Beyond Digital Distraction: Educating Today's Cyber Student (Digital Education and Learning) [1st ed. 2024] 3031532147, 9783031532146

Table of contents :
Acknowledgements
Praise for Beyond Digital Distraction
Contents
About the Author
List of Figures
Chapter 1: The Why…
Background and Argument
Theoretical Underpinnings
Engagement Theory
Cognitivism
My Positionality
My Motivation for Writing This Book
Driving Questions
The Method Matters
Sample, Data Collection, and Analysis
Follow the Yellow Brick Road
References
Chapter 2: How Do Students and Teachers Define Digital Distraction in School?
References
Chapter 3: How Do Students and Teachers See Digital Distraction in School?
References
Chapter 4: What Do Students and Teachers Believe Contributes to Digital Distraction in School?
References
Chapter 5: How Do Students and Teachers Respond to Digital Distraction in School?
References
Chapter 6: What Types of Experiences Do Students and Teachers Have with Digital Distraction in School?
References
Chapter 7: Implications for Theory and Research
References
Chapter 8: Key Takeaways and Conclusions
References
Terms to Know
References
Index

Citation preview

Beyond Digital Distraction Educating Today’s Cyber Student Kurt C. Schuett

Digital Education and Learning Series Editors

Michael Thomas Liverpool John Moores University Merseyside, UK Mark Warschauer University of California Irvine, USA

Much has been written during the first decade of the new millennium about the potential of digital technologies to produce a transformation of education. Digital technologies are portrayed as tools that will enhance learner collaboration and motivation and develop new multimodal literacy skills. Accompanying this has been the move from understanding literacy on the cognitive level to an appreciation of the sociocultural forces shaping learner development. Responding to these claims, the Digital Education and Learning Series explores the pedagogical potential and realities of digital technologies in a wide range of disciplinary contexts across the educational spectrum both in and outside of class. Focusing on local and global perspectives, the series responds to the shifting landscape of education, the way digital technologies are being used in different educational and cultural contexts, and examines the differences that lie behind the generalizations of the digital age. Incorporating cutting edge volumes with theoretical perspectives and case studies (single authored and edited collections), the series provides an accessible and valuable resource for academic researchers, teacher trainers, administrators and students interested in interdisciplinary studies of education and new and emerging technologies.

Kurt C. Schuett

Beyond Digital Distraction Educating Today’s Cyber Student

Kurt C. Schuett Concordia University Chicago Chicago, IL, USA

ISSN 2753-0744     ISSN 2753-0752 (electronic) Digital Education and Learning ISBN 978-3-031-53214-6    ISBN 978-3-031-53215-3 (eBook) https://doi.org/10.1007/978-3-031-53215-3 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover credit: Pattern © Melisa Hasan This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

To all the students and educators we lost throughout the COVID-19 pandemic, you are not forgotten.

Acknowledgements

To refer to the team of professionals who assisted in this endeavor as anything less than the Dream Team would be an understatement. Jamie Kowalczyk’s mentorship to me throughout this process was second to none. Pamela Konkol not only served as a continuous support system, but she challenged me to extend my thinking beyond the ordinary throughout this inquiry. Kathryn Wozinak helped me to identify how this research is applicable to improving student learning in the here and now as I prepare to share these findings with educational stakeholders from across the globe. This group of academics personifies best practices in academic research; they model excellence in all things related to twenty-first century teaching and learning. I am forever indebted to my study participants: an unforgettable group of ambitious students and insightful teachers. They are chance takers and stakeholders who believe in the power of learning engagement and academic focus. Their willingness to share uniquely personal insights in a research study conducted amidst a global pandemic was both brave and inspirational. This work will continue to pave the way for necessary change in 1:1 synchronous and asynchronous learning environments, whether that learning is happening “in person” or remotely. To my family and friends, throughout this academic journey, each of you has imparted a kind word or gesture when I needed it most. Your continued patience and enduring support for me never wavered, even when my appointments and deadlines pushed residual stressors in your direction. Thank you for being my sounding board and for never giving up on me. vii

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ACKNOWLEDGEMENTS

And finally to Art and Carrie, you are two of the finest educators I have ever known. Your students and their families are blessed to have had you in their lives, as am I.

Praise for Beyond Digital Distraction “An engaging narrative about learner and teacher perceptions of root causes and responses to digital distraction provides readers not only a set of practical findings that advise current pedagogy, but also encourages future investigation into this phenomenon that is ever-changing on the educational landscape.” —Jack W. Denny, Associate Professor, Teacher Preparation and Doctoral Programs, National Louis University, USA “In an environment that, for the past 25  years, has enthusiastically opened the doors to virtually every new technology, Dr. Schuett’s voice and those of his frustrated students and colleagues are vital contributions to the discussion of what works in today’s classrooms and what is getting in the way.” —David Narter, Adjunct Faculty, Concordia University Chicago and National Council of Teachers of English Contributor and Presenter, USA “Beyond Digital Distraction is a comprehensive and authoritative guide to the manner in which digital distraction plagues the progress of today’s students. It is essential reading for anyone who wants to understand today’s learning obstacles in depth. Kurt Schuett’s exhaustive research and years in the high school classroom make him an expert not only in the philosophical aspect, but in the practical one, as well. This is an essential resource for students, researchers, and practitioners.” —Gena Khodos, Adjunct Faculty, Northern Illinois University and Global Key Talent Design Management and Development Advisor at Abbot, USA “For the better part of three decades, Dr. Schuett has been keeping high school students attentive, curious, and engaged. At a school that adopted 1:1 computing early on, he has observed the progress of digital technologies closely. Educators will benefit greatly from his ideas about how to maintain technology’s potential while avoiding its perils.” —John Rossi, Department Chair of English, Journalism Adviser, and PBS Newshour Student Reporting Labs Consultant, Leyden High School, USA “Dr. Kurt Schuett is one of the most passionate educators I know. He cares deeply about his student-athletes and only wants the best for them. He is always giving and he’s driven to give his students and athletes the best experience possible. With this book, Dr. Schuett wants to help educators better understand today’s students and the times we live in.” —Dion Martorano, Sports Editor and Reporter for Journal & Topics Media Group (Rosemont Journal and Des Plaines Journal), USA

Contents

1 The Why…  1 2 How  Do Students and Teachers Define Digital Distraction in School? 39 3 How  Do Students and Teachers See Digital Distraction in School? 53 4 What  Do Students and Teachers Believe Contributes to Digital Distraction in School? 73 5 How  Do Students and Teachers Respond to Digital Distraction in School? 85 6 W  hat Types of Experiences Do Students and Teachers Have with Digital Distraction in School? 95 7 Implications for Theory and Research109

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8 Key Takeaways and Conclusions119 Terms to Know127 References131 Index133

About the Author

Kurt C. Schuett  is a seasoned educator of 27 years who teaches AP Research and English on the secondary level and undergraduate education courses on the collegiate level. Dr. Schuett is an early pioneer of 1:1 learning, and he has traveled the globe giving professional workshops over Socratic seminar instruction and facilitation for educators (NCCEP 2016 “Gear Up” Annual Conference in Washington, D.C.; SITE 2016 International Conference for Information Technology and Teacher Education in Savannah, Georgia; NISOD 2016 International Conference on Teaching and Leadership Excellence in Austin, Texas; End 2016 International Conference on Education and New Developments in Ljubljana, Slovenia; 2017 Choice Menu Conference in McHenry, Illinois; 2017 Schoology NEXT International Conference in Chicago, Illinois; 2022 AESA Annual Conference in Pittsburgh, PA). Dr. Schuett is a passionate educational researcher who is also an accomplished author of several works of fiction and a Pushcart Prize nominee. He resides in Libertyville, Illinois, with his family.

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List of Figures

Fig. 1.1

Fig. 1.2 Fig. 1.3 Fig. 1.4 Fig. 2.1 Fig. 6.1 Fig. 6.2 Fig. 6.3 Fig. 6.4

Here is an example of an in-school threshold sticker used as a cue for prompting students to put away their personal digital devices upon entering the classroom in the hope of mitigating digital distraction during learning 2 This is an in-school cell phone holder, also called a “Cell Hell” by students, where some teachers ask students to place their cell phones during class time 20 Data collection procedures used for this case study inquiry 26 Data analysis procedures chart, which highlights the steps used in this inquiry for coding 31 This is an in-school poster advertising mitigation efforts against digital distraction 52 This chart illustrates the digital distraction frequency for in-person student learning during a 75-minute instructional period101 This chart illustrates the digital distraction frequency for in-person teacher learning during a 75-minute instructional period102 This chart illustrates the combined digital distraction frequency for in-­person student and teacher learning during a 75-minute instructional period 103 This chart illustrates the digital distraction frequency for remote student learning during a 75-minute instructional period104

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List of Figures

Fig. 6.5 Fig. 6.6

This chart illustrates digital distraction frequency for remote teacher learning during a 75-minute instructional period This chart illustrates the combined digital distraction frequency for remote student and teacher learning during a 75-minute instructional period

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CHAPTER 1

The Why…

Abstract  Despite the digital policies school districts have created, and integrated, across the globe in secondary-level schools, stakeholders, especially teachers, are still scrambling to maintain students’ learning focus and academic engagement in our post-Covid educational landscape. 1:1 learning environments have become the norm across public American high schools as districts continue to use a variety of synchronous, asynchronous, in-person, remote, and hybrid learning structures. But even though technology appeared to be a silver bullet of sorts for engagement as schools infused more and more technology into the classroom setting during the early 2000s, the advent of school-issued mobile devices (i.e., Google Chromebook, iPad, tablets), coupled with students’ personal electronics (i.e., cell phones and smartwatches), the tide is beginning to shift as student focus, engagement, knowledge retention, and learning transfer continue to worsen and deteriorate. As a twenty-seven-year educator, this chapter focuses not only on the why of this digital distraction phenomenon and its significance, but it introduces the reader to a generalizable study, one which provides guidance for educational stakeholders in trying to minimize digital distraction during learning, no matter if learning is happening synchronously, asynchronously, remotely, or in-person.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. C. Schuett, Beyond Digital Distraction, Digital Education and Learning, https://doi.org/10.1007/978-3-031-53215-3_1

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Keywords  Digital distraction • Digital device • Mobile technology • Engagement theory • Cognitivist theory • Student engagement • Learning focus • Knowledge retention • Learning transfer • Metacognition • Covid-19

Background and Argument Cross the line, it’s learning time—or is it? (Fig. 1.1)

Fig. 1.1  Here is an example of an in-school threshold sticker used as a cue for prompting students to put away their personal digital devices upon entering the classroom in the hope of mitigating digital distraction during learning

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Post-COVID-19 pandemic, and the pendulum is beginning to swing back in the other direction. But instead of a subtle turning of the tide, it is more like a double-sided battle ax accompanied with a war cry from educators across the globe, “If we could just get these kids off their phones and screens, especially inside the classroom!” Yes, what was once considered a curricular jumpstart to boost student engagement is presently now becoming a dirty word of sorts inside schools—technology. As a 27-year educator, I continue to be fascinated with the role technology plays in learning. Unabashedly, I admit to being an advocate of digital learning, and I have even capitalized on this by traveling the globe, both in person and remotely, providing educational workshops on the power of the digital backchannel when conducting Socratic seminars. But COVID-19 proved to be a game changer, and my philosophy about the use of educational technology inside the classroom continues to evolve. Prior to COVID-19, 94% of children ages 3 to 18 had a computer at home, and 86% of these children had access to home internet while only 65% used the internet at school (Hull, 2017). As the use of personal 1:1 digital technology (i.e., devices and applications) continues to skyrocket in professional workspaces across the globe, school settings are keeping pace. But quantity does not ensure quality, especially when talking about the education of our youth. The COVID-19 pandemic changed the way students and educators access the internet during the school day, and with increases in remote synchronous, asynchronous, and hybrid learning, students and teachers are using mobile electronic devices (e.g., computers, tablets, cellphones, and smartwatches) in a variety of commonplace settings like their homes, libraries, and other public venues (Berdik, 2018; Berry & Westfall, 2015; Kist, 2013). But just because these electronic mediums are being used more often does not guarantee that learners are in fact learning more or even learning better. Hypothetically speaking, what if the exact opposite is happening instead? Shouldn’t a foundational tenet of digital citizenship inside the classroom be for the professionally trained educator to safeguard minors from falling into the rabbit hole of digital distraction, especially when learning is taking a backseat to entertainment and non-academic communication? If the answer is yes, then our present digital course needs to change and do so quickly and efficiently before significant learning losses compound even further. As already mentioned, digital technology includes a vast array of electronic communication applications, mediums, and platforms, which are used in both personal and professional life, ranging from texting and

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instant messaging to email and social media. It’s no secret that this uptick in mobile technology comes with a price—the diversion of students’ attention and their loss of engagement during the learning process (Cheong et al., 2016; Honawar, 2007). Boredom, entertainment, multitasking, and social media are all examples of distractions to student learning that can cause serious learning and behavioral concerns inside the classroom environment for both students and teachers alike (Cho & Littenberg-Tobias, 2016). Berdik’s (2018) research included an excerpt from a January 2018 edition of The Hechinger Report that examined distractions caused by digital technology inside American classrooms, and this research provided both narrative and quantitative information from students, teachers, psychologists, and sociologists that identified students’ compulsive use of technology. These digital distractions were cited as the reason some academic programs elected to block cell phone signals in classrooms rather than using punitive penalties to reduce digital distraction (Brazeau & Brazeau, 2009). Some might have considered this a bold move on the part of these districts, but in our post-COVID academic world, it is becoming increasingly evident that students, and teachers, need all the help they can get to recoup lost face-to-face “in person” learning. Blikstad-Balas and Davies (2017) investigated the value of 1:1 devices in the classroom setting, and their findings indicated a considerable amount of evidence pertaining to the practical benefits of 1:1 learning. Unfortunately, their findings presented little evidence of collaborative and/or systematic strategies for helping students manage their attentions and behaviors while using these devices. Charles’ 2012 small qualitative study focused on attempting to understand the rules of cellphones and other social networking devices in schools. The results from this study suggest that certain pedagogical practices situated in critical sociocultural theory could serve as potential solutions. Consequently, the applications students use on digital devices (e.g., Facebook, Twitter, Moodle, Edmodo) are another pertinent consideration for stakeholders as some classroom instructors use these applications to involve corollary learning, such as effective collaboration and strong communication skills; this extends teaching style strategies beyond more traditionalized formats (Fewkes & McCabe, 2012; Kist, 2013). But as with most things in life, the pendulum eventually swings back in the opposite direction, and today’s “in school” academic push appears to be more tactile by design than digitally driven as more teachers are requiring “on demand” and handwritten assessments

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instead of always going to the “tech well” to teach well. Undoubtedly, the evolution of artificial intelligence is a budding reason for these moves. Despite the insistence of 1:1 computer-based digital education in the present-day classroom, twenty-first century learning doesn’t, and can’t, occur inside a vacuum. To clarify, twenty-first century learning integrates the development of precise and targeted contemporary skills inside the classroom that include problem solving, collaboration, communication, connection-making, and computation. These skills are critical for students to be successful and competitive in higher education, the workplace, and in their personal lives (Blikstad-Balas & Davies, 2017). Twenty-first century workers collaboratively use digital resources to problem solve, oftentimes in “real time” as issues arise. In addition, employees must keep pace with advancing digital technologies inside unique workplaces that evolve and change, which in turn requires technology to do the same in order to keep pace. Subsequently, the modern classroom is no different. Secondary public schools have a duty to ensure that students are prepared with an adequate twenty-first century skill set in order to be competitive and successful in these ever-evolving workplaces. Additionally, we must not forget that some of the more traditional modes of “soft skills,” skills that will serve these students and their academic, behavioral, and social wellbeing, do not spring from a keyboard or off a computer or cell phone screen. The way in which learning is supervised in any twenty-first century academic setting is important since classroom management is the procedure through which an instructional facilitator (i.e., teacher, support staff, administrator, literacy coach) ensures appropriate academic, social-­ emotional, and behavioral learning actions are occurring inside an educational environment (Blikstad-Balas & Davies, 2017). To ensure appropriate classroom management in this unique and evolving learning setting while also contending with digital distraction, digital literacy, and the understanding of personal digital device culture inside the work and school setting (Seemiller, 2017), an educator must consider a variety of perspectives and practices. For example, school districts should provide continued training for teaching students how to behave appropriately when using digital resources and technologies. It is important to note that problem behaviors that cause distraction to the learning environment (e.g., assessing social media for non-educational purposes, listening to music, taking inappropriate pictures/selfies, sending inappropriate texts/images, using a personal 1:1 device to cheat/plagiarize, etc.) can happen equally as often outside the classroom as they can inside it (Cash et  al., 2019, p.  104).

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Research indicates that at least 50% of problem behaviors inside school settings actually occur in non-classroom settings like hallways, lunchrooms, study halls, and common areas (Cash et al., 2019, p. 104; Colvin et al., 1997; Nelson & Colvin, 1996). Even though research supports this trend, considerable limitations pertaining to the characteristics of this collected data are evident (Cash et  al., 2019, p.  104). This same research illustrates that observational data collected in high school is limited and emphasizes interactional quality inside the classroom more than anything else (Allen et al., 2013; Cash et al., 2019, p. 104). This was an important consideration when writing this book since most of the literature stems from inside classroom settings, even though many daily student interactions and activities occur outside of the traditional classroom setting, so digital distraction is no different. Through the development and maintenance of appropriate channels of technological fluency (i.e., professional communicative discourse and collaboration via technology and the development of digital citizenship), like the elements and actions taught through digital literacy that extend courtesy and respect throughout school and the workplace (e.g., digital citizenship), suitable digital behaviors are modeled for students. Examples from the realm of digital citizenship include the employment of business etiquette, interpersonal communication and teamwork skills, professionalism and work ethic, responsibility, and a positive work attitude, all in relation to the use of digital devices and electronic communications inside school and the workplace (Seemiller, 2017). Incorporating digital distraction as a key element in twenty-first century learning standards for secondary public schools may prove to be useful in the building, implementation, and reinforcement of these digital citizenship characteristics (e.g., professional etiquette/attitude, interpersonal/teamwork skills, workplace responsibility), which could serve as a useful tool in mitigating digital distraction’s impact on learning. The motivation behind this book’s research was a practical exploration into a current and relevant learning issue school districts around the world are struggling to understand and abate in order to increase student focus and engagement, which is the digital distraction phenomenon. This research stemmed from a case study that investigated how digital distraction was occurring inside a socio-economically diverse and largely populated (Hedrick, 2002, p. 68; Yin, 1994) Midwestern suburban high school inside the United States, one that is known for being a pioneer in 1:1 Google Chromebook integration.

