRATES, NON-HUMAN VERTEBRATES, AND HUMAN SUBJECTS Protists, insects, and worms are examples of invertebrates. If you do a project with any animalinvertebrate or vertebrate- you must provide proper care for the animal. Some elements of proper care include: ►

Respect for life;



Comfortable living place which is suitable for the species;



Procedures which do not injure the organisms;



Enough food, water, warmth, and rest;



Continuous care including weekends and vacation periods;



Gentle handing;



A proper home for the organisms when the experiment is finished.

By experimenting with non-human vertebrate animals, scientists can increase their understanding of living processes and biological principles. Vertebrates include fish, amphibians, reptiles, birds, and mammals. Experimentation involving human subjects must make valid contributions to psychology and human welfare. Scientists who wish to do experiments on non-human vertebrates and human subjects must have their research plans approved by a committee of fellow scientists. These rules are to help insure proper treatment. For detailed information, consult the references.

ENVIRONMENTAL FIELD STUDIES Many valuable investigations can be conducted in the natural environment including studies of various aquatic and terrestrial ecosystems and the behavior of organisms. Special safety precautions and rules must be followed when working in an outside laboratory. Some important items to keep in mind during field studies include: ►

Wear appropriate clothing and shoes for working in the outside environment including the use of life jackets when near water.



Know how to identify and avoid animals that can cause harm such as ticks, mites, and poisonous and venomous snakes and insects.



Know how to identify and avoid poisonous plants and those that may cause allergic reactions.



Know how to identify threatened and endangered species and the rules governing them.

264 Appendix B Using Safe Procedures ►

Know human dangers caused by seasonal hunting, spraying with herbicides and pesticides, or traffic.



Use non-breakable containers for testing chemicals and collecting samples.



Wear appropriate goggles such as indirectly vented chemical splash goggles when using chemicals and impact goggles when using chipping hammers or tools.



Follow safety guidelines for chemicals when using water, soil, or other test kits.



Know the legal requirements for collecting organisms and follow them.



Do not collect organisms, even though legal, unless there is a valid reason and you can care for the animals as described previously.



Secure permission to work in an area, such as from a park official or the property owner.



Know what to do in case of an accident, carry a first aid kit, and take a method of communication.



Never work alone and make others aware of your location and estimated return time. (Adapted from Maryland State Department of Education, 1999-2014).

REFERENCES At the time of publication, the links for the references were accurate. If they have changed, try searching by the author(s) or name of the publication. Interactive Leaming Paradigm, Inc. (2014, July). MSDS online-where to find material safety data sheets on the internet. Retrieved from http://www.ilpi.com/msds/ Maryland State Department of Education (1991-20 14). Outdoor safety-field studies. Science safety manual. Retrieved from http://mdkl2.org/instruction/curriculum/science/safety/outdoor.html MSDSonline. (1996-2015). Where to find material safety data sheets on the internet. Retrieved from http://www.ilpi.com/msds/ National Association of Biology Teachers (2014). Free teaching resources-resource links by topic. Retrieved from https://www.nabt.org/websites/institution/index.php?p=l 16 National Science Teachers Association. (2014). Books and resources-safety in the science classroom. Retrieved from http://www.nsta.org/safety/ Society for the Science and Public (2015). Intel International Science and Engineering Fairinternational rules and guidelines 2015. Retrieved from https://member.societyforscience.org/ document.doc?id=396 University of Wisconsin. (2004). Laboratory safety guide. Chemical and Radiation Protection Office, Safety Department. Wisconsin, Madison: Author. Retrieved from http://www.ehs.wisc.edu/ laboratorysafetyguide.htm U.S. Department of Health and Human Services. (2015, May). Agency for toxic substances and disease registry. Retrieved from http://www.atsdr.cdc.gov/ U.S. Department of Health and Human Services. (2015, May). Hazardous substances data bank (HSDB ). Retrieved from https://catalog.data.gov/dataset/hazardous-substances-data-bank-hsdb U.S. Department of Health and Human Services. (2014, August). Household products database. Retrieved from http://householdproducts.nlm.nih.gov/

APPENDIX

C Definitions of Key Terms

Argumentation-constructing and supporting a position with evidence. Brainstorming-a process for generating many ideas. Categorical data-data that is sorted into different groups that do not overlap, such as brands of products and kinds of papers. When displayed with a bar graph, the space between the bars is intended to show there is no overlap between the groups. The levels of the independent variable may be classified as categorical. Clustered bar graph-a graphical display where vertical bars are used to display the frequency of various categorical data for each level of the independent variable. Impact of Water on Paper Worm Shape

...

•1 Column bar graph-a graphical display where vertical bars are used to indicate the value of the dependent variable for each level of the independent variable tested. Impact of Side of l eaf on Diameter of Water Drops

Top

Side of Oak l eaf

Bottom

265

266 Appendix C Definitions of Key Terms

Conclusion-a verbal synopsis in which the validity of an experimental hypothesis, engineering design, or mathematical conjecture is augured. The conclusion generally includes the hypothesis or conjecture, major findings, a critique, and recommendations for future investigations or designs. Constants-those factors in an experiment that are kept the same and not allowed to change or vary; also used as a synonym for "controlled variables," which is the preferred term. Continuous quantitative data-may be any numerical value. This type of data can be obtained by measuring using a standard scale. The intervals between the units can be continuously subdivided into smaller and smaller units like tenths, hundredths, thousandths, etc. Controlled variables-those factors in an experiment that are kept the same and not allowed to change or vary. Although used as a synonym for constants, "controlled variables" is the preferred term. Control group-the part of an experiment that serves as a standard of comparison. A control group is used to detect the effects of factors that should be kept constant, but which are varied unintentionally. The control group may be a "no treatment control group" or an "experimenter selected control group." Counts-the number of items or the number of times something occurs, for example, the number of bees attracted to sugar water or the number of times a forest fire occurred in an area. Data- information (measurements, observations, or counts) gathered in an experiment; data takes a plural verb, "the data are; the data were." Data table with raw data-a chart to organize, display, and summarize the data collected in an experiment. The general format for a data table containing raw data is shown below.

Title: Communicate the independent and dependent variables displayed. Column A Independent Variable (units)

Column B Raw Data for Dependent Variable (units) Subdivide for number of repeated trials

1

2

3

4

Etc.

Column C Central Tendency (units)

Column D Variability (units)

Level 1 Level 2 Level 3 (control group) Etc.

Key: If qualitative data are collected, define the categories here.

Dependent variable- the factor or variable that may change as a result of changes purposely made in the independent variable. Descriptive statistics-summary statistics that describe the most typical values and the variations within a set of data.

Appendix C

Definitions of Key Terms

267

Derived quantities-values calculated from raw data such as the measures of central tendency and descriptions of variability. Directional research hypothesis-a hypothesis stating how a directional change in the independent variable will impact a directional change in the dependent variable using words such as increase, decrease, less than, more than, slower, faster, and stays the same. Design brief-a document used by engineers which describes the problem and the solution required. Discrete quantitative data-data collected by counting; these counts are not continuous data because it does not make sense to count "part" of something. For example, 1.5 bees were attracted to the sugar water would not make sense. Engineering design process-Major strategies used by engineers when designing, building, and testing a model. General strategies include a) identify the problem, b) determine criteria and constraints, c) brainstorm a solution, d) plan and select a design, e) build a model, f) test, evaluate, and redesign, and g) share the results. Evidence-the data and observations used to determine support or nonsupport for a hypothesis, conjecture, or engineering design. Experiment-a test of a hypothesis. It determines if purposely changing the independent variable does indeed change the dependent variable as predicted. Experimental Design Diagram-a graphic illustration of an experiment containing the components illustrated below. Title:

title

Hypothesis:

hypothesis

JV:

independent variable levels of independent variable number of repeated trials

DV:

dependent variable

CV:

controlled variables

268 Appendix C Definitions of Key Terms

Experimental report-an overview of the experiment used to report findings; major components include the experimental design, procedures, results, and conclusion. Explanation-An interpretation of the data using information from related experiments, major scientific concepts, and discussions with scientists. Explanatory model-a model that can be tested, used to determine if the model's inferences are supported by data, and refined through additional experimentation. Experimenter selected control group-the set of trials conducted for the level of the independent variable which is used as the standard of comparison. If an experiment involves determining the best brand of gasoline, a "no treatment control group" does not make sense. In this case, the experimenter can select a specific gasoline, such as the best-selling brand, as the comparison group. Four question strategy- an approach for generating experimental ideas from a familiar topic or science activities, demonstrations, experiments, and readings. Brainstorming responses to the four questions in the strategy results in many potential independent, dependent, and controlled variables to select among. It also results in descriptions of ways to describe or measure the dependent variable. Version of this strategy exists for generating ideas for engineering projects and mathematical investigations. Frequency distribution-the number of times each value occurs in a set of data, for example 2 red, 10 pink, and 25 green tomatoes; it communicates the variability within a set of data. Horizontal (X) axis-typically displays the independent variable; one exception is an experiment with repeated measures over time when the time intervals are placed on the X axis. Hypothesis-a prediction of the relationship of an independent and dependent variable to be tested in an experiment; it predicts the effect that the changes purposely made in the independent variable will have on the dependent variable. "If ... , then ..." hypothesis statement-a structured method for writing a hypothesis statement that serves as a prediction. The general form is: If the (independent variable) is (describe how you change it), then the (dependent variable) will (describe the effect). An example of a statement is: If the amount of salt is increased, then an egg's floating height will increase. "If ... , then ... because ..." hypothesis statement-a structured method for writing a hypothesis that goes beyond a prediction and explains (infers) the basis for the prediction. The general form is If the (independent variable) is (describe how you change it), then the (dependent variable) will (describe the effect) because (state the reason). An example of a statement is: If the salinity of the solution is increased, then the egg's floating height will increase because of the greater buoyant force of the salt solution. This type of hypothesis serves as an explanation model.

Independent variable-the variable that is changed on purpose by the experimenter. Intervals-the equal spaces marked along the axis of a graph, or the spaces between units of a measuring device. Levels of the independent variable-the specific values (kinds, sizes, or amounts) of the independent variable that are tested in an experiment.

Appendix C Definitions of Key Terms

269

Line graph-a graphical display in which the data points are connected by lines; it is used to visualize changes between two data points, as well as overall patterns such as changes over time. Maple Trees in Town over Sixty Years Ill

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I Decade Linear model-used to represent a relationship between the independent and dependent variable that is communicated by a straight line added to a scatter plot. The line is drawn so the points above and below the line are equal, e.g. roughly half of the data points are above and half are below. Material Safety Data Sheet (MSDS)-for chemicals, a fact sheet which provides information about toxicity, reactivity, flammability, corrosiveness, and appropriate disposal of a chemical; this is an older term for Safety Data Sheet (SDS). Mathematical conjecture-statement about possible relationships that seem true from observation but have not yet been proven through the use of theoretical mathematics. Mean-a typical value in a set of quantitative data; the formula for calculating the average (mean) IS:

sum of all measurements (or counts) Average (Mean) = - - - - - - - - - - - - - - ~ total number of measurements (or counts)

Measurements-data collected using a measuring instrument with a standard scale and defined zero such as the instruments used in the metric and english systems; scientists use the metric system because it is used world-wide. Measures of central tendency-value used to describe a typical value in a set of data, e.g. mean, median, mode. Median-the middle data value after all the data has been ordered from lowest to highest; half of the data values are above the median and half are below it. Methods and materials-a paragraph which describes the sequence for conducting an investigation including the materials and equipment used and the safe precautions followed. Mode-the value which occurs most often in a set of data. Negative association-increasing the independent variable values results in a decrease in the dependent variable values, or vice versa. Nominal data-data that consists of categories having no inherent order.