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An important discovery this book posits is that teacher buy-in relating to the benefits of 1:1 learning and the allowance of mobile technology in school varies widely based on a variety of factors (Berdik, 2018; Berry & Westfall, 2015; Blikstad-Balas & Davies, 2017; Brazeau & Brazeau, 2009; Cho & Littenberg-Tobias, 2016; Fewkes & McCabe, 2012). The research shared in this book highlights exploratory viewpoints in favor of and against both mobile digital devices and 1:1 learning in secondary public schools. There is a definitive gap in existing literature pertaining to parents’ perceptions, especially in conjunction with coping strategies for their children’s digital distractions when concrete solutions are not available. Consequently, the bulk of research on classroom digital distraction revolves around students and teachers, which pragmatically makes sense even though a future study into the perspectives of other potential stakeholders could be a significant inquiry for further studies. Even though digital distraction continues to be a common worldwide phenomenon, little research has been conducted into the digital distraction happening inside schools that purposefully integrate 1:1 digital instruction and learning. Granted, this research is most applicable to secondary and post-secondary schooling since these students are more likely to have both personal and school-issued mobile technology, but the trickledown effect of seeing these same devices in more middle and primary schools continues to increase. As teenage students’ mobile technology use continues to build (Mahiri, 2011, p.  1), understanding the effects and implications of digital distraction is becoming even more important. Of the few studies done on digital distraction, Seemiller (2017) indicated that one of the major reasons digital distraction occurs in the classroom is due to non-class related actions and behaviors, which indicates a kind of conduct that could eventually evolve into discourteous workplace behavior (pp. 215–216). For example, Pettijohn’s et al. (2015) quantitative study indicated college students are motivated to engage in cell phone distraction out of boredom (38.9%) and work (35.6%), which could lead to disruptive non-classroom related behavior(s). Granted, Pettijohn’s et  al. (2015) study involved college students, but many juniors and seniors in high school are on the cusp of becoming college students themselves. Seemiller’s (2017) study corroborated Pettijohn’s et al. (2015) findings, as students combat boredom through engaging in non-class related digital behaviors like online communication, social media posts and photo sharing, information seeking, music, and other forms of digital entertainment like gaming and videos. This indicates students’ partiality toward shorter

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surges of digital distraction, but even these shorter surges of distraction affect knowledge retention as poor learning transfer and overall academic achievement suffer (Berdik, 2018, p.  40). As Blikstad-Balas & Davies (2017) stressed, pedagogical change is a necessity in the twenty-first century classroom, as educators use student-centered instructional practices that incorporate technology while minimizing the potential distractions that come with it. Creswell and Guetterman (2019) stressed the need for early identification of those who read, reflect, and likely benefit the most from data collected on a research problem (p. 70). Undoubtedly, teachers, administrators, and support staff, as both formal and informal change agents, stand to garner the most from this book. In addition, the benefits this book provides for students and parents, especially as current instructional and managerial learning practices and policies continue to evolve due to 1:1 mobile technology, may help to achieve more focused learning, whether learning is happening in person or remotely. Exploring how to mitigate digital distraction helps policy makers and practitioners better create and sustain meaningful student-centered learning practices and interventions inside these digitally driven academic environments, whether the instructional settings are brick-and-mortar school buildings or remote learning hubs located inside homes. This book can also inform educational software and hardware developers of these same kinds of meaningfully digitally driven learning practices and interventions, potentially helping them to adjust and enhance their educational learning applications and programs to promote and improve student learning. The role of increased technical fluency and digital citizenship should be valuable byproducts of this book, too. Research related to workable solutions for exploring and assessing digital distraction in schools, including schools that have been fully 1:1 integrated for some time, is far and few in between. Most of the current information regarding digital distraction at school that has been shared professionally is anecdotal, and the majority of proposed solutions to digital distraction when learning are personal trial-and-error examples of things that sometimes work to mitigate digital distraction. Because of social media and the ever-present immediate access to digital entertainment, twenty-first century students must learn how to navigate mobile technology inside their learning environments. Since social media and digital entertainment are only building momentum among millennials, exploring adolescents’ compulsion to stay connected through these digital

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social circles, which they often use to combat boredom (Seemiller, 2017, pp. 217–218), is a significant reason for reading this book.

Theoretical Underpinnings Engagement theory and cognitivist theory provided the theoretical framework for this inquiry. Engagement theory is rooted in technology-based teaching and learning (Kearsley & Shneiderman, 1998; Marshall, 2007, p. 109), while cognitivist theory (Bélanger, 2011) provided a lens through which to analyze stakeholders’ participation with and attention toward mobile digital devices in both traditional and remote instructional learning settings.

Engagement Theory The meaning of engagement varies across ideological viewpoints (Francis, 2018, p.  3), but key perspectives embrace rational/technical, critical/ transformative, and interpretative/student-centered tenets (Hagel et al., 2010; Vibert & Shields, 2003). Engagement theory is a technologically based teaching and learning framework that promotes authentic learning experiences through worthwhile educational tasks (Kearsley & Shneiderman, 1998; Marshall, 2007, p. 109), like classroom activities that bridge the gap between students and their communities (e.g., project-­ based learning for community service). In order for engagement theory to be applicable to academic achievement and learning transfer, students must be meaningfully involved with collaborative project-based assessments that broker effective learning (Kearsley & Shneiderman, 1998). Consequently, this type of learning works well and in tandem with digital technology, facilitating relationships through collaboration while fostering creative, meaningful, and authentic learning (Kearsley & Shneiderman, 1998). Engagement theory served as an analytical research tool for this book since participating students and teachers engaged daily with collaborative learning activities through 1:1 integrated digital technology throughout this study. Theoretically, experiential knowledge, existing theory, and exploratory research (Maxwell, 2004, p. 37) coordinate well with engagement theory, along with engagement theory’s significance to twenty-first century’s 1:1 learning initiative. This is more important than ever as formerly

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non-traditional mediums like virtual reality and remote learning are now becoming the norm in our post-COVID world. Since the research in this book focuses on digital technology inside instructional settings, cognitivist theory also plays an important role due to students’ acquiring and processing knowledge (Bélanger, 2011) through the use of mobile digital devices. Bélanger (2011) stated how “acquiring and processing of knowledge is a cognitive process, a rational one” (p. 23). This mental process allows learners to store, organize, evaluate, and retrieve both procedural and non-procedural knowledge, facilitating both short and long-term memory to “generate relevant responses” (Bélanger, 2011, p. 23) that help to sustain attention to on-task learning behaviors. Bandura and Walters (1977) and Bandura (1994, as cited in Bélanger, 2011, p.  23) stated there is a reciprocal interaction between human beings and their environment, so individual and environmental influences could affect learners’ attention inside instructional settings when using mobile digital technology. Wang’s et  al. (2014) research highlighted the presumption that, “increased achievement, enrollment in challenging courses, and reduced dropout rates,” which are specific variables of growth measurement established by the US Federal Department of Education, drive educators’ efforts to foster student engagement (p. 517). Research also indicates that engagement fosters a relationship between behavioral and learning interventions when implementing reform efforts (Wang et al., 2014, p. 517) like restorative justice initiatives, restorative circles, behavioral/learning contracts, and mandatory after-school guided study. Likewise, Duckworth et  al. (2007, pp.  1087–1088) stated that grit, or “working strenuously towards challenges, maintaining effort and interest over the years despite failure, adversity, and plateaus in progress,” affects learning engagement inside the classroom. In layman’s terms this simply means that engagement is multidimensional, and it is usually firmly entrenched in specific learning activities (Christenson et al., 2012; Fredricks et al., 2004; Skinner et al., 2008, 2009a, 2009b; Muenks et al., 2017, p. 602), especially those that are cooperative and digital in nature. What also needs to be included in our discussion of engagement is behavior engagement and disaffection, both of which relate to grit because of the “perseverance and passion for long-term goals” (Duckworth et al., 2007, pp. 1087–1088) and their effects on engagement inside the classroom. Muenks et al. (2017) stated that while Duckworth’s et al. (2007) work on grit continues to gain traction inside educational circles (p. 158),

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few studies have been conducted on the relationship between grit and high school students (p. 162). Muenks et al. (2017) also states that studying 11th grade students and their relationship(s) to grit is important since these students are transitioning to careers and higher education, two key benchmarks of adulthood (p. 162). A decade before Muenks’ et al. (2017) study, Duckworth and Quinn (2009) discovered that grit played a predictive role regarding GPA achievement in a sample of middle and high school age students, “controlling for age and hours spent watching TV” (Muenks et al., 2017, p. 162). Also, Eskreis-Winkler et al. (2014) revealed how grit predicted graduation rates when “controlling for conscientiousness, school motivation, situational factors, standardized achievement test scores, and demographic variables” (Muenks et al., 2017, p. 162). Muenks et al. (2017) stated that perseverance regarding effort (but not consistency between or among interests) predicted junior high school students’ grades when “controlling for gender and ethnicity, but neither grit component significantly predicted grades when controlling for personality, self-­ regulation, and engagement variables” (Muenks et  al., 2017, p.  162). Muenks et  al. (2017) used the Grit-S (Duckworth & Quinn, 2009) to measure 190 high school juniors (52.6% female) in a mid-Atlantic region of the United States (p. 163) and found based on the analysis of quantitative data that more research is warranted pertaining to what long term means, especially relating to the developmental measurement of grit between age groups (pp. 164–173). Classroom engagement equates to students actively participating in learning activities inside academic arenas (Reeve et  al., 2004; Skinner et  al., 2009a, b; Wang et  al., 2014, p.  517). This includes “attention, interest, investment, and effort students expend in the work of learning” (Marks, 2000, p. 155; Wang et al., 2014, pp. 517–518). Engagement can be organized into three dimensions: affective (emotional), behavioral, and cognitive (Archambault et al., 2009; Fredricks et al., 2004; Wang et al., 2014, p. 518). Affective engagement includes the positive emotions students experience inside a classroom setting, like curiosity, enjoyment, and enthusiasm (Fredricks et al., 2004; Skinner et al., 2009; Wang et al., 2014, p. 518). Behavioral engagement includes “effort exertion, persistence, attention, and concentration” (Skinner et al., 2009) while behavioral affection incorporates both “passivity” and opting out of achievement activities (Muenks et al., 2017, p. 602; Skinner et al., 2008). Another interesting component of behavior engagement is that it is observable. For example, in-class

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behaviors like “time-on-task, overt attention, classroom participation, question-asking, and choice of challenging tasks” are observable student choices occurring inside the classroom setting (Wang et al., 2014, p. 518). The last dimension, cognitive engagement, relates to the mental aspects of engagement (i.e., cognitive processing, mental strategy, concentration, meta-reasoning, metacognition), all of which occur at the classroom level (Wang et al., 2014, p. 518). Fredricks’ et al. (2004) research indicates that the majority of engagement studies merely concentrate on one of the types of engagement (p. 83), so there is a present-day need for educational stakeholders to explore multiple elements of classroom engagement across a variety of instructional learning scenarios (Wang et al., 2014, p. 518). This is why the exploration of student engagement while using mobile digital technology during both in-person and remote learning is so important, and the COVID-19 pandemic provided a unique lens to do just that. Having an awareness of student engagement for learning and academic achievement is a must for any teacher, school leader, and parent. The chance of successful school completion hinges on the fostering of commitment and belonging that stems from student involvement and participation in the schooling process (Christenson et  al., 2001; Shernoff et  al., 2003, p. 159). An earlier study focused on the phenomenological aspect of “high involvement in classrooms, which includes concentrated attention, interest, and enjoyment as opposed to apathy and lack of interest with instruction” (Newmann, 1992; Shernoff et al., 2003, p. 159). Since high engagement during tasks in high school has proven to be a strong predictor of continued motivation and college success (Shernoff & Hoogstra, 2001), identifying various potential influencers on engagement is an important first step (Shernoff et al., 2003, p. 159). Some of these phenomenological factors that influence student engagement include instructional relevance and perceived control (Shernoff et al., 2003, p. 159). When educational instruction is deemed relevant by students, students have a greater propensity toward engagement because the academic work is authentic. This authenticity segues into academic work that is “meaningful inquiry to solve real life problems that extend beyond the classroom” setting (Newmann, 1992; Shernoff et al., 2003, p.  159). Additionally, student control over learning choices inside the classroom have attributed to increased positive emotions, furthering the phenomenological significance student engagement plays (Deci et  al., 1981; Shernoff et al., 2003, p. 159).

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Other than phenomenological influences, instructional and teacher factors can also affect student engagement. Specifically, instructional format and delivery, coupled with particular school subjects (Shernoff et  al., 2003, p.  159), can influence student engagement. Grannis (1978) and Stodolsky (1988) cited how students’ engagement increases in more student-­ controlled activities (e.g., cooperative learning, project-based learning) versus more traditional teacher-centered instruction like lecture (Shernoff et al., 2003, p. 160). Marks (2000) extended this distinction by stating that individual and small-group instruction is more student-­ controlled than whole-group learning is, which is often perceived as teacher-controlled (Shernoff et  al., 2003, p.  160). Interestingly, certain traditional summative evaluations and assessments like “exams and other external evaluations that emphasize social comparisons” appear negatively to influence students’ curiosity and attentiveness (Boggiano et al., 1998; Shernoff et al., 2003, p. 160). Exploring how teachers use mobile digital technology across both traditional and non-traditional instructional formats is an important step in identifying engagement levels, particularly now as students across the globe continue to navigate both in-person and remote learning post-COVID-19 pandemic. Certain demographic factors and learning history also influence student engagement. Flashing back to the twentieth century, educational researchers cited that females reported being more engaged than their male counterparts did inside the classroom setting (Finn & Cox, 1992). A decade or so later, Yair (2000) argued that 6th and 8th grade students were more engaged than 10th and 12th graders (Shernoff et  al., 2003, p.  160). Reinforcement history, or the degree to which on-task behavior is rewarded and praised in the past, directly correlates to student engagement in the present (Martens et al., 1997; Shernoff et al., 2003, p. 160). Interestingly, the research does note that the corresponding effect sizes regarding demographic differences and previous learning history are quite small when compared to instructional and classroom factors (Marks, 2000; Shernoff & Hoogstra, 2001; Shernoff et al., 2003, p. 160), which is something that needs to be taken into account too. Another consideration is that school engagement does not always mirror classroom engagement (Wang et al., 2014, p. 518). For instance, the same student may be exceedingly more engaged in one class than another (p.  518). Plus, classrooms vary across averages in student engagement, teaching style, and student makeup (Darr, 2012), not to mention how the measurements used to assess engagement often intermix classroom

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engagement with school-level engagement (Fredricks et al., 2004; Wang et al., 2014, p. 518). In the creation of this book, I would be remiss in failing to discuss the importance of flow theory as it relates to engagement, too. Shernoff et al. (2003) described flow theory as a theory “based on a symbiotic relationship between challenges and skills needed to meet those challenges” (p.  160). Csikszentmihalyi (1996) denoted that highly creative professionals (e.g., artists, scholars, athletes) experience flow: “a state of deep absorption” in their skilled activity that is “intrinsically enjoyable” when focused on their play/performance (Shernoff et al., 2003, p. 160). Because the state of flow is intrinsically motivating, students and teachers should seek to replicate the same feelings experienced in the flow state (Shernoff et  al., 2003, p.  161). Csikszentmihalyi (1997) asserted that one must simultaneously experience concentration, interest, and enjoyment in any given activity for the flow state to ever occur (Shernoff et al. 2003, p. 161). Engagement theory shares theoretical elements with constructivist and problem-based learning approaches, and teachers can maximize student learning through the use of interactive technology by increasing levels of engagement otherwise not afforded via other approaches (Kearsley & Shneiderman, 1998; Marshall, 2007, p.  109). Because of this, engagement theory helps to explain certain cognitive processes and behaviors (e.g., construction, problem solving, synthesis, decision-making, evaluation) seen in significant learning tasks and meaningful learning experiences (Kearsley & Shneiderman, 1998; Marshall, 2007, p.  109). Again, the COVID-19 pandemic provided an opportunity for the exploration of teachers’ use of interactive technology to increase student engagement for both in-person and virtual learning. Even though “traditional methods of tertiary instruction” (Marshall, 2007) may be valuable for providing students with information, these practices do not allow for the development of collaborative skills (p. 110). Furthermore, the application of engagement theory helps students to develop more profound levels of understanding pertaining to course concepts and instructional outcomes (Kearsley & Shneiderman, 1998, as cited in Marshall, 2007, p. 111). Engagement theory emphasizes learner collaboration through hands-on, project-based tasks ensconced within real world applications, which results in innovative and authentic learning experiences (Miliszewska & Horwood, 2006). Engagement theory is not just grounded in student engagement—it factors in “learning, retention and performance,” too (Gunuc & Kuz, 2015), in relation to a “student’s

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psychological investment, effort and interest in learning” (Francis, 2018, p. 3; Hagel et al., 2010; Vibert & Shields, 2003). Subsequently, engagement theory unilaterally ties into a variety of learning perspectives, something educators should model and integrate for their students. The technical perspective of engagement theory is both current and significant; educators should be creating curricular activities that are important to twenty-first century learning, and student engagement is a prerequisite for the completion of these meaningful activities (Francis, 2018, p. 3). This is important work as students, teachers, and administrators daily use both personal and school-issued 1:1 digital devices to complete class-related tasks deemed as important (e.g., attendance, assignment completion, discussion threads, email posts, calendar entries). Pertaining to the critical/transformative element of engagement theory, learners must be willing to engage in critical reflection, the suspension of judgment, and the transformation of personal perspectives through questioning and reframing ideological stances and beliefs (Francis, 2018, p. 4; Hodge, 2011). Hodge (2011) posited an interesting perspective that transformative learning does not align with skills and knowledge normally measured through traditional assessment tasks (Francis, 2018, p.  4). Engagement theory’s critical/transformative perspective provides a lens through which to observe students’ motivation to learn with digital technology, which could occur in conjunction with the kind of collaborative teamwork (Miliszewska & Horwood, 2006) that happens outside the brick-and-mortar classroom. This adds a dimension of real-world authenticity to learning since digital technology provides a medium through which twenty-first century learners can create, implement, and sustain new ideas in and around the workplace setting, whether they are working individually or in groups. Because of this, Hodge’s assertions provide a unique conceptual foundation from which to launch a theoretical inquiry into engagement theory’s usefulness. A quantitative study investigating the appropriateness of engagement theory as a theoretical framework for incorporating culturally inclusive curriculum inside a transnational context indicated that some students valued instructional content and collaboration when project-based tasks were modeled (Miliszewska & Horwood, 2006). Yet again, this illustrates how both students and teachers can use technology to motivate learning in these types of twenty-first century instructional settings. Educational researchers theorized that the interpretive/student-­ centered perspective of engagement theory provides a lens through which

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to observe how learners construct knowledge and meaning from experience (Francis, 2018; Hagel et al., 2010; Vibert & Shields, 2003, p. 4). Through the 1:1 integrated learning environment, students have more autonomy and choice pertaining to their learning processes, coupled with greater ease for self-reflection of classroom tasks and activities (p.  4). During the COVID-19 pandemic, students may have benefited from increased autonomy and choice as more teachers likely assigned digitally driven asynchronous work due to remote learning requirements. Engagement theory provides a valuable construct for this book, especially pertaining to its potential significance regarding twenty-first century learning. 1:1 learning is, by nature, hands-on; it gives learners the opportunity to engage in non-traditional mediums like virtual reality and distance learning. For example, opportunities like distance learning and virtual reality allow students to work beyond the walls of their classrooms, encouraging authentic learning experiences through the expansion of cooperative learning circles through sharing and cooperating with others around the world in real time. Additionally, engagement theory affords an opportunity to observe both self-engagement and group interaction inside a classroom setting. As the primary researcher for this book’s case study, I collected and coded participant narratives concerning student and classroom engagement via in-depth, semi-structured, one-on-one interviews. I also integrated an interactive self-reporting log where participants could identify cause and tally frequency of digital distraction occurring during an instructional period. Coupling interviews with both interactive participant logs and a formal research journal helped to increase the effectiveness of data triangulation for this book.