270 Appendix C Definitions of Key Terms

Non-directional research hypothesis-a hypothesis stating that a change in the independent variable will impact the dependent variable without using quantitative terms, such as increase, decrease, stays the same. Non-linear model-a relationship between the independent and dependent variables that is communicated by various types of curves on a scatter plot. 24

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No treatment control group-a group that receives none of the independent variable, for example in an experiment testing the effect of varying the amount of a fertilizer on plant growth, a no treatment control group would be the set of plants that receives no fertilizer. Numerical data-data which are collected by counting or measuring using the English or metric scale. Observations-data that are descriptions of qualities such as shape, color, and gender. Operational definition-a statement containing specifics about how a variable will be measured, counted, or described. Ordinal data-data that can be placed into ordered categories Positive association-increasing the independent variable values results in an increase in the dependent variable values, or vice-versa. Procedure-a sequence of precisely stated steps that describes how an investigation is done. It includes the materials, equipment, and safety precautions. Qualitative data-observation of qualities of an object such as color of leaves, cloudiness of a solution, or activity of an organism; also called categorical data. Quantitative data-also called numerical data; counting or measuring objects with a standard scale, such as the tools used in the English or Metric system. Continuous quantitative data is collected by measuring objects with a standard scale. Discrete quantitative data is collected by counting objects; these counts are not continuous because it does not make sense to have "part of an object. Range-the difference between the smallest and largest value in a data set; it communicates the variability or spread within the data.

Appendix C Definitions of Key Terms

271

Raw Data-the individual measurements, observations, or counts gathered in an experiment; these data are generally not included in a formal paper, but are summarized using statistics. However, the experimenter may include these raw data in an appendix. Repeated trials-the number of times that a level of the independent variable is tested in an experiment or the number of organisms tested at each level of the independent variable. Results-presentation and analysis of the data which often includes a data table, graph, and verbal summary.

Safety Data Sheet (SDS)-for chemicals, a fact sheet which provides information about toxicity, reactivity, flammability, corrosiveness, and appropriate disposal of a chemical. This is a new term which has replaced Material Safety Data Sheet (MSDS). Scatter plot-a graphical display of two quantitative variables in which each data point represents a single pair of data. These plots are used to detect patterns or trends in the data. The Effect of Salad Oil Temperature on the Time for a Water Drop to Fall through It 160

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272

Appendix C Definitions of Key Terms

Summary data table-a chart to organize and display the measures of central tendency, variability, number of trials, and other statistics for a set of data. The general format for a summary data table is shown below. Title: Communicate the independent and dependent variables displayed. Column B Name of Independent Variable (u nits) Subdivide for levels of independent variable

Column A Name of Dependent Variable

Name of Level 1

Name of Level2

Name of Level3

Etc.

Name of Measure of Central Tendency

cell

cell

cell

cell

Name of Variability

cell

cell

cell

cell

Number of Trials

cell

cell

cell

cell

Key: If applicable for qualitative data.

Testable question-a question which can be used to design an experiment and collect data to provide a real answer to the question. Title-a statement describing an experiment, a data table, or a graphical display. Titles are often written in the form, "The Effect of Changes in the Independent Variable on the Dependent Variable." Trend-represents the relationship between the independent and dependent variables, and can be linear or non-linear.

Types of data-the kinds of information collected in an experiment; typical types are qualitative (nominal and ordinal) and quantitative (continuous and discrete). Value-the size, amount, or extent of a property described by a piece of data, observation, or count. Variability-the dispersion or spread within the values of a data set. Variables-things or factors that can be assigned or take on different values in an experiment; examples include the independent variable, dependent variable, and the controlled variable. Vertical (Y) axis-typically displays the dependent variable.

Index

A

C

acid rain, 80 algebra, 24 analysis of experimental data, viii of experimental design, 60-65 applications of science, 256 appropriate experiment, 72 argumentation, 18-19, 240 defined,265 assessment, viii checklist, viii, 15, 50 comparing more than one, 18 comparison, 71 of experiment, 15-19 hypothesis, 71 practice, 21-22 question, 71 of refined experiment, 47-50 rubric, viii assessment comparisons, 110- 111, 249 axis,graph, 160, 161, 162, 163, 181

categorical data, 39, 265 central tendency, 127 checklist assessment, 22 for conducting experiment, 15, 16 for conducting refined experiment, 47, 48 data table with raw data, 138 design brief, 248 for experimental design, 76 experimental design diagram, 69, 70 experimental report, 217-218 graphical displays, 181 procedure, 107, 108 summary data table, 145 clustered bar graph, 162, 163 defined,265 collaborative tools, 23 collections, 23 column bar graph, 161, 162, 167 defined,265 Common Core State Standards for Literacy in Science and Technical Subjects, 5, 33, 61, 9 1, 123, 159, 195, 231 Common Core State Standards for Mathematics, vl 5, 33,61, 9 1, 123, 159, 195,23 1, 257258 communication, 91, 123, 159, 195,213,231 complexity, in assessment, 7 1 computer models, 23 computer simulations, 23

B bar graph clustered bar, 162, 163 column bar, 161, 162 practice, 165- 166 stacked bar, 163- 164 brainstorming, 237, 239- 240, 243 defined,265

273

274

Index

conclusion, 208,209, 211-212 defined,266 key elements in, 209 practice, 211-212 strategies for writing, 208 constants, 9 defined,266 continuous quantitative data, 126 defined,266 controlgroup,37,40 in assessment, 71 defined, 266 in experimental design, 62 practice, 40, 41-42 types of, 37 controlled variable, 9, 16 in assessment, 22, 71 in comparing assessments, 18 defined,266 in experimental design, 62 in experiment refining, 37 refined experiment, 48 core ideas, and experiments, 5 core procedure, 110 counts, 38 defined, 266 creativity, 5, 33, 61, 71, 91, 123, 159, 195, 231 critical thinking, 5, 33, 61, 91, 123, 159, 195,23 1 cross-cutting concepts, 5, 33, 61, 91, 123, 159, 195,231 ,256 cross-disciplinary applications, vi

D Daphnia, 17, 18 data, 23, 32, 38 defined,266 data analysis, 110, 199-203 data collection, 23, 32 data interpretation, 199-203 data pairs, 181 data points, 168 data table, 122 assessment, 140 Common Core State Standards for Literacy in Science and Technical Subjects, 123 Common Core State Standards for Mathematics, 123 constructing with raw data, 133 format for raw data, 124, 125 ISTE Standards for Students, 123

and national standards, 122, 123 Next Generation Science Standards, 123 STEM connections, 149, 151-154 data table with raw data, 133 defined, 266 data types, 38-40, 129, 272 decision making, 5, 33, 61, 91, 123, 195,231 dependentvariable,9, 140, 141, 142, 160 in assessment, 22, 71 defined,266 in experimental design, 62 in raw data table, 138 refined experiment, 48 derived quantities, 125, 145 defined,267 descriptive statistics, 125, 131-132, 145 defined, 266 design brief, 233, 235-236 assessing and improving, 24 7 checklist, 248 defined,267 writing, 251 design, build, and test, engineering model, 233 design focus, 244 digital citizenship, 5, 33, 61, 91, 123, 159, 195, 231 digital technology, vi digital tools, 23 directional hypothesis, 11 directional research hypothesis, 11, 267 disciplinary core ideas, 5, 33, 61, 91, 123, 159, 195,23 1,256 disciplines, vi discrete quantitative data, 126 defined,267

E Earth, 25 Earth and Space Sciences, 256 electronic sensor, 23 energy, 25 engineering, vi, 152, 256 practices, vii and STEM connections, 23, 54, 84, 114, 188, 222 engineering design, viii, 230-233, 235-251 and national standards, 230, 231 process, 232-233 engineering design brief, 233 engineering design process, 237-239