Cognitivism Cognitivist theory provides a strong lens to consider the research shared in this book because, “learners, becoming aware of their learning process in their specific context is indeed a critical ability which could predict their autonomy and self-development” (Bélanger, 2011, p. 26). Such actions of metacognition can tie directly to both attention and engagement in digital device usage during learning. Trying to understand attention, especially regarding on-task versus off-task classroom behavior(s) when using mobile digital technology, is important for instructional facilitators. Cognitivism provides this theoretical link between the human condition of learning, the consequences of learners’ actions, and the most appropriate alternative

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solutions, all of which potentially culminate in classroom management strategies and potential solutions for mitigating any digital distraction that negatively affects student learning (Bélanger, 2011, p. 22; Gagné, 1985). Legendre (2005, as cited in Bélanger, 2011) stated that cognitivist theory, influenced by research on artificial intelligence, helped to interpret cognitive processes (i.e., reasoning), specifically in relation to the organization and handling of information. Interestingly, Gestalt theory influenced cognitivist theory since the Gestalt model interpreted learning as “an inner cognitive process” (Bélanger, 2011, p. 22). Cognitivists believe that inner non-observable cognitive processes may provide insight into what causes distraction versus what sustains attention when using mobile digital technology during learning. Lodge and Harrison (2019) stated the one cognitive function “consistently featured as the primary place where technologies are having a negative impact: attention” (p. 23). Subsequently, educational researchers can use cognitivist theory to explore the thinking behind attention, investigating how students process information in digital learning environments. Cognitivist theory’s basic principles and pedagogical implications include the following key concepts: procedural “know how” and non-­ procedural knowledge, short and long-term memory, knowledge transfer, metacognition, cognitive dissonance, and simple to complex learning sequencing (Bélanger, 2011, p.  24). Educators using any of these concepts as steps in the cognitivist framework may want to explore what inner cognitive processes may help chunk curriculum into manageable parts and organize those parts into sequential hierarchy that becomes increasingly more complex (Bélanger, 2011, p.  20; Fosnot, 2005). Digital learning management systems (i.e., Blackboard, Google Classroom and Schoology) provide an online space for teachers to manage curricular parts. Teachers can use these online management systems to sequence instructional units and subunits with embedded digital formative and summative assessments that reinforce learning tasks for students. Bruner (1996, 2009, as cited in Bélanger, 2011, p. 24) stated that there are some parallels between human learning processes and the kinds of information processing performed by some computational devices. This contextually ties into this book’s sample since study participants received instruction and learning inside a setting that integrated mobile digital technology for information processing. Conceptually, cognitivist theory also plays an important role in understanding the importance of this book’s findings. Educators should consider cognitivism’s key concepts when integrating learning sequences,

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especially those they deem appropriate for 1:1 integrated learning environments. For example, memory is one of cognitivism’s key concepts, and it both affects and is affected by attention during the learning process. When students retrieve knowledge, they initially catalog the information as “short term” memory before it is “processed, transferred, and encoded into long term memory” (Bélanger, 2011, p.  23). This could play an important role in classroom management pertaining to digital distraction since students make lasting associations between the consequences given by teachers for certain behaviors, which could increase attentiveness to on-task behavior(s). This same idea is also transferable to punitive consequences assigned to students from school administrators like deans and principals, too. The online learning environment can influence student behavior positively through engagement and negatively through distraction. Through discussion, reflection, and knowledge of such cognitive processes, students become more conscious of their own learning processes like metacognition, which allows them to better navigate complex learning sequences (Bélanger, 2011, p. 24). Only through appropriately reinforced simple and sequenced cognitive processes can students become better managers of their own digital learning behaviors like on-task learning, enhanced student participation and engagement, digital citizenship, and online safety. Furthermore, through the lens of cognitivist theory, we can better understand how research participants’ minds work in terms of student actions, behaviors, and reactions with digital device use and misuse, regardless of whether it is happening in school or remotely from home. In addition, cognitivist theory provides a theoretical construct through which to reflect over perceived cognitive conflicts and problem situations (Allal, 1998, and Astolfi, 1997, as cited in Bélanger, 2011, p. 24), which depending on context and variable(s) could become more problematic for a student in one learning setting as compared to another.

My Positionality Because I have worked exclusively inside a 1:1 integrated environment for the past decade, my perspective of digital distraction inside secondary and post-secondary environments may differ from other educational worldviews. I likely have more experience with this kind of learning environment, especially since I have traveled and shared Socratic seminar techniques that incorporate a digital backchannel into the instructional

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setting at a variety of professional educational conferences (i.e., AESA, Schoology, NCCEP/Gear Up, SITE, NISOD, END). This undoubtedly illustrates my advocacy for 1:1 learning with certain instructional techniques, which may be more liberal than other educational practitioners. This book does in no way critically analyze the Socratic seminar instructional method, but I felt it was important to acknowledge my use of it as a teacher inside the 1:1 digital classroom. Maybe buffered within my positionality is a certain sense of guilt, too. Anecdotally speaking, many educators are increasingly feeling like heretics after signing off on the use of digital technology inside the school setting. Presently, there is likely no dirtier word that can be uttered in and around the halls of school for teachers than cell phone. And it’s not like certain mitigating actions haven’t been tried (Fig. 1.2). Granted, much of this digital insistence within school districts is top-­ down, but maybe a few of us educators became temporarily blinded by the bright shiny objects (e.g., Google Chromebooks, Apple iPads, Macs) partnering software developers/companies and school district’s disguised as magic bullets and imposed on educators over the past decade. Educational stakeholders become somewhat concerned when hive mentality is employed within school districts, and rightfully so. But now when it comes to mobile technology use during learning, no matter if the instruction is in person, remote, or hybrid, maybe hive mentality seems a little less like mob mentality and a little more like good old fashioned common sense. Operating too many forms of technology at once during the learning process is a critical issue discussed throughout this book. All too often, when just a single particular piece of technology fails inside working academic environments, learning slows or comes to a halt. So, one can only imagine how juggling multiple digital failures on multiple devices would hamper learning focus and engagement. When situations like this arise, students and teachers put the onus of their blame for this interruption in learning on technology. Sometimes, stakeholders rely too heavily on multiple digital devices or technological applications (i.e., teachers projecting instructional material on a smartboard while students are also working independently on a digital backchannel via some electronic discussion thread in Schoology). This causes students and teachers to struggle with troubleshooting issues in real time because of competing technologies. For example, if teachers and students are familiar with only using technological applications for a backchannel discussion, what happens if the digital backchannel has a bug or technical issue when learning is happening,

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Fig. 1.2  This is an in-school cell phone holder, also called a “Cell Hell” by students, where some teachers ask students to place their cell phones during class time

or if the school’s Wi-Fi network has a major connectivity issue. If teachers and students know how to operate non-digital techniques when problems arise, there is little to no obstruction to or pause in learning, even if a piece of technology fails in the middle of a lesson. Learning transfer and retention can suffer when users attempt to micromanage their learning through digital technology alone (Berdik, 2018, p. 40). Blikstad-Balas and Davies (2017) indicated the importance of change agents, whether teachers, instructional coaches, or school leaders, needing to modify instructional techniques when students are using technology. When technology creates

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a distraction for student engagement and interrupts attention, learning transfer and knowledge retention suffer. Since most American high schools now provide 1:1 technology for teachers and students on site, and since I am an American secondary educator, I should go a little more in depth concerning my own personal assumptions in writing this book. As previously mentioned, I have advocated for digital learning in and out of the physical brick-and-mortar school building. I have witnessed firsthand the power of certain technological tools and apps like the digital backchannel and virtual reality (VR) in making learning more engaging for both students and teachers. Because my students and I have worked well beyond the integration of simple classroom laptop use, my perspective of 1:1 technology inclusion may be widely different from others. As a result, my former students’ experiences may be different from those in other classrooms. Being cognizant of these implicit biases, values, and experiences helped my transparency as the primary researcher throughout my method. Bracketing out and suspending judgment pertaining to any internal conjectures I had regarding digital distraction in the 1:1 integrated classroom, coupled with holding external assumptions stemming from the digital distraction phenomenon itself in abeyance (Gearing, 2004, p.  1433), was a continual reminder for me when writing this book. Operating with this degree of reflexivity was necessary, especially when collecting data since I developed a working relationship with my study participants. Subsequently, I had to be continually cognizant of how study participants perceived me, and how I assumed they perceived me, in relation to how I perceived them. Without explicitly interweaving these reflexive insights and perspectives throughout the study, I could have jeopardized the legitimacy of this research. This reflexivity also helped to foster mutual trust between me as the researcher and study participants in both the data-collecting and reflective analysis portions of the study. Since I used Otter.ai’s Chrome extension to transcribe my collected interview data, it allowed me to better immerse myself into the rich narrative experiences shared from study participants, making it easier to locate meaningful themes and patterns. I also incorporated a formal research journal to reflect upon my personal biases (e.g., technology is an important daily instructional learning tool both in and out of the classroom setting) while acknowledging any limitations to the research site during the data-collecting phase, especially because of mandated COVID-19 school procedures with emergency protocols at the research site.

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My Motivation for Writing This Book My purpose for writing this book is to share findings from my exploration into stakeholders’ perspectives about the digital distraction caused by mobile technology in 1:1 integrated learning environments. Initially, my goal was simply to explore the viewpoints of teachers and students regarding digital distraction to discover if digital distraction contributed to poor engagement and attention lapses during learning inside a public American high school. The secondary American high school presented itself as an important gap in the 1:1 knowledge base over digital distraction, especially when considering there are over 33,000 public high schools inside the United States alone. After conducting research before, during, and post-COVID-19 restrictions, it is now more evident than ever that poor engagement and lapses in attention are not the only valuable byproducts of this work. This book also identifies potential next steps, real time suggestions and strategies, that educational policy makers, practitioners, and students can take to manage digital distraction during learning. As a lifelong educator, the last thing I ever want is to be setting students up for failure. Technology, when harnessed and channeled appropriately, can be a positive motivator and tool for learning. But when technology becomes curricular fast food for our students—an educational diet rich in instant gratification, copy-and-paste jobs, shiny bells, and shrill whistles—learning becomes nothing more than optics on a screen.

Driving Questions This research examined the digital distraction caused by mobile devices inside a 1:1 digitally integrated public American high school. The central research question was open-ended, flexible, and broadly indicative of experiential narratives stemming from a specific site, a large district known for being a pioneer in 1:1 learning. Due to the cultural phenomenon of using and applying mobile digital technology, research participants had plenty of flexibility and latitude regarding how they wanted to describe their experiences with digital distraction in school, whether that setting was in-person or remote. R1: What types of experiences do teachers and students have with digital distraction inside the school setting? S1: How do participants define digital distraction in the classroom and school?

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S2: S3: S4:

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How do participants see digital distraction occurring and experience digital distraction in the classroom and school? What do participants believe contributes to digital distraction in the classroom and school? How do participants respond to digital distraction in the classroom and school?

The Method Matters As technology continues to influence society and professional workspaces, it is unsurprising that school districts across the world are struggling to understand how digital technology is being used and misused inside their school systems. The case study highlighted in this book explored what is happening inside one American high school, one that has been 1:1 Google Chromebook integrated since 2011. Since 1:1 integration at this site, teachers have voiced concerns regarding the negative impact to learning due to students’ inappropriate use of technology inside school in common areas like classrooms, hallways, cafeterias, washrooms, locker rooms, buses, auditoriums, and gymnasiums. Faculty and staff have documented the negative impact of inappropriate technology use on student behavior and learning, citing such concerns during their district’s monthly occupational advisory committee meetings too. To counter such concerns, school leadership at this case site implemented a new cell phone usage policy in the fall of 2019 after receiving survey results from 88 high schools pertaining to allowable mobile phone usage inside cafeterias and during passing periods. One of the largest concerns faculty and staff voiced was that when students listen to music during passing periods, they struggle to both figuratively and literally “turn off” the distraction when they cross the threshold into any given classroom. Distraction from the onset of the learning process cannot be a suitable precursor for learning as teachers inside this research site have implied. Berdik (2018) reiterated that even small lapses of digital distraction cause poor learning transfer and retention (p. 40). Because of this concern for digital distraction, school leaders at this case site employed a handful of interventions to help mitigate digital distraction among students (e.g., creation/integration of a three-step cellphone offense policy). Unfortunately, the district’s initial interventions did not net the gains faculty hoped for as student classroom grades still suffered. Norm-referenced standardized test scores indicate learning transfer and knowledge

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retention among students are still suffering too, resulting in lowered academic achievement of students. This reinforces Berdik’s (2018) research that any degree of digital distraction encourages academic shortcomings (p. 40). The qualitative method was used to explore the problem of digital distraction while developing a comprehensive interpretation of this present-­ day digital phenomenon (Creswell & Guetterman, 2019). By gathering in-depth interview data, I was able to catalog my findings in order to analyze digital distraction inside a 1:1 secondary-level learning environment. The qualitative approach provided a medium from which to understand participants’ real-world experiences pertaining to digital distraction inside a 1:1 setting, bringing to surface strategies to mollify, and possibly even mitigate, digital distraction during learning. The definition of a paradigm is a group of “shared assumptions, values and views about the phenomena addressed in particular sciences” (Smith, 2008, p. 4; see also Imenda, 2014, p. 190). The qualitative and quantitative research paradigms are the most commonly utilized models in present day research (Denzin, 1978; Dzurec & Abraham, 1993; Guba & Lincoln, 2005; Imenda, 2014, p. 190; Johnson & Onwuegbuzie, 2004). I specifically used a qualitative research paradigm, which meant as the primary researcher, I had to be aware of my positionality to minimize bias, embrace a worldview, and safeguard the perspectives of study participants. In addition, I established a more personalized relationship with my participants through the qualitative method; the research design was thematically structured and narratively supported. I would argue that teaching is a profession built upon the fostering of positive relationships. Since study participants were students and teachers, the case study provided an opportunity for stakeholders to share personalized experiences and viewpoints, which provided narrative rich data for this book. The methodology I employed for this study was rigorous. Not only was my approach time consuming and labor intensive, but the qualitative method with semi-structured interviews culminated in over 1000 pages of research data that had to be culled line by line through three distinct methods of coding. The qualitative approach provides the researcher with a lens through which to observe stakeholders’ real-world experiences in order to explore a complex problem while developing a comprehensive understanding of the problem (Creswell & Guetterman, 2019). The qualitative method is not only discovery-oriented; it is also helpful for hypothesis-generation and the meaningful consideration of study participants’

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lived experiences and viewpoints (Minges et al., 2015, p. 382; Pope et al., 2007). In addition, the qualitative approach is advantageous in the exploration of “perceptions, processes, barriers, and facilitators of complex phenomena” (Johnson & Waterfield, 2004; Minges et  al., 2015, p.  382), which helped me to develop a deeper understanding of stakeholders’ viewpoints and perspectives. The qualitative method was also the most appropriate for this inquiry because it allowed me to best explore stakeholders’ experiences about digital distraction and attention lapses in relation to their levels of engagement in school. Through specific sources of data (in-depth individual interviews, interactive log, and formal research journal) and their collection, I was able to develop a rich narrative from the viewpoints of study participants (Fig. 1.3). Finally, the coding process used in the qualitative approach allowed me to identify the necessary “active codes” (see Table  13.1, Creswell & Guetterman, 2019, p. 436) required to capture and analyze themes, messages, and patterns shared by study participants regarding digital distraction and behaviors associated with it. Cousin (2005) asserted there is no “settled view” regarding the limitations of case study research, but in general, case study research “aims to explore and depict a setting with a view to advancing understanding of it” (pp. 421–422). This theory is supported by Yin (2003). Selecting a case study for an inquiry into digital distraction allows “an in-depth exploration of the actual ‘case’” (Creswell & Guetterman, 2019, p.  477; Yin, 2014). Since this technique is typically researcher-centered, it often involves in-depth interviewing as it “attempts to provide a holistic portrayal and understanding of the research setting” (Cousin, 2005, p. 423). Case studies allow researchers to focus on specific programs, events, and activities involving small groupings of individuals instead of large groups (Creswell & Guetterman, 2019, p. 477; Stake, 1995). Since case studies are in-depth explorations of bounded systems (separated via time, place, and physical boundaries), its use regarding this inquiry is significant (Creswell & Guetterman, 2019, p. 477). Consequently, the boundaries of case study research correlate with the physical boundaries, activities, and time span of the inquiry (Cousin, 2005, p. 423), as this research does with the boundaries of a traditional public American high school. Researchers often refine their focus throughout the course of a case study; hence, the importance of the researcher establishing both “temporal and spatial