Index

brainstorming, 237 defined, 267 design selection, 238 model construction, 238 problem identification, 237 results sharing, 239 testing, evaluation and redesign, 239 engineering design rubric, 243 engineering practices, 123 English measurement system, 38 equipment, in procedures, 102 evidence, 44 defined,267 q ualitati ve, 201-203 quantitative, 199-200 evidence vs. explanation, 27, 44 experiment. see also experiment, refining assessment, 15- 19 checklist, 15, 16 component identification in, 9 conducting, 6 controlled variable, 16 defined, 4,267 dependent variable, 16 An Experiment to Cry Over, 109 An Experiment to Cry Over experiment, 111 Fresh Water Pearls, 197-198 Huff, Puff, and Slide, 67-68 hypothesis, 16 hypothesis construction in, 10-11 hypothesis support in, 11 independent variable, 16 making sense of, 194 and national standards, 4, 5 objectives for conducting, 4 operationally defined, 17 Paper Worms, 135-136 Pearly Environments, 215- 216 question, 16 Rapid Swingers, 7- 8 refining, 32-56 Stretching to the Max, 179- 180 Sudsational Experience, 110 Sudsational Experience experiment, 95-96 testable questions in, 10 variables, 9 experimental conclusion, 207-209 topic research, 207- 208 writing conclusion, 208, 209, 211-212 experimental data collection, 194, 196 experimental data graph, 177

275

experimental data interpretation, viii experimental design, 60-86 diagram construction, 62, 63. see also experimental design diagram and national standards, 60, 61 experimental design diagram, 62-81, 217 assessment, 69-72, 69-76 Common Core State Standards for Literacy in Science and Technical Subjects, 61 Common Core State Standards for Mathematics, 61 constructing, 62 defined,267 format for, 62 ISTE Standards for Students, 61 Next Generation Science Standards, 61 with one independent variable, 62 practice, 62-63 with two independent variables, 80, 81 experimental evidence interpretation, 199-203 experimental procedure, 93, 95-100 adding details to, 97-98 precision in, 99-100 experimental report, 216, 217-218 defined,268 experimental report checklist, 217-218 experimental results, practice, 205-206 experimentation, viii experimenter selected control group, 37, 41 defined,268 experiment, refining, 32-56 assessment of, 47- 50 Common Core State Standards for Literacy in Science and Technical Subjects, 33 Common Core State Standards for Mathematics, 33 conducting, 34, 35-36 control group in, 37 Floating Eggs, 35-36 ISTE Standards for Students, 33 and national standards, 32, 33 Next Generation Science Standards, 33 qualitative data, 39-40 quantitative data, 38, 39 repeated trial, 38 An Experiment to Cry Over experiment, 109, 111 explanation, 44 defined,268 explanatory model, 43, 268 external stimuli, 79 extrapolate, 172-173

276

Index

F field study, 23 Floating Eggs experiment, 35-36 observational scale for, 39 and STEM connections, 53-56 force, 25 format, 111 four questions strategy, 268 frequency distribution, 128 defined,268 Fresh Water Pearls experiment, 197-198

G geometry, 24 graph, 158-190 axis, 160 Common Core State Standards for Literacy in Science and Technical Subjects, 159 Common Core State Standards for Mathematics, 159 defined, 158 dependent variable, 160 independent variable, 160 ISTE Standards for Students, 159 linear model, 169 mathematical model, 171 multiple independent variables, 183-185 and national standards, 158, 159 Next Generation Science Standards, 159 non-linear model, 170 qualitative independent variables, 161-166 scatter plots, 168-173 selection, 160 graphical display, two independent variables, 185 graphical displays checklist, 181

H hidden variables, 37 horizontal (X) axis, 160, 162, 268 Huff, Puff, and Slide experiment, 67-68 hypothesis in assessment, 22, 71 changing to explanatory model, 43 in comparing assessments, 18 constructing, 10- 11 defined, 268 directional, 11 in experimental design, 62

general format, 10 "if' and "then" sentence structure in, 10 and input and output variables, 11 non-directional, 11 practice, 13-14 refined experiment, 48 revised, 10 hypothesis support, 11