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Fig. 1.3  Data collection procedures used for this case study inquiry

parameters” for the study is vital (Cousin, 2005, p. 423), which is something this book accomplishes. The case study proved to be an appropriate research design for this topic because digital distraction is a budding twenty-first century phenomenon—a phenomenon that not only occurs at the research site used for this book, but one that is prevalent across the world in this post-­ COVID era of hybrid learning. The case study design allowed me to highlight the prevalence of digital distraction in an established 1:1 learning environment, one that fully mandated 1:1 learning 8 years prior to COVID lockdown. Because the site was a pioneer of 1:1 learning on the secondary level (i.e., one of the first all-district 1:1 Google Chromebook sites inside the United States), it provided useful research tools (in-depth individual interviews, interactive log, and formal research journal), which Creswell (2015) argued is necessary for qualitative studies. The case study design allowed me to serve as the primary researcher. Not only was I the chief instrument in data collection and the analysis of

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gathered interview data, but I was also able to collect study participants’ real-world experiences in a natural setting (Merriam & Tisdell, 2016) by having them participate in a self-reporting interactive log. This log allowed participants to identify how often (and by what means) they became digitally distracted throughout two 75-minute periods of learning and instruction (one “in person” and the other “remote”). Since I used the qualitative research paradigm, one of the most commonly used models in present day research (Denzin, 1978; Dzurec & Abraham, 1993; Imenda, 2014, p. 190; Johnson & Onwuegbuzie, 2004; Guba & Lincoln, 2005), I had to ensure a more personalized research relationship with the participants, especially since the design was thematically structured and narratively supported. Given their familiarity with me, participants felt more at ease sharing their insights and opinions with me as an interviewer. This, in turn, protected the authenticity of the data collection. I also continued to be aware of my positionality in order to minimize bias while safeguarding study participants’ viewpoints. Later in this chapter, I will delineate conflicts of interest due to my role at the case site and how I mitigated them, as minimizing researcher’s bias is not the same as minimizing the risks of collecting data influenced by my status as an organizational insider. Circling back, the purpose statement and research questions for this book support the research design definition of a case study. The purpose of this inquiry was to explore stakeholders’ experiences and viewpoints about digital distraction caused by mobile technology inside a 1:1 integrated learning environment, with an end goal of analyzing what causes poor engagement and attention lapses during learning. The central research question dealt directly with the types of experiences teachers and students have with digital distraction inside the school setting (in-person and remote) while the sub questions narrowed the inquiry by asking study participants to: define and describe their observations and experiences with digital distraction in school, explain what contributes to this distraction, and express how people respond to digital distraction in school. The central and sub research questions reflected engagement and cognitivist theory by asking participants to share experiences and observations regarding how digital distraction affects levels of engagement and attention lapses during learning. As mentioned earlier in this chapter, case study research allowed me to be the primary research instrument: It afforded me the ability to create “fuzzy generalizations” (Bassey, 1999) about the study’s aim while

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predicting potential probabilities with words like “may” instead of words like “will” (Cousin, 2005, p. 426). The research questions for this inquiry probed participants’ viewpoints associated with the impact of digital distraction on student engagement and attention during learning. Participants shared their experiences with digital distraction in school by defining it, explaining how they saw it occurring, identifying what contributed to digital distraction, and sharing stakeholders’ responses to it. These research questions coincided well with case study research since its design centered around “description, exploration and understanding” (Cousin, 2005, p. 426).

Sample, Data Collection, and Analysis Since this research involved a small sample size with personalized interactions between the researcher and participants, I was able to explore both the researcher’s perspectives as well as participants’ viewpoints, comparing and contrasting the existing individualized constructions between the two (Guba, 1990, p. 26). As previously mentioned, the setting was a public high school in the suburbs of a major metropolitan area inside the United States. This site has been fully 1:1 Google Chromebook integrated since 2011, and my rationale for selecting this public American high school as the data-collection site was purposeful since it is a pioneer of 1:1 learning, and there is a definitive gap in data collected over digital distraction from inside public high schools across the United States. The teacher-participants discussed in this book worked in three different classrooms, each representing a different discipline and grade level (two male, one female; math, science, and social studies departments; no bilingual teachers). This provided a well-rounded sample since no single discipline or grade level dominated the set. In addition, 12 students from a pool of interested volunteers participated in this research, 8 females and 4 males spanning all 4 secondary grade levels (8 underclassmen, 4 upperclassmen), 7 of whom were multilingual (Spanish-English, Polish-English, Bulgarian-English, and Filipino-English). Whether teachers or students, participants included only those who had experienced both in-person and remote learning during the COVID-19 pandemic. Let’s meet the student-participants: • Greg—multilingual honors freshman who enjoys sports; interested in STEM-related courses; older sibling graduated from the same high school; second child in family to attend an American college/ university.

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• Peter—freshman honors’ student who values his family’s Filipino cultural heritage but considers himself Americanized; avid sports fan; passionate about video gaming, computers, and STEM-related coursework. • Bobby—multilingual underclassman who is a gregarious communicator; avid reader with a penchant for historical and contemporary non-fiction; feels he is a good manager of digital device use during class. • Marcia—multilingual underclassman following in the footsteps of an older sibling who graduated from the same high school; “A” student across the board but thrives in humanities classes; considers herself a verbal-linguistic learner; plays high school team volleyball and is active in multiple clubs; acknowledged the adjustment from private elementary/middle school into a large public high school was challenging. • Jan—multilingual underclassman who identifies herself as a verbal-­ linguistic learner even though her PSAT-9 math score is among the highest at her school; avid reader who enjoys creative writing; heavily involved with extracurricular clubs and activities; attends Polish school on the weekends. • Cindy—multilingual freshman student who struggled academically first semester; expressed some frustration making the transition from an inner-city metropolitan middle school to a suburban high school; has general anxiety disorder and ADHD, which made “remote” learning stressful for her, especially since she had to care for younger siblings while her parents worked. • Laurie—English-speaking underclassman whose family has lived in the case site’s district for generations; highly involved with extracurricular sports and activities; her freshman English teacher recommended a level-change, moving Cindy to honors English between first and second semester; describes herself as a soft-spoken but eager participant. • Tracy—multilingual sophomore who ranks at the top of her class; takes all honors-level and AP (advanced placement) courses; standout athlete who broke swimming records as a freshman and ­sophomore; favorite classes are STEM-related; leading spokesperson for her school’s Women in STEM program. • Simone—all-honors junior student-athlete who enjoys writing; plans to take honors journalism as a senior; enjoys her part-time job as a park district counselor, which sparked her interest in eventually pur-

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suing an elementary education degree in college; family is fourth-­ generation American from the research site’s area. • Shirley—graduating honors senior who is a standout varsity athlete; accepted an athletic college scholarship during the spring semester of her senior year; active in her school’s Women in STEM program; plans to pursue a “hands on” career in technology. • Alice—graduating valedictorian with a full AP/honors class schedule; plans on pursuing a civil engineering degree at the University of Illinois Urbana-Champaign; multilingual; decorated all-conference and all-area multi-sport varsity athlete; talented public speaker who is active in STEM-related classes and clubs/activities. • Keith—quiet and industrious senior who took more AP-level classes over 4 years of high school than any other graduating senior; struggled with anxiety and social-emotional health at managing so many AP-level classes; ran cross-country and participated in STEM, Ecology, and Video Game Clubs; also participated on his school’s Scholastic Bowl Team. Next, here are our teacher-participants: • Ms. Johnson—vibrant and outspoken college prep and honors’ level math teacher (5 years of experience); strong advocate of digital technology when appropriately managed inside the classroom; practices yoga and meditation; coaches her school’s dance team. • Mr. Keating—recently tenured 4-year social studies teacher; structures classroom instruction around discussion and academic debate; prides himself on his strategic and often limited use of digital technology inside the classroom setting, getting his students to “unplug” and engage in meaningful face-to-face discussion; coaches volleyball and actively participates in a variety of school-related clubs and committees. • Mr. Holland—beloved 22-year veteran of the science department; shifting into the Industrial Technology department in order to teach engineering, woods, and construction; a successful head varsity cross-country coach, he has also served as an assistant coach for girls’ basketball; a strong advocate for limiting the use of personal digital devices at school in lieu of the exceptional “hands on” technology afforded to students inside classrooms on a daily basis at his work site; believes the only thing more important than education is family; enjoys reading, running, gardening, and grilling.

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Data collection followed an adaptation of Creswell’s (2015) progressive steps (Fig.  1.4). Transcripts from interviews served as the primary research for this book. Two rounds of 45–60 minutes recorded in-depth interviews with each participant provided over 30 hours of interview transcript data, coupled with individual handwritten interactive logs so participants could note type and frequency of digital distraction over the course of subsequent “in person” and “remote” instructional days. A formal research journal was also employed to help triangulate the collected data before analysis procedures were finalized (organization/preparation of data; close reading of data; coding of data; generating descriptions, patterns, and themes; furthering the development and support of identified patterns/themes; interpretation of data). Codes were grounded instead of priori since the research codes emerged from the collected data, and three levels of coding were used to establish the grounded coding process (initial/open coding, focused coding/category development, and axial/ thematic coding).

Fig. 1.4  Data analysis procedures chart, which highlights the steps used in this inquiry for coding

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Follow the Yellow Brick Road Digital distraction while learning continues to be a common classroom phenomenon, and it is starting to slip into primary grade levels, too. Not only are more schools committing to 1:1 integrated digital learning, but secondary schools continue to trailblaze the way since high school students have greater access to mobile technology both in and out of the school setting. All too often, educational stakeholders hold the assumption that secondary-level students are better equipped to handle technology as they transition to higher education and the workplace. Because the research for this book was collected during the COVID-19 pandemic, its significance is obvious since many schools across the world experienced operating in hybrid or fully remote instructional modes that increased the likelihood of digital distraction among students and teachers. This book is unique to the field of education because K-12 educational literature lacks saturation of research data pertaining to the coping and/or mitigating of digital distraction in 1:1 learning environments. Additionally, there is a major gap in the literature regarding digital distraction, its effects, and mitigation efforts across the secondary school level. The viewpoints and perspectives shared inside this book are unique as educational stakeholders around the world are still trying to mitigate ever increasing digital distraction in today’s post-COVID educational sphere. The following chapters are organized around the sub patterns, patterns, and themes that emerged from the primary and secondary guiding research questions (Chaps. 2, 3, 4, 5, and 6); in addition to an interpretation of these findings, these chapters will include interesting vignettes, anecdotes, and participant quotes that paint a compelling picture of this evolving phenomenon.

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Lodge, J. M., & Harrison, W. J. (2019). The role of attention in learning in the digital age. Yale Journal of Biology and Medicine, 92, 21–28. Mahiri, J. (2011). New literacies need new learning. In Digital tools in urban schools: Mediating a remix of learning (pp. 1–24). University of Michigan Press. http://www.jstor.org/stable/j.ctv65swfn.4 Marks, H.  M. (2000). Student engagement in instructional activity: Patterns in the elementary, middle, and high school years. American Educational Research Journal, 37, 153–184. Marshall, S. (2007). Engagement theory, WebCT, and academic writing in Australia. International Journal of Education and Development using Information and Communication Technology (IJEDICT), 3(2), 109–115. Martens, B. K., Bradley, T. A., & Eckert, T. L. (1997). Effects of reinforcement history and instructions on the persistence of student engagement. Journal of Applied Behavior Analysis, 30, 569–572. Maxwell, S. E. (2004). The Persistence of Underpowered Studies in Psychological Research: Causes, Consequences, and Remedies. Psychological Methods, 9(2), 147–163. https://doi.org/10.1037/1082-­989X.9.2.147 Merriam, S., & Tisdell, E. (2016). Qualitative research: A guide to design and implementation. Jossey-Bass. Miliszewska, I., & Horwood, J. (2006). Engagement theory: A framework for supporting cultural differences in transnational education. In ACM SIGCSE Bulletin. https://www.researchgate.net/publication/228786927. https:// doi.org/10.1145/1124706.1121392 Minges, K. E., Owen, N., Salmon, J., Chao, A., Dunstan, D. W., & Whittemore, R. (2015). Reducing youth screen time: Qualitative metasynthesis of findings on barriers and facilitators. Health Psychology, 34(4), 381–397. https://doi. org/10.1037/hea0000172 Muenks, K., Wigfield, A., Yang, J. S., & O’Neal, C. R. (2017). How true is grit? Assessing its relations to high school and college students’ personality characteristics, self-regulation, engagement, and achievement. Journal of Educational Psychology, 109(5), 599–620. https://doi.org/10.1037/mot0000076 Nelson, J. R., & Colvin, G. (1996). Designing supportive school environments. Special Services in the Schools, 11, 169–186. https://doi.org/10.1300/ J008v11n01_05 Newmann, F. M. (Ed.). (1992). Student engagement and achievement in American secondary schools. Teachers College Press Columbia University. Pettijohn, T. F., Frazier, E., Rieser, E., Vaughn, N., & Hupp-Wilds, B. (2015). Classroom texting in college students. College Student Journal, 49(4), 513–516. https://doi.org/10.1016/j.chb.2014.03.045 Pope, C., Mays, N., & Popay, J. (2007). Synthesizing qualitative and quantitative health research: A guide to methods. Open University Press.

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Reeve, J., Jang, H., Carrell, D., Jeon, S., & Barch, J. (2004). Enhancing students’ engagement by increasing teachers’ autonomy support. Motivation and Emotion, 28, 147–169. Seemiller, C. (2017). Curbing digital distractions in the classroom. Contemporary Educational Technology, 8(3), 214–231. https://doi.org/10.30935/ cedtech/6197 Shernoff, D. J., & Hoogstra, L. (2001). Continuing motivation beyond the high school classroom. New Directions in Child and Adolescent Development, 93, 73–87. Shernoff, D.  J., Csikszentmihalyi, M., Schneider, B., & Shernoff, E.  S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158–176. https://doi.org/10.1521/ scpq.18.2.158.21860 Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100, 765–781. https://doi.org/10.1037/a0012840 Skinner, E.  A., Kindermann, T.  A., Connell, J.  P., & Wellborn, J.  G. (2009a). Organizational constructs in the dynamics of motivational development. In K.  Wentzel & A.  Wigfield (Eds.), Handbook of motivation at school (pp. 223–245). Lawrence Erlbaum. Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009b). A motivational perspective on engagement and disaffection: Conceptualization and assessment of children’s behavioral and emotional participation in academic activities in the classroom. Educational and Psychological Measurement, 69, 493–525. https:// doi.org/10.1177/0013164408323233 Smith, M. J. (2008). Disciplinary perspectives linked to middle range theory. In M. J. Smith & P. R. Liehr (Eds.), Middle range theory for nursing (2nd ed.). Springer Publishing Company. Stake, R. E. (1995). The art of case study research. SAGE. Stodolsky, S. S. (1988). The subject matters: Classroom activity in math and social studies. University of Chicago Press. Vibert, A.  B., & Shields, C. (2003). Approaches to student engagement: Does ideology matter? McGill Journal of Education, 38(2), 221–240. Wang, Z., Bergin, C., & Bergin, D. A. (2014). Measuring engagement in fourth to twelfth grade classrooms: The classroom engagement inventory. School Psychology Quarterly, 29(4), 517–535. https://doi.org/10.1037/spq0000050 Yair, G. (2000). Educational battlefields in America: The tug-of-war over students’ engagement with instruction. Sociology of Education, 73, 247–269. Yin, R. K. (1994). Case study research: Design and methods. SAGE. Yin, R. K. (2003). Case study research, design and methods (3rd ed.). SAGE. Yin, R. K. (2014). Case study research (5th ed.). SAGE.

CHAPTER 2

How Do Students and Teachers Define Digital Distraction in School?

Abstract  Since the inception of this book was a knowledge pursuit, trying to understand better the definition of digital distraction from two groups of key stakeholders, students and teachers, was a significant undertaking. Because the majority of this book’s research stemmed from non-­traditional learning environments like remote settings and in-person settings that tethered remote students to the classroom through synchronous videoconferencing instruction, never-before findings over learning focus and engagement shaped participants’ perspectives over what constitutes digital distraction when learning. Formulating a shared definition of digital distraction among stakeholders will help school districts and parents to understand the why, so foundational management practices can better become the norm in digital policy development and classroom management strategy. Keywords  Digital distraction • Cell phones • Google Chromebooks • Covid-19 • In-person learning • Remote learning • Hybrid learning • Engagement • Focus • Time-management Distraction. Loss of focus and engagement. Many feel as if this has become a contemporary plague of sorts because whether you are working on site or from home, it has become a contagion across our post-COVID world. Some feel the gateway to digital distraction is self-imposed, like an © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. C. Schuett, Beyond Digital Distraction, Digital Education and Learning, https://doi.org/10.1007/978-3-031-53215-3_2

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addiction. Unfortunately, addictions can escalate into terminal illnesses if allowed. Just like biological sickness can quickly grow through incubation and the spreading of symptoms between the infected, digital distraction increases exponentially among the masses as conscious and subconscious digital group-think, especially inside social arenas like schools, occurs. Students and teachers defined digital distraction as a loss of focus and engagement for non-academic purposes during “in person” and “remote” learning on personal and school-issued mobile digital technology. These same participants identified boredom, multitasking, entertainment, and social media as general reasons for digitally distracted behavior, which caused student struggles with participation and time management during remote learning, and breaks in focus and intentional disengagement from collaborative activities during in-person learning. Some of these non-­ academic purposes included communicating with family and friends via texting, checking social media sites like Instagram, Snapchat, and Tik Tok, and accessing entertainment like music, video games, and movies. Some educators and parents may not even realize how popular communication with family via mobile technology is with students. Over 36 open codes emerged from this sub-pattern, and each student and teacher participant mentioned something related to this particular sub-pattern over the course of both interviews. Social pressures like FOMO, or the “fear of missing out” on something (Fewkes & McCabe, 2012), likely influenced participants’ decisions for communication with family and friends over digital media during academic learning time. During the first round of interviews for this research project, a student acknowledged that cellphone use had the potential to affect attention and focus during school for non-academic communication with family and friends, but it personally depended on the complexity and importance of the at-hand academic task. “And if I have a friend texting me, and if I’m doing a test, I’ll put it aside. But if it’s after I’ve finished my work, I’ll check my texts or snap” (Cindy, Interview 1). Another student participant noted school-issued Google Chromebooks and the school-mandated online platform (Google Meet) used for synchronous learning sessions, too. So, I believe they probably have their Chromebooks on for their Google Meet with the teacher and their cameras off. And then there’s this girl in my accounting class, and she’ll actually be Face Timing her other friend while on the Google Meet with her class. So, I definitely think they’re on FaceTime or talking to each other on a gaming set. (Shirley, Interview 1)

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This insistence toward students’ misuse of school-issued technology for non-academic communication during class was a common thread shared by both students and teachers alike. But this, for all intents and purposes, is just the tip of the iceberg. Another student discussed in his definition of digital distraction how cell phone use during class was often triggered by an urge to respond quickly to non-academic messages sent to friends. In addition, he mentioned how these phone distractions often spill outside of the classroom into the hall and other parts of the school building. When it comes to mobile technology, I mainly use it for either doing homework or communicating with my friends and family. But besides that, I’d also be talking with friends, sometimes, when they text me or email me during class, and I have the urge to respond immediately. Or you know, trying to sneak the phone in during class or just outside in the hallway, either texting friends or sifting through social media. (Keith, Interview 1)

Keith’s comments regarding digital distraction’s potential for extending into other parts of the school building should be an important takeaway for anyone reading this book. Stakeholders need to realize that digital distraction’s effect on learning focus and engagement often occurs before a student even crosses the threshold into any given classroom. These same teachers, school leaders, and parents must stop kidding themselves into thinking the base definition of digital distraction is organically recreated each and every day inside certain teachers’ specific classrooms. Oftentimes, the distraction is simply culminating and reinforcing itself inside the classroom setting. Students were not the only participants who identified digital devices being used for non-academic communication with family and friends as a basic tenet of digital distraction’s definition. One teacher disclosed the ongoing issue of students using digital technology during class for non-academic socializing when discussing her definition of digital distraction. “I’ve got kids on different Google Meets during class with their friends while they’re gaming, so gaming on different Google Meets during class” (Ms. Johnson, Interview 1). Another teacher reinforced this insistence of using digital devices during class to communicate with friends and family. So digital distraction could even be you chatting with your buddy at home to get help on a lab or something like that. If you’re not laser-focused on what’s going on around you, and you’re talking with your buddy, then when you come back,

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you’re like, “What did I just miss?” That’s digital distraction. (Mr. Holland, Interview 1)

Mr. Holland’s response provides insight into the impact of digital distraction on focus and engagement during learning. His definition reminds us that even a momentary lapse in concentration can affect a student’s ability to keep up with in-class instruction. During the second round of interviews, a student reiterated that classmates communicating with family and friends during designated class time continued to be an ongoing problem and an important aspect of digital distraction’s definition. I definitely think it impacts it in a pretty significant way. For example, if a student in the classroom is either watching YouTube or on their phone texting friends and all that, they are basically tuning into the entire outer world and not focused on the activity they’re doing in class. (Keith, Interview 2)

Keith, like many other students, insisted that social media and non-­ academic communication with friends diverted students’ attention to non-academic pursuits. Likewise, Mr. Holland reinforced his earlier stance in the following quote, but this one includes parental undertones that relate to student loss of attention and focus caused by non-academic communication with friends during remote learning. In addition, he mentioned how learner fatigue compounded due to digital distraction, which serves as an important tangential sub-definition of digital distraction. Okay, we’re coming in here to learn, right? We’re not coming in here to eat dinner or hang out in our bedrooms having dance parties. But then when they’re doing their homework, their phone beeps, that’s the first thing. “Oh, I gotta pick it up and see who’s texting me.” So, their phone beeps again, so they stop the homework, then they start it again, then stop, start, stop, start, stop. There’s no longevity to their learning pathway, which makes them fatigued, especially when they try to read longer passages. (Mr. Holland, Interview 2)

This longevity to their learning is a significant data point since focus and concentration during learning influences engagement, which in turn affects cognitive functions like knowledge retention and learning transfer. The compulsion of checking social media was another common thread among both students and teachers when sharing their definitions of digital distraction. Additionally, students disclosed how non-academic

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communication with friends and family, usually for entertainment, also occurs through social media. One underclass student said, “Normally, it’s probably either answering a text or checking social media. Like Tik Tok has been a big thing; you’re always going to want to scroll through its videos, or on Snapchat you always send stories to people who send you stories” (Greg, Interview 1). Even as an underclassman, Greg already recognized social media’s influence on his definition of digital distraction. Another student identified the impact of social media when communicating with friends and family for non-academic purposes in his definition of digital distraction. This particular student went so far as to mention the urge to check social media even when it was for purposeless reasons. I use a lot of social media, and I keep up with other classmates and friends on social media to see what they are up to and what they post on social media as well. Usually, I’m just checking up on social media, checking out internet drama and pointless things. (Peter, Interview 1)

Similarly, a different student when referencing social media as part of his definition, also acknowledged witnessing other students becoming distracted on social media apps during class, too. “A lot of the time, I just ‘chat up’ friends…For me, I’m probably on social media, and I’m assuming it’s the same for others since I’ve seen a lot of other people be on social media, too” (Bobby, Interview 1). This realization that students are cognizant of others actively choosing to lose focus during class for non-academic communication through texting and social media is an important takeaway for the readers of this book. When sharing her definition of digital distraction, Cindy specifically referenced Snapchat as a popular social media app for students to become distracted on when learning. Snapchat’s instant messaging capabilities are similar to texting, so it serves as a popular communication tool for teens. I say iPhones and social media in general. My mom just let me get Snapchat when I graduated from junior high because she knew that it was a distraction. She knew she could trust me, but she didn’t trust other people on Snapchat. I totally agree with her that it’s a distraction. I get distracted by it a lot. (Cindy, Interview 1)

Snapchat and other social media apps provide communicative immediacy for their users, which could be difficult for adults, let alone adolescents, to

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manage, especially during class. Working social media applications into the ever-evolving definition of digital distraction needs to become a norm among educational stakeholders, not only pertaining to classroom management but also regarding curriculum and development, too. A couple of other students suggested that communication with friends through social media apps is on a par with texting, but social media provides a steady feed with images that texting does not necessarily do. Again, when students shared their definitions of digital distraction during times of instruction, they preferred using social media over texting with family and friends. I feel like the number one thing that I use it for is to communicate with my friends and family through social media apps and other forms like text messages. Usually, I’m communicating with my friends through some sort of social media app, looking at their feed and pictures. Mostly communicating. (Tracy, Interview 1)

Tracy’s comments indicate that her primary reason for checking and using devices during class was for non-academic correspondence with friends and family, which reinforces the same patterns already established earlier in this chapter. Three different students also mentioned apps like Snapchat and Tik Tok, stating how they use these social media applications for nonacademic activities during class time. Again, these particular social media apps provide a platform for users to communicate with others while simultaneously engaging in other online content. So, I use apps like Snapchat to communicate with friends or for messaging family, or like Tik Tok as a form of entertainment to see what dances are popular. When I’m on a digital device, even during learning, I’m usually getting Snapchats from friends to where I’m responding back to them. (Alice, Interview 1)

Alice’s comments provide an interesting take away because social media apps often invoke responses among users. A preconceived notion among teachers is that social media is merely used by students for entertainment. Educational stakeholders must remember that social media is often used as a “go to” communicative channel among adolescents because it’s not just used for entertainment. One student mentioned how social media apps like Tik Tok are really easy for teens and young students to navigate, which causes users to lose

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track of time when engaged on them. This issue creates a time warp of sorts for students’ learning focus when engaged on apps like Tik Tok as users become “lost in space.” I’d say definitely their phone would be one of the main things they’re using, specifically for social media and all that stuff. I have seen multiple cases where my friends have told me that during normal classes, they just have their cameras shut off and they are scrolling through Tik Tok the entire time. So, the phone and the social media aspect of using your phone is definitely the number one distraction students have when learning remotely from home. (Keith, Interview 1)

Students and teachers both agree that cell phones remain the most popular device for students to become digitally distracted on. “So, when you see the kids being digitally distracted inside the brick-and-mortar school, it’s normally phones, and they’re spending time on Snapchat, Instagram, and texting” (Ms. Johnson, Interview 1). Another teacher, Mr. Keating, also noted the commonness of the social media diversion. “If I go to the most common, which is kids on their phones sending a message to someone by utilizing either texting or social media, that is the primary way they’re distracted” (Interview 1). Both of these educators agree on social media’s influence on focus and academic engagement at school, illustrating the link between social media and non-academic communication among students during class time. During the second round of interviews, more students than teacher participants noted the continuance of social media’s influence on attention and focus during learning, especially when in remote learning. Interestingly, half of these students explicitly mentioned social media more during the second round of interviews than during the first. I don’t think it’s really changed. It’s just because more people just get distracted by the freedom to go onto social media when they are remote more than at school. Just being able to check your phone and social media. Social media is very enticing when it comes to digital distraction. People are getting distracted, you know, because of its addictive qualities. There are certain elements that make it difficult to get off some sites like Instagram. All the time, you get ­recommendations and things you interact with on Instagram, and it leads over into other things. For instance, if you interact with a certain post about let’s say basketball, it’ll continue to show basketball on your feed, and it gets addictive. And that happens with all social media apps as well. After interacting with one thing in your

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feed, like one post, it leads to another and keeps going on and on with whatever the topic is, like referring back to basketball videos, so then you lose your focus on whatever the main learning topic is because you’ve distracted yourself off of basketball videos. I think personally owned devices are more distracting because of their access to social media, too. (Peter, Interview 2)

Peter’s comments not only capture the break in learning focus caused from students interacting with social media, but he also describes the addictive nature of falling into the social media rabbit hole. Social media can become a viral loop that can digitally distract users for extended periods. A thought-provoking insight provided by Jan during the second interview specifically mentioned a social media app that, according to her, does not disclose time when accessing videos in the same way most other social media apps do. Subsequently, Jan also referenced the difficulty in breaking social media distraction when one loses track of time. “So, it shows you things you’re interested in. TikTok actually gets rid of time, so you don’t know what the time is when you’re on TikTok, which will cause you to spend even more time on it. You literally lose track of time” (Interview 2). Jan’s insights strengthen the concern educational stakeholders should have pertaining to students falling victim to the viral loop by continual scrolling and sharing of online content, especially during learning. Social media is something educational stakeholders need to consider when conveying their definition of digital distraction to students and parents. During the second round of interviewing, Mr. Keating even acknowledged the pleasure users feel when becoming digitally distracted on certain social media apps during learning. I’d have to sit and doodle or whatever I needed to do, and it’s like, well, I’ll just check Twitter really quickly, and then all of a sudden, I’m out. And again, that doesn’t mean staring at a piece of paper until you’re done. But I think a lot of students use digital distraction to lie and satiate themselves. Like I am having a hard time in my brain right now, so I want to do something that is pleasurable, and something that is pleasurable is checking Instagram. (Mr. Keating, Interview 2)

Mr. Keating also felt that the pleasure from distracting oneself on a device for social media became more enticing when learning became more difficult, which makes sense. The digital distraction social media offers acts like

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digital dopamine for students and teachers alike, which has no place when an educational stakeholder is attempting to “hold one’s thinking” inside an instructional learning cycle. Using entertainment was another important element that impacted both students and teachers’ explanation of loss of engagement caused by digital distraction when sharing their definition of this phenomenon. Oftentimes, non-academic activities like entertainment (i.e., music, video games, movies) divert attention and focus from learning. This emerging trend connected as much with students as it did with teachers, particularly when learning was occurring outside the brick-and-mortar classroom setting during remote learning. Boredom, a well-documented phenomenon among students (Buxton, 1973; Csikszentmihalyi & Larson, 1984; Jackson, 1968; Mitchell, 1993), further exacerbated this diversion from learning for more pleasurable activities like social media and gaming. Subsequently, boredom should be included in our evolving definition of digital distraction inside the twenty-first century classroom. During both rounds of interviewing, Peter disclosed his affinity for video games and streaming TV apps. He also identified the mobility associated with some video games, too, which makes our evolving definition of digital distraction even more compelling. And like with digital tech, I also use video games, and I play some mobile games as well. But when I’m not on the PlayStation, I use my phone. It’s a bunch of platformer games like Geometry Dash. My classmates would probably either be watching TV or watching favorite shows or whatnot on Netflix and Hulu. (Peter, Interview 1)

Again, Peter suggests that other students share his affinity for gaming and popular entertainment apps. A different student mentioned the variety of larger digital devices one can access at home. Due to remote learning during the pandemic, this is something many students and teachers had to navigate in real time while learning. “Then at home, I feel like it’s going to be a lot of your bigger devices like video-gaming, TV, iPad, watching movies during class, etc.” (Simone, Interview 1). Stakeholders need to take note of this digital “at home” variety when considering the definition of digital distraction, especially since managing student access to these devices is becoming even more difficult for teachers and parents as hybrid methods of instruction continue to be used inside classrooms across the globe.

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Another student mentioned the difficulty in separating oneself from digital entertainment while learning, especially since an individual could use certain non-traditional communication channels like gaming consoles for socialization purposes while learning. She felt that mobile entertainment could be a contributing factor and should be included in the definition of digital distraction. Actually getting off task with your work when you’re looking down at your phone. Like the temptation to see the news, what’s happening now, is there a new video posted, what’s going on in the world. But mostly, it’s just talking to each other on a gaming set. And at home, I’ll definitely be more distracted. If my camera’s on, I have my AirPods in and I’m listening to music, so that obviously keeps me distracted, especially if I like a song. (Shirley, Interview 1)

Shirley also expressed that the management of mobile entertainment while learning remotely was more difficult as she often gave into the temptation of becoming digitally distracted for amusement and pleasure. A different student also reinforced online entertainment as a means of digital distraction during class. She stated how some students played video games on their phones during instruction, especially depending on what was being taught in class. Popular mainstream entertainment continues to be a recurrent underlying catalyst to distraction on digital devices. “Or like TikTok as a form of entertainment to see what dances are popular. Sometimes, I play games online on my phone as well. It depends on what’s going on in class” (Alice, Interview 1). Keith shared an anecdotal snapshot of what he often witnessed while learning at school during the COVID-19 pandemic. Specifically, he mentioned seeing students watching videos for entertainment purposes in the middle of class. “When it comes to ‘at school’ learning, one of the main things that I’ve seen is students on their Chromebooks, hopping onto YouTube and watching videos in class” (Keith, Interview 1). This witnessed behavior was a common observation among study participants. During the second round of interviews, Cindy also stated how the struggle of distraction for entertainment on cell phones increased, saying how the hybrid-learning situation caused by the pandemic increasingly made digital distraction more of a personal issue with learning than prior to the pandemic. I’ve always had a problem when playing video games, but never like on my phone because I wasn’t on my phone as much or like on digital devices as much

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as I am now. I’d say it’s a difficulty because sometimes students learn better that way, depending on what they’re doing, like how I said last time with music. And then some students just use it as a digital distraction don’t actually focus on the work or assignments. (Cindy, Interview 2)

The pandemic compounded the difficulty many students already faced with managing their digital devices during class, especially with gaming. Similarly, other students repeated the notion that gaming is a bigger problem during remote learning because of digital device proximity and freedom of use, two more variables stakeholders should consider when defining digital distraction when learning. …I think it is a bigger problem with students at home because they don’t have anyone telling them to get off their phone. And they also have more devices to use because they have their TVs and their PlayStation and all this other technology right there. (Simone, Interview 2)

Simone’s comments expressed how the number of available digital devices at home could become problematic for some, especially students. Another participant enthusiastically repeated the same thing, stating the struggle students have separating digital device use for entertainment, especially during remote asynchronous work since nobody is usually supervising them, should be factored into digital distraction’s definition. I think there is more distraction at home because the teacher is not watching you, and you’re not engaging with others in the classroom because you’re usually home alone. So, then they completely move their device alongside themselves, and they don’t even have to stare at the screen because nobody’s watching them. Meanwhile, the device is just providing us students with entertainment on our free time, or that’s what it’s meant for, but we’re the ones deciding to use extra time that isn’t really “extra time” because it’s supposed to be for learning. And we’re using that time instead to focus on entertaining ourselves instead of learning. (Alice, Interview 2)

This lack of supervision could also be a contributing factor to students’ struggle with time-management and on-task academic behavior, which are two more tangential variables stakeholders should consider when defining twenty-first century digital distraction inside the classroom, whether the classroom is in person, virtual, or hybrid. Another student stated during his second interview that the type of digital distraction, especially when it

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is for entertainment, affects learning more than other types of digital distraction. I mean it depends on the sort of digital distraction because, for example, if you’re playing video games in class or watching TV, of course it’s going to distract you. I definitely think it impacts it in a pretty significant way. For example, if a student in the classroom is either watching YouTube or on their phone texting friends, they are basically tuning into the entire outer world. (Keith, Interview 2)

Since entertainment on digital devices provides immediate gratification, students have a tough time separating themselves from it, particularly when learning is not engaging. Being cognizant and helping students better understand the effects of this immediate gratification on their learning focus and engagement should be included in the development of our definition of twenty-first century digital distraction. Any educator worth their salt readily admits that channeling student focus and engagement inside the classroom is no easy task. Additionally, this realization is no epiphany for any educational stakeholder. Volumes of professional development literature attempting to forecast the why and how of engagement lapses decorate the office shelves of many an educational administrator, likely gathering as much dust as many of our framed diplomas. Not to mention the amount of abandoned stapled and collated worksheets hiding in the corners of classrooms, packets illustrating strategies educational specialists like instructional coaches, consultants, and department chairs have cooked up to combat disengagement during learning, theoretical “cure-alls” often left untested from those in the daily trenches because they’re too busy trying to survive. Not to take anything away from former or retired educators because they already earned their stripes battling things like whoopie cushions, handwritten student notes folded into origami, disposable cameras attached to keychains, and vibrating pagers, because at that point in time, these were all distractions to learning at school. But combating the cell phone distraction, especially post-COVID, is the single most important endeavor educators and parents have ever faced when trying to maintain focus and engagement during learning. Nothing else compares. Remote distance learning was a thing prior to COVID-19. Anecdotally speaking, I managed a modern language class during my first couple years

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of teaching, and today’s distance learning is far better equipped to help students learn than previous versions did. Twenty years ago, we were still showing VHS tapes and mailing homework to university programs that snail-mailed feedback back to students and managing instructors. Hence, the immediacy of distance learning has improved with the internet and face-to-face communication platforms like Google Meet and Zoom. But just because virtual distance learning has become more prevalent by no means proves that it is more effective, or even more popular among learners. Plus, we need to remember that even though remote and/or hybrid learning may increase access to learning through non-traditional platforms, its ease of accessibility with limited accountability is concerning, especially with our current “We gotta have this now” societal expectation. Immediacy, particularly when motivated by monetary profit, should not be the foundational benchmark for any educational learning strategy. There is no “one size fits all” learning approach, but any attempt to either rush or monetarily capitalize on the learning process through digitizing it merely for immediacy is criminal. Not only does remote learning increase the chances of behavioral problems because of the non-traditional instructional environment, especially with increased access to other digital media and decreased supervision, but the distractions it presents are contagious, often negatively affecting others. An interesting discovery this book posits is the realization that in-person learning often suffers because students bring their distracted behavior(s) with them to class (i.e., texting in the hallway, listening to music on earbuds during passing period, checking social media between classes). The thresholds of classroom doorways aren’t secret passageways into another digital-free dimension. Just because a school district displays posters on the walls and floor that say, “Cross the line, it’s learning time,” in no way eradicates or even minimizes student digital choice, especially when addictions have already been established (Fig. 2.1). We’ve been taught from an early age that actions often speak louder than words, and school districts’ open-ended advertisements aren’t enough. It’s time for teachers, administrators, and parents to begin explicitly teaching the definition and negative impacts of digital distraction on learning—it’s time school districts and states mandate that digital distraction becomes part of the required digital literacy curriculum.