"if' and "then" hypothesis statement, 10, 43, 44, 268 independent variable, 9, 140, 141, 142, 145, 160 in assessment, 22, 71 in comparing assessments, 18 defined, 268 in designing experiments, 77-80 in experimental design, 62 levels of, 9, 62, 268 in raw data table, 138 refined experiment, 48 independent variable levels, 9, 62, 268 innovation, 5, 33, 61, 91,231 input variable, 11 interpolate, 172 interpretation, data, 199-203 intervals, 268 investigation, 4 ISTE Standards for Students, 5, 33, 61, 91 , 159, 195,231,259

K key terms, 265-272

L levels of independent variables, 268 Life Savers engineering activity, 241-242 Life Sciences, 256 linear model, 169 defined,269 line graph, 167 defined,269

M Material Safety Data Sheet (MSDS), 269 materials list, in procedures, 103 mathematical conjecture, 269

Index mathematical domains, 5, 33, 6 1, 91, 123, 159, 195 mathematical model graph, 170-171 examples of, 171 mathematical patterns, 27 mathematical practices, vii, 5, 33, 61 , 91, 123, 159, 195,231 mathematics, vi and data tables, 153- 154 and STEM connections, 23, 54-56, 85-86, 114-116, 188-190, 223-224 mean, 127, 269 measurement, defined, 269 measurement concepts, 24 measure of central tendency, 127, I 29, 140, 141 , 142 defined,269 in raw data table, 138 median, 127 defined,269 media tools, 23 methods and materials, 269 metric system, 38, 126 mode, 39, 127 defined, 269 and frequency distribution, 127 Moh's Hardness Scale for Minerals, 126 multiple independent variables, 183-185

N Nationwide learning standards correlations, 256-259 natural phenomena, 23 natural world, 25 negative association, 170 defined,269 Next Generation Science Standards, vi, 5, 33, 61, 91 , 123, 159,195,231,256 and argumentation, 18-19 and controlled variables, 9 nominal data, 126, 129 defined,269 non-directional hypothesis, 11 non-directional research hypothesis, 11 defined, 270 non-linear model, 170 defined,270 no treatment control group, 37, 4 1 defined,270

277

number sense, 24 numerical data, 270

0 observation, 4, 6, 23, 39 defined, 270 operational definition, 16, 17 defined, 270 operationally defined, 16, 17 ordinal data, 126, 129 defined, 270 ordinal data scales, 126 output variable, 11

p Paper Worms experiment, 135-136 Pearly Environments experiment, 215-216 peer assessment, viii percentage, 55 phenomena, 23 positive association, 170 defined,270 practice assessing experimental design dia~ram 72 73-75 b ' ' assessing experiments, 2 1-22 assessing refined experiment, 49 bar graphs, 165- 166 conclusion, 211 - 212 control group and repeated trials, 40, 41-42 data table assessment, 139 descriptive statistics, 131-132 design brief, 251 experimental design diagram, 63-64 experimental designs and procedures, 103, 105- 106 experimental results, 205-206 explanatory hypotheses, evidence, and explanation, 44, 45-46 precise procedure, 99- 100 refined experiment assessment, 49 scatter plots, 175-176 summary data table, 147- 148 variables, questions and hypotheses, 13-14 practices, STEM, vi, vii foundations for, viii precision, in experimentation, 90. see also procedure

278

Index

prediction, 11 problem solving, 5, 33, 61, 79, 91, 123, 159, 195,231 procedure assessment, 107-111 core, 110 data analysis, 110 defined,90,270 from design diagram to, 101-103 experimental, 93, 217 format, 111 and national standards, 90, 91 repetitions, 110 safety, 110 for tasks, 92-93 progress assessment, viii