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Fig. 2.1  This is an in-school poster advertising mitigation efforts against digital distraction

References Buxton, C. (1973). Adolescents in schools. Yale University Press. Csikszentmihalyi, M., & Larson, R. (1984). Being adolescent. Basic Books. Fewkes, A. M., & McCabe, M. (2012). Facebook: Learning tool or distraction. Journal of Digital Learning in Teacher Education, 28(3), 92–98. Jackson, P. W. (1968). Life in classrooms. Holt. Mitchell, M. (1993). Situational interest: Its multifaceted structure in the secondary school mathematics classroom. Journal of Educational Psychology, 85(3), 424–436. https://doi.org/10.1037/0022-­0663.85.3.424

CHAPTER 3

How Do Students and Teachers See Digital Distraction in School?

Abstract  Perceived distractions might not always directly relate to actual distractions, so this chapter delves deeper into what students and teachers initially witnessed regarding digital distraction inside these unique pandemic learning environments. Subsequently, both students and teachers saw digital distraction through their own individual lenses (i.e., actions and choices), as well as the behaviors of others. Some of these distractions were witnessed in person, while others were seen through digital mediums like videoconferencing (e.g., Google Meet and Zoom). In addition, unpacking participants’ shared perspectives about how they see digital distraction in school gives readers a variety of generalizable anecdotal evidence that can and should be discussed among school leaders when developing digital policies at school, and among teachers when discussing how best to modify classroom management strategies and techniques for minimizing digital distraction inside their classrooms during professional development sessions (i.e., weekly in-service meetings, district institute day breakout sessions, etc.). Keywords  Digital distraction • Cell phones • Google Chromebook • 1:1 Device • Electronic notifications • Mobile device accessibility • Attention • Focus • Engagement • Time-management • Non-academic communication • Digital entertainment • Remote learning • Non-­

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. C. Schuett, Beyond Digital Distraction, Digital Education and Learning, https://doi.org/10.1007/978-3-031-53215-3_3

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digital distraction • Lack of supervision • Digital variety • Artificial intelligence (AI) • Covid-19 • G-chat • Google Docs • Google Meet • Web 2.0 What you see is always “the truth,” right? Like what you see is what you get. So, readers, especially if they are academics living in the world of education, are seeing exactly the same form(s) of digital distraction participants in this study saw and experienced, or is that just another educational pipe dream? Excessive hyperbole? Maybe, but you get the point—different geographical locations and varying socio-economic levels present the potential for a variance of perspectives regarding how teachers and students see digital distraction in the twenty-first century. With this being said, the test site for this book’s findings was socio-economically diverse and populated, too. These two characteristics give this book’s findings a higher degree of generalizability, so stakeholders might be able to draw similar conclusions throughout a wider array of educational contexts. This may not be an epiphany for anyone reading this book, but students and teachers both picked cell phones as the most common device seen for students to become digitally distracted on, whether learning was happening in person or remotely. Cell phone accessibility, coupled with its ease of concealment, makes this choice for students a “no brainer.” Interestingly, as much as teachers want to see cell phones out of the hands of students, especially inside the classroom, many educators do not want to be held liable for policing the devices themselves. Teachers mentioned the fears of privacy issues, coupled with the potential cost of accidental damage to a student’s personal electronic property. Subsequently, teachers do not want to see these personal mobile devices, but at the same time they are not willing to confiscate them, which fosters the potential for relationship-fallout between school administrators and teachers. Case in point, if school leadership does not mandate specific mobile device protocol by leaving it up to the teachers, students and teachers alike must navigate mixed-signals inside school on a daily basis. When this happens, frustration builds because what is allowable electronic etiquette in one area or section of the school may not be acceptable in another. What might be of more serious interest for readers of this book is that teachers selected school-issued Google Chromebooks as the device most teachers become digitally distracted on during class, citing their increased instructional use and the ease by which a teacher could hide their

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distraction on a mandated school-issued device. As early as 2011, US school districts started the process of arming students with 1:1 devices— laptops, Chromebooks, Macs, iPads, and tablets. Up to this point, most schools operated with computer labs or transitory rolling computer cabinets. Granted, some students already owned personal 1:1 devices, which some chose to bring with them to school either regularly or occasionally. In addition, many districts across the country had already committed this 1:1 initiative for administration, faculty, and staff as schools continued the transition from handwritten gradebooks to mandated electronic versions. But when school districts armed students with similar 1:1 digital technology, a metaphorical war of unparalleled degree was waged on students’ focus and engagement inside school. Teachers mentioned students’ conditioned responses to mobile devices, stating how students even check their cell phones inside classrooms with zero connectivity. Teachers also discussed the irony behind school-­ mandated 1:1 technology, citing how the nature of the Google Chromebook for instructional use is a distraction in itself for both students and teachers. Participants felt that personal cell phones and school-issued Google Chromebooks were the two most likely mobile digital devices which students and teachers became distracted on during in-person and remote learning. Participants shared a variety of other digital devices, but the accessibility, mobility, and freedom of use for both cell phones and Chromebooks made these two devices the most prevalent among students and teachers. The primary source data for this inquiry stemmed from 2 45-minute, in-depth semi-structured interviews. From this interview data, 182 data chunks unanimously supported the cell phone as the primary digital device stakeholders became distracted with when learning from home. For in-­ person learning, student-participants again unanimously picked the cell phone. However, teachers identified the school-issued Google Chromebook as the device students became most digitally distracted on during learning. This challenged the literature since the cell phone was the most popular device for distraction during class. Teachers who participated in the case study stated that since Chromebooks were a mandated requirement during the school’s COVID-19 hybrid schedule, students were required to use their Chromebooks exclusively for class, whether class was in person or remote. When students were physically at school, Chromebooks were used exclusively, so students were more inclined to

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hide their distraction on the Chromebook itself. Some teachers, though, also allowed cell phones to be accessible to students during class. Granted, the number of teacher participants was only one-fourth the size of the student participant group for this case study, so if more teachers had participated, teacher findings may have been different. When combining both student and teacher findings, the cellphone was still the clear winner for the most likely device to see students becoming distracted on during class, which supports the literature (Berdik, 2018; Campbell, 2006; Cheong et al., 2016; Lawson & Henderson, 2015; McCoy, 2013; Pettijohn et al., 2015; Redner et  al., 2019; Roberts, 2016; Rosen et  al., 2013; Seemiller, 2017). Mr. Keating, a social studies teacher, even mentioned how conditioned students had become about checking their phones during class. He stated how some classrooms at this school have zero cell phone connectivity, but that seldom stopped students from occasionally checking their phones. Regarding Chromebooks, Mr. Keating and another teacher, Mr. Holland, a seasoned science instructor, both indicated the irony behind a school-­ issued digital device contributing to digital distraction during class. Mr. Keating said, “But then when they’re on their Chromebook because I’ve told them to look at something, they’ll get distracted as well.” Mr. Holland’s comments about the entrenched irony of a school-issued device contributing to digital distraction were blunt, “I even think Chromebooks are distractions, which again, I disagree with how we do a lot of our stuff that we do.” These findings indicate the frustration some teachers felt in managing device usage inside their classrooms, whether the device was school-issued or personal. During the first interview, a student said that cell phone notifications, coupled with cell phone accessibility, especially during remote learning, all contributed to increased digital distraction during learning. This student even identified seeing non-classroom spaces at school where students struggle with digital distraction on a daily basis. I see digital distraction as any type of electronic device that you can get your hands on. It could be any type, like your phone. Like you’d get a notification, and you’re going to want to check it. I’d say the top one would be phones because you could practically do anything on it. It’s like a mini-computer, so you can text people and look at different things. I see students using them, for example inside classrooms. Someone will have their phone under their desk or in their bag or behind their computer and out in the hallways. People are always looking

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down at their phones, which causes them to bump into others in the hallway. And if they aren’t allowed to have their phones out during class, they’ll probably find a reason to get out of class, like go out into the hallway or the bathroom, just to check their phone, which seems like more of a distraction. They will sometimes keep it behind their Chromebooks, but they put their phones upside down, so it looks like they are looking at their Chromebooks instead. And then they also sometimes put it in their bags and pretend they’re looking through their bag when they’re actually on their phones. I think during remote learning, it’s much easier to be distracted most of the time. In some classes, even though it’s a policy to have your camera on, people still don’t. They just have their Chromebook open on the Google Meet, and they’re on their phone. In school, I see myself getting distracted a lot because I always have my phone, not on but out. It’s either in my pocket or next to me on the desk, so when I see the screen light up, I want to check it. I think it’s kind of like you’re always going to be checking your phone. Most of the time I get distracted by seeing that the notification light turns on from my phone. I’ve also seen in a lot of situations where someone will be in their learning group, and there is probably a member who is just sitting on their phone versus doing their part of the work. (Greg, Interview 1)

According to Greg’s observations, cell phones are easy devices for students to hide during in-person learning and impossible for teachers to supervise when students are learning online. Interestingly, a different student also mentioned how cell phone distraction at school spills over into the hallways and other common areas for both students and teachers. Her comments illustrate the frustration many students feel concerning this. “At school, I see phones in the hallway, lunchroom, and even in the locker room because sometimes in the hallway people don’t like to talk to other people, so they’ll go on their phones right away. Sometimes in class, your eyes wander, and you even see the teacher on their phone” (Shirley, Interview 1). This widespread accessibility and proximity of mobile phones at school compounds stress for those who are trying to maintain their academic focus and learning engagement. Another student mentioned the frequency of seeing phone notifications, stating how they are a gateway to digital distraction during learning. But I mainly get distracted if I get a notification on my phone. I like to check it a lot, and then, sometimes I get carried away. I just don’t listen to my teachers; I get distracted a lot. To me, seeing digital distraction is like not focusing on priorities such as schoolwork and procrastinating and stuff due to getting distracted and carried away by using your phone. Sometimes, students ask to go to

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the bathroom, and it’ll take them quite a while to come back. And that’s when I’m assuming they’re checking their phones. It’s easier for me to get distracted because I keep my phone on the desk, and I have the ringer on. Every time I get a notification, I tend to check. I text my friends in the middle of class as well. (Peter, Interview 1)

One student explicitly used the words focus and engaged when seeing cell phone distraction during class. She also discussed the nature of phone notifications, especially since they could occur as audible, tactile, or visual distractions. Digital distraction looks like getting messages or notifications during class on your phone. Your focus is off of what’s going on in class to where you’re not engaged on what you’re learning, and you’re distracted by a message you’re getting or things that are popping up on your phone. Most often, your cellular device is what gets you distracted. When you’re sitting in class, and when you see your phone buzz, you automatically want to look at it. It’s also just normal seeing people walking down the hallways on their phones. (Alice, Interview 1)

Even these high school students note the frequency of checking their phones during school. In addition, many student-participants continue to note how often students excuse themselves from the classroom just in order to engage with their phones in other places throughout the school building, like restrooms, hallways, and other common areas. Several other students also mentioned routinely seeing others attempt to conceal their phones during class, stating how cell phones by nature are easy for students to hide. “Definitely the phone. It’s easy to conceal, easy to take out and put back. You’ve got all your social media and friends on it. It’s just so easy to use. It’s all right in front of you, you know…a lot of my friends, they’ll try to ‘chat me up,’ you know, on their phones during class” (Bobby, Interview 1). This continual phone presence is something that all students witnessed throughout this inquiry. And for some reason, everyone always has a phone out on the desk, which I think is significant to this interview. Just computers and phones. If you’re watching a video in class, or if the teacher is making you just listen, it’s so tempting to just pick up your phone. Even in classes with strict phone policies where the teacher enforces it, people still use their phones. (Jan, Interview 1)

Keith, another high school student, identified the ease with which students can hide their cell phones, whether learning is happening remotely

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or at school. “Because, sure, we students have access to our phones, and it’s, you know, something pretty easy to hide…at school, you know, students are just trying to sneak their phone in during class or just outside in the hallway by either texting friends or just sifting through social media” (Keith, Interview 1). All teacher participants saw the same thing regarding cell phones being the primary device people become distracted on at school. Ms. Johnson described what a typical high school classroom looks like before the passing period bell rings, and the presence of mobile phones is a daily occurrence. A high school classroom is socializing, students standing at the back of the room before class, phones out before class and after dismissal. See, my own phone is constantly checked. That’s how I tell time. I don’t have a smartwatch, so that’s my clock. I’m also checking in on friends who text me. For both in-person and remote learning, phones are the main distraction. Absolutely 100% phones. So, when you see the kids being digitally distracted inside the brick-and-mortar school, it’s normally a phone. So, I know when they are at home, you can’t necessarily see what they’re doing on their phones, but you know that phones are still the problem. (Ms. Johnson, Interview 1)

Straight from an educator who is in the instructional trenches on a daily basis, and she said, verbatim, “phones are the problem.” Ms. Johnson undoubtedly earns brownie points with readers, too, because she herself admits to the frequency of how often she checks her own phone during school since it is her means of telling time and measuring activities while staying inside her own personal social loop. A different teacher, Mr. Keating agreed that seeing phones is the greatest source of distraction for students when learning in person. He even discussed how often he witnesses students checking their phones in areas of the school with a known lack of cellular connectivity. I would say for in-person learning, it’s definitely the phone, number one. If I go to the most common, which is kids on their phones, they are on their phones ­sending a message to someone, utilizing either texting or social media. That is the primary way they’re distracted. And it’s interesting because since I’ve been at this campus mostly this year in a section of classrooms where cell phone service is much harder to get than where I am right now, students are still trying to use their phones. It’s not going to work. It never works, and students are still trying to use their phones at the same rate they would, I think, in a room that had cell phone service. (Mr. Keating, Interview 1)

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A different teacher with a similar response, “…it’s definitely the phone, number one.” Another in the trenches statement from an educator fighting from the front lines of digital distraction on a daily basis. Mr. Holland not only agrees with students’ cellular fixation, but he also revealed a personal disdain toward cell phone distraction, stating that mobile phones were a trigger for non-academic behaviors, “Digital distraction is every time you grab your stupid phone and check YouTube and everything else like that, and it causes you to have ‘off task’ thoughts and behaviors. Nine-nine percent of their distractibility is their stupid cell phone” (Mr. Holland, Interview 1). This is where we as educators, administrators, and parents have to do a better job helping our young people to better identify the underlying causes of digital distraction, and how it impedes learning by affecting concentration and engagement. School leadership knows it’s the elephant in the room, yet nobody wants to blow the whistle on it. After our second round of interviews, both students and teachers continued to reinforce the notion that the majority of witnessed digital distraction occurs on cell phones, citing similar trends from the first round of interviewing: the inconspicuousness of mobile phones, the popularity of cell phones, losing track of time when engaged on cell phones, and struggling to transition between learning activities when actively engaged on cell phones. Oftentimes, students do not even realize the extent of time-­ on-­task learning focus they are losing after falling victim to the viral loop. It is like a digital vacuum of sorts where a student can click, see, and share while losing track of time, which becomes a serious problem for learning focus. Students continued to make similar statements as they did during the first round of interviews, but during this second round, their comments incorporated terminology like “attention,” “focus,” and “anxiety.” Here is some of that additional student commentary: • Phones because that’s the most common device that people use when digitally distracted, and it’s like always with you in hand. People can’t focus on two things at once, so drawing their attention to the phone obviously takes their attention away from what they’re supposed to be doing and learning. In my own experience, sometimes when I’m in class, I’ll just be looking at my phone. (Tracy, Interview 2) • The cellphone. I think because it is just so popular now as a device to use. Really anywhere now you’ll see people on their phones. Everyone has a cell phone. I think that it is a bigger problem with students when they

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don’t have anyone telling them to get off the phone. (Simone, Interview 2) • Phones because almost everyone has a phone, and almost everyone has something on their phone that they can’t get away from, like their games. Some students never really pay attention in school because they’re more worried about their phone. (Shirley, Interview 2) And if readers think the licensed educational professionals inside the school felt differently from students, absolutely not. During the second round of interviews, teacher-participants stated that phones were the default go-to and most addictive objects that students carry around with themselves on a routine basis at school. Additional teacher-commentary is listed below: • Phones because that’s the most universally addictive thing on our persons. It’s the first thing we check in awkward situations when you pass people in the hallway and don’t want to talk. It’s just the “go to” thing to check. (Ms. Johnson, Interview 2) • Phone. I just think that cell phones are things we all, whether consciously or subconsciously, view as extensions of our bodies at this point. (Mr. Keating, Interview 2) • I think it’s very hard for people to disconnect things, very hard for people to actually turn off their phones or to actually not check their phones. Like it’s normal for us to pull out a phone and check out a time versus checking a watch, or it’s normal for us to hit our smartwatch. But when students are doing their homework, and then their phone beeps, that’s the first thing, and then they’re like, “Oh, I gotta pick it up and see who’s texting.” (Mr. Holland, Interview 2) Even though mobile phones are the devices students are constantly seeing used for non-academic choices inside class, many students still own up to the frustration of becoming distracted digitally. This upfront honesty displayed by students concerning their digitally driven frustrations not only increases the reliability of this book’s findings, but it also brokers the likelihood of more generalizability among this book’s findings, too, as students and teachers in similar contexts likely share similar experiences. Your phones because you can basically do anything on your phone now, and there’s so many things, like so many apps now, that people use to get distracted

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on, and it just takes priority, I guess, when it shouldn’t, but it does. It literally just sucks. People are looking at their phones, and they’re not paying attention to what’s going on around them or to who’s talking to them or addressing them. They just won’t pay attention, and they’ll just look at their phones instead. (Tracy, Interview 1)