Q qualitative data, 39-40, 126, 129 defined,270 qualitative evidence, 201-203 qualitative independent variables graph, 161-167 quantitative data, 38, 39, 126, 129 defined,270 quantitative evidence, 199-200 quantitative independent variables graph, 167-173 column bar graph, 167 line graph, 167 scatter plots, 168-170 question, 10, 11 in assessment, 22, 71 in comparing assessments, 18 experiment, 16 practice, 13- 14 refined experiment, 48

R range, 128 defined,270 Rapid Swingers experiment, 7-8 and core components, 15 and engineering, 26-27 and mathematics, 27-28 revised hypothesis for, 11 and science, 25-26 and STEM connections, 23-24, 25-28 and technology, 26-27

raw data, 38, 39, 124 assessment, 137 defined, 271 types of, 126 reading, 5, 33, 61 , 91, 123, 159, 195,23 1 repeated measures over time, 77, 183 repeated treatment designs, 78 repeated treatments over subjects, 78 repeated trial, 38-40 in assessment, 71 defined,271 in experimental design, 62 refined experiment, 48 repetitions, 110 research, 195, 231 and experimental design, 61 and experiment refining, 33 and experiments, 5 and graphs, 159 and procedure, 91 topic, 207-208 respiration, 80 results, 199-203 defined, 271 rubric, 242 engineering design, 243

s safe procedures, 261-264 chemicals, 261-262 electricity, radiation, and projectiles, 262 environmental field studies, 263-264 invertebrates, non-human invertebrates, and human subjects, 263 mold, bacteria and other microbes, 262-263 safety, 110 Safety Data Sheet (SOS), 271 scatter plots, 28, 168- 173 data points in, 168 defined,27 1 practice, 17 5- 176 and prediction, 172- 173 science, vi, 151 and STEM connections, 23, 53, 83, 113, 187, 221 scientific experimentation vs. engineering design and build, 233

Index scientific practices, vii, 5, 33, 61 , 91 , 123, 159, 195,231,256 Scoville Heat Units of Peppers, 126 self-assessment, viii Shake It Up engineering activity, 235- 236 simulations, 23 skewed data, 129 software, 23 spreadsheets, 23 stacked bar graph, 163-164 defined, 271 standard scale, 271 defined, 38 standards, STEM Common Core State Standards for English Language and Literacy in History/Social Studies, Science, and Technical Subjects, v Common Core State Standards for Mathematics, v, vi International Standards for Technology in Education Standards for Students, v Next Generation Science Standards, v, vi statistics, 24, 122 appropriate, 129 STEM connections, 23-24 engineering, 23 mathematics, 24 science, 23 technology, 23 STEM disciplines, 83-86 connections in, 23-24, 51 , 81, 111, 113-116, 185, 187-190,221- 224 goals of, vi STEM practices, vi, vii Stretching to the Max experiment, 179- 180 Sudsational Experience experiment, 95- 96, 110 summary data table, 122 cells, 143 checklist, 145 constructing, 142- 144 defined,272 examples of, 142- 143 format, 142-143 key, 143

279

practice, 147- 148 qualitative data, 144 quantitative data, 143 title, 143 support, hypothesis, 11

T tables, 122. see also data table technology, vi, 5, 33, 61, 123, 152, 159, 195,231 , 256 and STEM connections, 23, 54, 84, 114, 188, 222 "Temperature and Bean Plants" scenario, 45 testable question, 10, 11, 62 defined, 272 title data table, 138, 140, 141, 142, 143, 145 defined,272 graph, 161,162,163,164 graphical display, 181 topic research, 207-208 trend, 272 types of data, 272

V value, 272 variability, 128, 129, 140, 141, 142 defined, 272 in raw data table, 138 variable, 9 controlled,9 defined, 272 dependent, 9 independent, 9 practice, 13- 14 vertical (Y) axis, 160, 162, 272

w Wind Power engineering activity, 245-246 word processing software, 23 A Working Heart activity, 17 writing,5, 33, 61, 91, 123, 159, 195,231