This lack of collective attention and lapses in focus cause learning to slow down for many as teachers try to get digitally distracted students back on track. A different student expressed similar frustration during class, especially when learning was in person, “In person, you see a lot of cell phone and smartwatch use. I see a lot of students trying to hide their phones from their teachers…I feel like it is a very big problem. I feel like there is a very big distraction because I do have my phone right next to me” (Simone, Interview 1). Simone’s comments also reflect the vast amount of digital freedom afforded to high school students because of their access to digital technology in school, which continues to be a global issue across most school districts. Even though cellphones and Chromebooks were the most popular devices used for digital distraction during learning, study participants also mentioned seeing other mobile technology. Some of this mobile technology was used for non-academic communication (i.e., smartwatches and earbuds), while other digital devices were used predominantly for entertainment purposes (e.g., TVs, Bluetooth speakers, video game systems). For Simone, 3 years of high school (even though almost half of it was remote) was still enough to identify a litany of devices students became digitally distracted on during class. For “in person” learning, you see a lot of cell phone and smartwatch usage. Then for “at home” learning, I feel like it’s gonna be a lot of your bigger devices, like your video gaming, your TV, your iPad, watching movies during class, etc. Students continued to use these devices for non-academic purposes (e.g. non-­ academic communication and entertainment) in a variety of instructional settings, whether class was happening inside a traditional classroom or remotely from home. (Simone, Interview 2)

Other non-academic activities mentioned by students and teachers that diverted attention during in-person and remote learning revolved around digital entertainment (e.g., music, video games, movies). Alice, a top student from the school, was adamant when describing the negative impact

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digital entertainment had on students when learning remotely from home, claiming, “They can play video games, watch YouTube, or do whatever they want. Meanwhile, the device is just providing us with entertainment…and we’re using that time instead to focus on entertaining ourselves instead of learning” (Interview 2). Many other students also admitted to being complicit to using digital entertainment during class. Their additional comments are listed below: • And now what’s been popular in past years is like Apple Watches because you can text and take pictures and all that on them. In addition, you’re like starting to have TVs everywhere you look at school. (Greg, Interview 1) • I get distracted a lot, and with digital tech, I also use video games and game consoles. I play some mobile games as well. And then my number two distraction when learning at home would probably be game consoles, and I’ve seen a few of my classmates on them too. I sometimes see them watching their favorite TV shows on Netflix and Hulu. When students are learning remotely from home, they have the freedom to do whatever they please. They could be watching TV or playing video games while the lesson is going on. (Peter, Interview 1) • So even though I have my personal laptop sitting in front of me at home, I have my school-issued Chromebook sitting right on top of it. I don’t really turn off my TV or any stuff like that. I do know of people who just take their Chromebook onto their couch or into the living room to watch TV or play video games, stuff like that. I’d say it’s probably tougher when learning at home. (Bobby, Interview 1) • At home, I mostly use art apps that are actually on my iPad. When at home during remote learning, the TV serves as a distraction, too. Maybe we like the background noise, or if you’re bored, you can watch TV. When I’m at school, I have my earbuds in, and adults never say anything. (Jan, Interview 1) • Usually, I mainly listen to music, so I just plug in my AirPods, only one of them. Some students like having their blue tooth speakers on in the hallways between classes, too. (Cindy, Interview 1) • For in-person learning, you see a lot of cell phone and smartwatch usage. Then for remote learning, it’s going to be a lot of your bigger devices, like your video gaming, TV, and iPad, watching movies during class. (Simone, Interview 1)

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• Sometimes, I see Apple Watches and earbuds. I think that’s distracting because if you’re listening to your music, then you’re not listening to the teacher. So, this is happening inside the classrooms and also out in the hallways. When learning remotely at home, there’s the TV on in the background from other students’ computers, or you hear your TV or your parents playing music in your own house. Not only is the TV going on in the background, but I’m also checking my Apple Watch, too. (Laurie, Interview 1) From Laurie’s comments, one can see the irony in students choosing digital distraction during remote learning because of the increased potential for a variety of digital and non-digital disruptions randomly occurring and caused by others. And again, the continual lack of supervision during remote learning is an important recurrent takeaway, too. • At school, if it was really important, I have a smartwatch that I would look at if my dad texted me or if something happened. On those remote learning days, it’s definitely different from when I’m at school because I have the freedom to use my cell phone whenever I want. So that’s where I’m a bit more lenient with myself when talking to friends on it. For the number two overall distraction, I definitely say it goes on to the smartwatches after the cellphone. The TV is third, and this kind of corresponds to television and the gaming systems that a lot of people enjoy, like the PS4 or Xbox. When I’m at school, I normally put my phone in my bookbag but keep my AirPods in. (Shirley, Interview 1) • Apple Watches, too. I don’t have one, but I see a lot of people often looking down at them. (Alice, Interview 1) These students’ comments reinforce the recurring theme of digital variety, a factor stakeholders will undoubtedly continue to wrestle with as more and more new and engaging technology continues to develop over time. Tag-teaming mobile digital devices is becoming a common everyday phenomenon, and some students are using their own personal computers, in addition to their school-issued device(s), because of the school district’s inability to regulate their activity. During Keith’s first interview, he mentioned how he uses his personal laptop simultaneously with his school-­ issued Chromebook because his high school cannot regulate his personal computer. Keith suggested his greatest digital distraction stemmed from running his personal computer alongside his school-issued Chromebook

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during class. Ironically, Keith’s teachers never questioned his actions, so the assumption is his teachers simply thought Keith was cyber-tasking even though he was really playing video games. Teachers participating in this study went so far as to mention AI. Ms. Johnson stated during her first interview how she personally uses Google Assistant throughout the day to check notifications and weather. Another teacher, Mr. Keating noted how he uses a digital alarm clock, in addition to a tablet, to track time or to stay up to date with local, national, and international news. He also mentioned noticing a major uptick in students wearing smartwatches to school over recent years. This captures the cause-­ and-­effect relationship between this uptick in personal mobile digital technology caused by an increase in reasonably priced digital device surplus, which likely compounded during the COVID-19 pandemic. Finally, Mr. Holland discussed students’ penchant for video games, arguing that mobile gaming consoles serve as significant a distraction for students during learning as cell phones because of the gaming chat features. The problem is that a lot of these kids with their PlayStation or Xbox become just as valuable as the phone because you have all these chat features with these games. You have all these apps and all this stuff that students can just use through their digital technology. Kids when they play games will actually be on their phone and on the game at the same time. I think it’s very hard for people to disconnect things, very hard for people to actually turn off their phones or to not actually check their phones, email, iPad, or smartwatch. (Mr. Holland, Interview 2)

Other than personally owned mobile digital technology, both students and teachers cited the irony in witnessing digital distraction happening on school-issued digital technology. The site studied for this inquiry provided students with Google Chromebooks, and this study’s data revealed the Chromebook to be the second most witnessed digital device study participants became distracted on during both in-person and remote learning. As mentioned earlier, some participants noted the irony of the Chromebook distraction since it was a school-issued device. Many of the participants stated how the Chromebook could perform most of the same actions and run the same applications as a smartphone. Because of the Chromebook’s multi-faceted applications, it became a common device for students to use for non-academic purposes during class.

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And then other things could be your Chromebook. I think during remote learning, it’s much easier to be distracted because most of the time in some classes, even though it’s a policy to have your camera on, people still don’t. They just have their Chromebook open on our Google Meet. On my Chromebook, I’ll see that someone G-chatted because I’ll get a notification, so I’m going to want to check that. Or if someone mentioned something in class, I’m going to want to look it up and get distracted by that. Every student has a Chromebook. (Greg, Interview 1)

Another student, Bobby, mentioned how notifications on school-issued Chromebooks were as distracting as cell phone notifications, “I think a lot of digital distractions are notifications you randomly get on your phone or Chromebook.” The immediacy of information digital technology provides in today’s world, as seen with notifications, provides an easy outlet for students to become distracted during learning. When coupling the aforementioned with the mobility of school-issued Chromebooks or iPads, and student accessibility to distraction when learning on these devices practically parallels student-owned smartphones. Not to mention, many students use their school-issued devices in tandem with their personal devices, so the potential for distraction significantly increases. I define digital distraction as any type of electronic device that you can get your hands on. It could be any type of device, like your phone or Chromebook, because you’re going to get a notification and want to check it out on your Chromebook. In school, I see myself getting distracted a lot. On my Chromebook, I’ll see that someone G-chatted me or something because I got a notification, so I’m going to want to check that out. (Marcia, Interview 1)

With the advent of G-chat, students often message each other on their school-issued Chromebooks during class, and sometimes these chats are for school-related business, but oftentimes they are used for non-academic purposes, which compounds learning distraction. When certain Chromebook apps originated like Google Docs, which provided a fresh new way for users to communicate with each other while working on the same document in real time, it proved to be a collaborative game-changer for students and teachers when workshopping in groups on writing assignments. But it did not take long for students to find how easily they could communicate with each other for non-academic purposes on this app, which manifested distracted learning. With the availability of G-chat, Google docs, and Google Meets, students have a cornucopia of

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possibilities for fostering and sustaining distracted learning, even when learning is happening in person. So the “school-issued” 1:1 Chromebook is the next digital distraction. Case in point, if you are in a classroom and the teacher asks for phones to be put away or takes phones away, then you know some of the distraction would have potentially happened on their phone instead of on the Chromebook. This case site opened up the G-chat feature for students, so you can email friends through chat, and some people even communicate through Google Docs. They just share the docs, and they’re all typing on it at the same time. But the other thing too is with the Google Meet because kids can run multiple Google Meets. So a kid could be on a Google Meet with their teacher for learning, but then they could be chatting or gaming on another Google Meet with their friends. From personal experience, I know certain teachers just “close out” their students’ tabs for them, and they just don’t let them open them up at all. So it’s pretty effective using lockdown browsers. (Tracy, Interview 1)

Students have become increasingly adept at using the multiple tabs features of Chromebooks, which Tracy referenced in the previous quote. Some schools do not provide teachers with the software for a hard lockdown of students’ browsers (e.g., software programs like Hapara), so then it becomes a foot chase inside the classroom for teachers, dodging between desks while trying to police students’ use of multiple tabs. Some teachers have even gone so far as to install rear view mirrors in the back upper corners of their classrooms to visually spot students becoming distracted on non-academic tabs, but management techniques like this can actually become distracting to students who are on task with all the busy-bodying of constant teacher mobility in and around the classroom and other instructional spaces. The following anecdotal examples further illustrate how students and teachers are seeing digital distraction happening on school-issued 1:1 devices like Google Chromebooks: • I think our Chromebooks are the biggest contributor to digital distraction at school because there are still a lot of things you can do on them that aren’t related to class, even when you’re inside the school. (Simone, Interview 1) • And then number three for digital distraction, I would say our Chromebooks because you can go on Pinterest and other websites that no one is supposed to be on. So, I believe that some students have their

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Chromebooks on for their Google Meet with the teacher and their camera off. (Shirley, Interview 1) • But when it comes to Chromebooks and all that, usually we have our Chromebooks on with a Google Meet running regardless if we’re “in person” or learning remotely. So we always have that level of distraction where we can check our email during other classes and homework assignments while we’re technically in a different class. When it comes to technology in an “in person” school setting, there’s always that relationship between student and Chromebook that students have access to. Personally for me and my online setup, I guess I have my Chromebook off to the side with either class notes and the actual Google Meet running on my personal laptop, so then I have a second display I can use for notes and stuff like that…The multiple tabs selection definitely has its play in the level of distraction because if you know the shortcuts on your keyboard and all that, it’s really easy to open and close not only different tabs but different windows, too. So if the teacher is ever trying to walk behind you, it’s really easy just in a matter of seconds to switch tabs. So that’s definitely a level of distraction that could come with using the Chromebook and the multiple tabs feature. I don’t know, but I’m just the type of person that doesn’t really spend time clearing their tabs until the end of the day. I’m usually running around with eight different tabs on like five different windows, so in total there could be around forty tabs open at a single point in time. When it comes to “in school” learning and student distraction, I guess the device that would most commonly be used for students when it comes to digital distraction would definitely be our Chromebooks. Because sure, we students have access to our phones, and it’s something pretty easy to hide. And if you ever get caught with it, you know you’d obviously get into trouble. But when it comes to the Chromebook, you can easily open in a different tab and all of that to make it look like you’re actually doing something else. When it comes to “at school” learning, the main thing that I’ve seen was students on their Chromebooks hopping on YouTube and watching videos in class. I think that definitely has an overall effect when it comes to distraction because there are certain ways that students can use a laptop. For example, using shortcuts, opening different tabs and all that can be used to get distracted while making it appear that you’re doing work. (Keith, Interview 1)

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Students not only considered the accessibility of the school-issued Google Chromebooks, but they also mentioned students’ ability to ghost calls by turning off their webcams while working on non-class related tabs. Stakeholders must remain cognizant that the digital instruments themselves are only half the concern when managing appropriate digital behavior during class. The creation of new applications and programs that run on digital devices continues to generate challenges for the management of non-academic digital behaviors (e.g., communication with friends) during class. Logistically, some students’ rationale for the use of multiple tabs makes sense as they were born into this computerized windows style of management. In addition, students have conditioned themselves to navigate multiple windows quite effortlessly when in class, but this by no means ensures students are maintaining focus and engagement during learning. From the onset of this knowledge pursuit, teacher-participants noted the potential for distraction on school-issued Chromebooks. Specifically, some participants like Mr. Keating mentioned the irony of teachers inadvertently prompting students into digital distraction by asking them to research certain topics on their Chromebooks during instruction, “But again, I try to minimize their ability to be distracted by their Chromebook by really managing when they should have their Chromebook out. But then when they’re on their Chromebook because I’ve told them to look at something, they’ll get distracted as well” (Mr. Keating, Interview 1). Mr. Holland identified the Chromebook’s chat features, citing how many students run multiple Google Meets on their Chromebooks for non-academic communication with friends during class. “I even think Chromebooks are distractions, which again, I disagree with how we do a lot of our stuff that we do” (Mr. Holland, Interview 1). Along with students’ personal cell phones, the school-issued Google Chromebooks are seen as another potential distraction at school. During the second round of interviews, more students provided perspectives into the digital distraction posed by Chromebooks. Many of these students mentioned the G-chat instant messaging feature during the semi-structured interview. When I’ve noticed other students’ Chromebooks, I noticed that they Google Chat with their friends to their emails, and sometimes they’re even on a separate Google Meet, so they can talk to each other without the teacher knowing even though they can still see class on the main Google Meet. You will definitely get more instant gratification with a G-chat versus an email because it’s much

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faster. Whereas with G-chat, it gives you a notification. You get an audible notification. (Peter, Interview 2)

Chromebooks serve as popular “go to” devices for students, especially when teachers limit student access to personal cell phones inside the classroom. This accessibility of school-issued devices like Chromebooks provides students with a continuous medium through which they can communicate with others throughout the day, even when in the midst of instructional class time. The only thing they could do is probably go on their Chromebooks and open separate tabs, but even that’s limiting the amount of things because certain sites are blocked on our Chromebooks. But I also feel like having a Chromebook would probably cause people to go on their other digital devices a little bit less just because the Chromebook is a digital device itself. So people can go on there to communicate or do whatever they need to do rather than pulling out their phone. Even if it is in the middle of the school day because I could possibly be in-­person learning while the student I’m working with will be at home, and we’ll have to use our Chromebooks to communicate with each other, which is going to just open the door for more digital distraction on both of our parts. (Tracy, Interview 2)

The accessibility of school-issued devices, like Chromebooks, provides students with a continuous medium through which to communicate both academically and non-academically with others throughout the school day. Some students try to circumvent these digital temptations by deactivating certain technological features. During his second interview, Keith mentioned just this, stating how he deactivates any feature(s) that prevents him from accessing multiple tabs or websites because of the distraction they impose. Unfortunately, too many students have become accustomed to navigating between various non-academic websites during class because of the ease modern classroom technology affords. Mr. Keating reinforced this recurrent issue during his second interview, “I guess the one thing that I thought was interesting with kids is their dexterity and ability to move between those opened Chromebook tabs fairly effortlessly.” This effortlessness Mr. Keating referenced is conditioned student behavior. Today’s students were born into Web 2.0 technology, so the click-and-share mindset is not a new phenomenon for high school students. Logistically, it makes sense that student dexterousness and ability to navigate multiple tabs and windows on multiple devices simply improved with remote 1:1 schooling

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throughout the COVID-19 pandemic. But now as school districts and teachers are attempting a return to some kind of instructional normalcy post-pandemic, unlearning these conditioned digitally distracted behaviors is becoming education’s next big challenge.

References Berdik, C. (2018). Dealing with digital distraction. Education Digest, 84(1), 40–45. http://search.ebscohost.com.cucproxy.cuchicago.edu/login.aspx?Direct=true &AuthType=cookie,ip,cpid&custid=s8419239&db=tfh&AN=131039574&site =ehost-­live Campbell, S.  W. (2006). Perceptions of mobile phones in college classrooms: Ringing, cheating, and classroom policies. Communication Education, 55, 280–294. Cheong, P. H., Shuter, R., & Suwinyattichaiporn, T. (2016). Managing student digital distractions and hyperconnectivity: Communication strategies and challenges for professional authority. Communication Education, 65(3), 272–289. https://doi.org/10.1080/03634523.2016.1159317 Lawson, D., & Henderson, B. B. (2015). The costs of texting in the classroom. College Teaching, 63, 119–124. https://doi.org/10.1080/87567555.2015. 1019826 McCoy, B. (2013). Digital distractions in the classroom: Student classroom use of digital devices for non-class related purposes. Faculty Publications, College of Journalism & Mass Communications. Paper 71. Retrieved March 10, 2017, from http://digitalcommons. Pettijohn, T. F., Frazier, E., Rieser, E., Vaughn, N., & Hupp-Wilds, B. (2015). Classroom texting in college students. College Student Journal, 49(4), 513–516. https://doi.org/10.1016/j.chb.2014.03.045 Redner, R., Lang, L.  M., & Brandt, K.  P. (2019). Evaluation of an electronics intervention on electronics use in a college classroom. Behavior Analysis: Research and Practice. https://doi.org/10.1037/bar0000158 Roberts, R.  C. (2016). Preventing cell phone use in the classroom. College Teaching, 64(3), 145. https://doi.org/10.1080/87567555.2015.1125844 Rosen, L.  D., Carrier, L.  M., & Cheever, N.  A. (2013). Facebook and texting made me do it: Media-induced task-switching while studying. Computers in Human Behavior, 29, 948–958. https://doi.org/10.1016/j.chb.2012.12.001 Seemiller, C. (2017). Curbing digital distractions in the classroom. Contemporary Educational Technology, 8(3), 214–231. https://doi.org/10.30935/ cedtech/6197

CHAPTER 4

What Do Students and Teachers Believe Contributes to Digital Distraction in School?

Abstract  A combination of digital and non-digital factors triggers digital distraction during learning, whether learning is happening synchronously or asynchronously, at school or remotely from home. Boredom, a well-­ documented phenomenon within school (Buxton, Adolescents in schools, Yale University Press, 1973; Csikszentmihalyi & Larson, Being adolescent, Basic Books, 1984; Jackson, Life in classrooms, Holt, 1968; Mitchell, Journal of Educational Psychology, 85(3), 424–436, 1993), was well supported through this book’s findings. Other non-digital influences included multitasking and instant gratification (Berdik, Education Digest, 84(1), 40–45, 2018; Berry & Westfall, College Teaching, 63(2), 62–71, 2015), all of which can lead to cognitive overload when learning (Rubinstein et al., Journal of Experimental Psychology. Human Perception and Performance, 27(4), 763–797, 2001; Skok, No teacher without a student … A theoretical analysis and practical implications of educational changes in the era of digital natives. In M.  Kowalczuk-Walêdziak, A.  Korzeniecka-Bondar, W. Danilewicz, & G. Lauwers (Eds.), Rethinking teacher education for the 21st century: Trends, challenges, and new directions (pp. 111–126). Verlag Barbara Budrich, 2019). Cognitive overload is concerning, especially since it can lead to a variety of emotional and psychological problems such as addiction, general anxiety, separation anxiety, instant gratification, and “fear of missing out” (FOMO). Digital devices inside the learning setting, whether that setting is inside a brick-and-mortar school or remote, compound the potential for these social-emotional issues, leaving students and © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. C. Schuett, Beyond Digital Distraction, Digital Education and Learning, https://doi.org/10.1007/978-3-031-53215-3_4

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teachers openly stressed and anxious, which further exacerbates lapses in learning focus and active engagement. Keywords  Focus • Engagement • Boredom • Web 2.0 • Multitasking • Multiprocessing • Instant gratification • Fear of missing out (FOMO) • Addiction • Anxiety • Stress • Lack of supervision • Device accessibility • Device leniency • Asynchronous learning • Intrinsic motivation • Electronic notifications • Digital entertainment • Digital apps • Multiple tabs/windows • Digital distraction • Google Generation • iGeneration • Hypertext minds Participants felt that focus and engagement were affected by a combination of digital and non-digital factors that contributed to digital distraction during both in-person and remote learning. Even though participants identified both digital and non-digital factors, the participant majority felt that non-digital influences contributed the most to losses of focus and engagement when learning, which challenges the literature. This book’s research stemmed from a student-participant majority, so that might have contributed to this discovery, especially since all participating students and one participating teacher were born after 1993. Subsequently, the majority of research participants are digital natives, individuals born into Web 2.0 technology with “hypertext minds” often labeled Google Generation and iGeneration (Prensky, 2001a, 2001b; Skok, 2019). This particular generation believes that multitasking and multiprocessing while attached to mobile technology is good executive functioning (Prensky, 2001a, 2001b; Bennett et  al., 2008; Grigoryan, 2018; Oblinger & Oblinger, 2005; Skok, 2019; Smith, 2012a, 2012b; Tapscott, 1999), even though this book’s findings challenge the effectiveness of multitasking with technology while learning. Boredom was the top non-digital influence, which supports previous literature (Buxton, 1973; Csikszentmihalyi & Larson, 1984; Jackson, 1968; Mitchell, 1993). Non-digital influences like boredom, multitasking, and instant gratification divert attention from learning toward digital distraction (Berdik, 2018; Berry & Westfall, 2015), and this initiates cognitive overload when learning (Rubinstein et al., 2001; Skok, 2019). This cognitive overload can lead to psychological and emotional problems with addiction, general anxiety, separation anxiety, instant gratification, and “fear of missing out” (FOMO) for students, all of which is fueled by

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parental/teacher leniency, required mobile technology use (especially with COVID-19 protocols like daily health self-certification, homework submission, and Google Meet/Zoom sessions), lack of supervision, and device accessibility. According to one student-participant, when students felt disengaged during class, boredom often triggered digital distraction even when attending school in person. “Either if they have an itch to text their friends, or mainly if the teacher isn’t interactive enough with teaching. And like I said before, if they release us on our own free time to do the work, students tend to get bored a lot” (Peter, Interview 1). Peter addressed the difficulties students had when teachers were not instructionally interactive, or when they assigned asynchronous work. This feeling of disconnection from class and the course material is something many student-participants addressed. Sometimes, you’ll just be bored, and I don’t know, but you maybe check out YouTube or go on Twitter or something and see what people are doing. But besides that, I would say that the topic in class, you know, if the student finds it boring or there’s something they don’t understand, and they feel disconnected from the class. (Bobby, Interview 2)

Another student mentioned how learning engagement and focus were only as good as the educational content delivered during class. The interactivity of a teacher’s instructional delivery method and style contributes to the likelihood of students becoming engaged on digital devices for non-academic purposes. For two of my three classes, it’s not a problem because I focus on staying engaged, and I like understanding the content because that’s really important to me. And the teacher asks us more questions as well, so that keeps me more engaged and on top in order to answer questions and give responses. And in the other class that I sometimes get distracted in, I think it’s just because they’re more like giving you a speech, like they’re just talking to the class. They lecture the whole class period, so you don’t feel like you are engaged as much…I know I’m distracting myself on a digital device, and that I probably should not be doing it. (Alice, Interview 1)

When a teacher simply lectures, students become bored because of the lack of active learning. Stakeholders need to be aware that the proximity of digital devices is usually not the fault of students, especially when school districts or specific teachers mandate 1:1 learning, which became the

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universal norm throughout the COVID-19 pandemic. When boredom sets in during a non-engaging class, students have access to digital technology that they are masterfully comfortable with navigating. Here are some other participant comments that corroborate the boredom phenomenon: • Probably a lot of it is boredom, and so then that causes a downshift of engagement, and students look for that engagement in something else. (Peter, Interview 2) • Crazy boredom. Just the “not knowing” of what to do. It’s so easy to grab your phone to look at if you’re just sitting there, or if you’re “in class” and just want to look at your notifications. On days when we have to master and actually learn new skills, more people pay attention. (Jan, Interview 2) • …and our way of accessing the internet is of course technology and this infinite flow of information. It kind of stimulates your brain whenever it’s bored or looking for something to do. (Bobby, Interview 2) According to students, one of the quickest ways teachers can foster participation is by increasing classroom engagement through more face-to-face interactions and open conversation, because engagement matters to students. Try to engage more with the class, talk to them, or even just converse with them more. Let’s just say engage with them and try to have conversations with them. Try to make learning more fun by incorporating games and activities. Even though we’re high schoolers, we are still kids at heart, so we love playing games and engaging with teachers and just knowing them more so we can get comfortable with them. (Cindy, Interview 2)

As the reader can see, Cindy’s comments illustrate that not only engagement mattered, but it increased her active participation in class. When students like Cindy become bored because the class and the teacher lack engagement, they lose learning focus. Another student, Laurie, reiterated this, “Maybe just in general trying to have more excitement in class. If the teachers are providing either a boring class or boring material, not only are they bored, but their students are bored too” (Interview 2). If teachers are bored, students will be bored too. Combatting this boredom by creating and facilitating engaging instructional pedagogy, whether that includes

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digital technology or not, should be an expectation of all educational stakeholders. When teachers model something as simple as instructional passion, student engagement appears to be bolstered—subsequently, energy may provide a non-digital remedy of sorts to help combat digital distraction inside the classroom. To know what they do affects students, and to see the effort that they put in is like the effort students will put in. Because if students see that their teachers are really passionate about a topic and want to learn with them, then they will put more effort in themselves. But if the students see that the teacher is digitally distracted, then they will become digitally distracted too. And that might be one of those subconscious deals where you know if the teacher doesn’t seem engaged, then why would students be engaged. (Shirley, Interview 2)

Educators can foster their instructional energy through the incorporation of digital technology, but digital technology is just a tool used in and out of the classroom setting. Technology by itself can by no means guarantee a teacher’s instructional energy or passion for instruction in any given subject. Other comments pertaining to what participants believed contribute to digital distraction inside the brick-and-mortar and/or virtual classroom include the following: • Boredom is a problem because when we’re at home, we’re not as engaged in the classroom, and we don’t find it as important. Then we get distracted super easily, so we focus on entertaining ourselves with our electronic devices in those moments of boredom we experience in the classroom. (Alice, Interview 2) • But in most cases, I would say it’s mainly just a lack of interest. So if a student is not really interested in the class, their immediate reaction, I guess, is to search, or find something else to get busy with, and that usually takes place on the phone that’s right next to them. I guess students could be aware to some extent, but in other ways it’s sort of a natural reaction to boredom. (Keith, Interview 2) Keith used the phrase “better teacher-to-student engagement,” which indicates that though he is a senior in high school, he is still aware of the importance of collaboration between students and teachers on focus and engagement during the learning process. When this shared partnership lags because a team member becomes inattentive due to digital

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distraction, disengagement from the work and collaboration with the learning team both suffer. One teacher-participant discussed his personal struggle with navigating boredom during hybrid teaching. The one negative I will tell you is that I found out that I am bored, and I am bored because I think that we as a society feed off of other people, especially in this type of environment. No kid had an incentive to put a camera on. No kid had an incentive to talk, and maybe that was my problem as a teacher. To incentivize it somehow, or to make it cool, or to make it like, “Hey, this is normal guys for us to have our cameras on” versus having to look at each other’s emoji from 1994. (Mr. Holland, Interview 2)

Mr. Holland even mentioned the definitive lack of personalized communication between teachers and students over the course of teaching because of remote and hybrid online learning, which continues to plague online learning post-pandemic. This input suggests that social media and other interesting online platforms easily draw bored students into becoming digitally distracted. Jan discussed how digital distraction is the present-day version of doodling. “I would compare it to how before phones were popular, kids would just doodle or scribble on paper. Instead of doodling, now we have phones. It’s just the modern way of ‘being bored’ and dealing with that boredom” (Interview 1). When students become bored, digitally distracting themselves with technology is similar to how students have always sketched, doodled, and drawn on paper during class. But unlike studies that have shown doodling’s potential for increasing input retention while listening to instructional facilitators lecture, students’ off-task digital behavior simply derails learning focus and engagement. Addiction, anxiety, and the stress of “missing out” on something, especially when it came to social media (Fewkes & McCabe, 2012), were other important non-digital influences participants mentioned. For example, digital device actions like texting allow students to feel connected to their social circles (McCoy, 2013; Seemiller, 2017, p. 217). Greg, a freshman heavily involved in extracurricular activities, talked about his addictive fear of missing out on something that was happening on social media, “It’s really an addiction…I will be thinking about it the whole time” (Interview 1). Teachers also mentioned the social-emotional anxieties students felt when separated from their digital devices. Ms. Johnson and Mr. Keating acknowledged how social pressures drive these psychological and emotional stressors, pushing students toward digital distraction. Ms. Johnson

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said, “…their reason for checking, I think, is a lot more psychologically and emotionally based…Teenage anxiety and the need for social interaction, which is usually figured out through a phone” (Interview 1). Mr. Keating followed suit by saying, “So, I think fundamentally, it is social pressures that drive digital distraction, like the idea that if students are not checking their phones, Snapchat, whatever it is, they are missing out. And so, I think that is what primarily drives them to check their devices…like students feeling like if they don’t check their texts, their social media, whatever, they are going to miss something” (Interview 1). Negative emotional promoters like anxiety were not the only psychological or emotional facilitators of digital distraction described by participants. Students and teachers addressed the feelings of instant gratification digital devices provide, which could also trigger digital distraction during class, too. Study participants also discussed how instant gratification, a well-documented phenomenon among this generation (Bennett et  al., 2008; Ramble, 2012; Rowlands et  al., 2008; Skok, 2019; Skok & Laszewicz, 2014), could serve as a contributing influence toward digital distraction during both traditional and remote learning, but especially in the realm of on-line learning. One student even mentioned the guilty pleasure associated with accessing digital technology during class because of the feelings of instant gratification that occur. Another student discussed how some school-sanctioned apps on students’ Google Chromebooks, like G-chat, promote feelings of instant gratification because of their immediacy when compared to more antiquated modes of digital communication, like email. Two sub-patterns that garnered a lot of attention by participants included parental and teacher leniency toward digital device usage because of COVID-19, and the lack of supervision, coupled with freedom of device accessibility, also due to the pandemic. Students shared similar viewpoints that mobile device use in school was more relaxed than prior to the pandemic, especially since the school required students to use more digital technology for protocols like daily health self-certification, homework submission, and Google Meet sessions. Some students, like Jan, a freshman student-athlete, felt that the general frustrations of pandemic living caused parents to be less strict about mobile device use, “It’s definitely made everybody kind of slack off. If you’re on your phone but not actually doing your work, a lot of people are saying it’s okay because it’s been a hard year” (Interview 1). The majority of student participants shared similar observations to Jan’s sentiments.

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This increased leniency and lack of supervision ties directly into engagement theory, and what the literature describes as reinforcement history or the degree that on-task academic behavior(s) rewarded in the past directly affects student engagement in the present (Martens et al., 1997; Shernoff et al., 2003). When parents and teachers left students unsupervised, especially in remote asynchronous learning, there was limited opportunity for students to receive real time praise, encouragement, and direction from adult stakeholders. This not only affected student engagement, but it undoubtedly stifled students’ intrinsic motivation to replicate meaningful focus and engagement during learning, especially over extended periods of time. As the literature denotes, an individual must simultaneously experience concentration, interest, and enjoyment for any given activity for the flow state to occur (Csikszentmihalyi, 1997; Shernoff et al., 2003). When students become digitally distracted during class, oftentimes by boredom, the transfer of knowledge and their metacognition, two important cognitive processes (Bélanger, 2011) suffer. Maintaining learning focus during class cannot occur when students become disengaged for non-academic reasons through use of digital devices. Because of the lack of remote structure and unsupervised learning from home, few if any students likely experienced anything close to the flow state when learning remotely throughout the COVID-19 pandemic. The majority of examples stemming from this theme were non-digital contributors, but participants provided some interesting digital contributors as well. Not all technology used in the classroom is positive, especially when the devices themselves become distractions for their users and for other classmates (Seemiller, 2017, p. 214). Throughout both sets of semi-­ structured interviews, participants noted that texting, checking notifications, especially from social media, and engaging in digital entertainment caused a meaningful loss of focus and engagement during learning. Notifications sent to and from mobile digital technology was an extremely popular response among case study participants. Twenty-four unique data chunks supported this sub pattern as students discussed the break in learning focus caused by electronic notifications, especially on cell phones and Chromebooks. Greg described the addictive nature of notifications on both his cell phone and Chromebook, “So, when I see the screen light up, it makes me want to check it. Or on my Chromebook, I’ll see that someone G-chatted me something because I’ll get the notification. I’m going to want to check that out” (Interview 1). Another student, Peter, also identified notifications on his school-issued Chromebook, “Whereas with

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G-chat, it gives you a notification. You get an audible notification. Yes, I believe people get distracted because if they get it, it’ll pop up on the screen and be all flashy, and it’ll be interesting to them” (Interview 1). This addictive impulse to check notifications, whether notifications are coming through personal or school-issued mobile technology, derails the necessary focus students need to meaningfully engage with course material. In addition to notifications, students and teachers described other digital contributors to digital distraction, like digital apps, multiple tabs, and extra windows. New and engaging apps, coupled with multiple tabs and windows features on mobile digital devices, were other common patterns cited as contributing factors to loss of focus and engagement during both in-person and remote learning. Some of these apps were sanctioned and installed on school-issued devices (e.g., Google Chat on Chromebooks), while others were installed by students on personal electronic devices. In addition, the finesse and dexterity students exhibited when employing multiple tabs and windows provided yet another channel for digital distraction during class. Cindy, a freshman student who admittedly struggled while learning remotely, described how a popular app and the multiple tabs feature could foster digital distraction. But now kids can open up multiple tabs so that way they can be watching YouTube while also being on a Google Meet with their class, or potentially opening up a Google Meet with friends while also being on a Google Meet with our class. Because like this school year, I will FaceTime my friends during class. (Interview 1)

Keith, a graduating senior majoring in aeronautical engineering, reinforced this finding, The multiple tabs selection definitely has its play…it’s really easy to open and close out, not only different tabs but windows. So, if the teacher is ever like, you know, trying to walk behind you, it’s really easy to just close out in a matter of seconds. So that’s definitely a level of distraction that could come with using a Chromebook and the multiple tabs feature. (Interview 1)

Students’ use of these new and engaging technologies continued to affect their level of focus and attention during class, whether students were attending class remotely or in person. Because of this, educational stakeholders must weave digital distraction into the daily classroom vernacular,

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and not just as a classroom management term. Taking the time to invite both students and parents into the digital distraction conversation while showing them the data, and ensuring all parties actually understand the magnitude of the data, has to become the norm if meaningful change is ever to occur. Common sense dictates that everyone generally knows digital distraction is negatively impacting people’s attention and focus throughout an individual’s personal and work day, but actually taking the time to actively show students and parents how digital distraction’s influence affects people’s long-term intellectual and socio-emotional success— breaking it down with visuals all parties can understand while having in-depth conversations to increase the likelihood of understanding—needs to become the new norm if schools want to foster true working relationships with families.

References Bélanger, P. (2011). Learning theories: Discussion. In Theories in adult learning and education (pp.  49–52). Verlag Barbara Budrich. http://www.jstor.org/ stable/j.ctvbkjx77.8 Bennett, S., Maton, K., & Kervin, L. (2008). The “digital natives” debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786. Berdik, C. (2018). Dealing with digital distraction. Education Digest, 84(1), 40–45. http://search.ebscohost.com.cucproxy.cuchicago.edu/login.aspx?Direct=true &AuthType=cookie,ip,cpid&custid=s8419239&db=tfh&AN=131039574&site =ehost-­live Berry, M. J., & Westfall, A. (2015). Dial D for distraction: The making and breaking of cell phone policies in the college classroom. College Teaching, 63(2), 62–71. https://doi.org/10.1080/03054985.2017.1305045 Buxton, C. (1973). Adolescents in schools. Yale University Press. Csikszentmihalyi, M. (1997). Finding flow: The psychology of engagement with everyday life. The masterminds series. Basic Books. Csikszentmihalyi, M., & Larson, R. (1984). Being adolescent. Basic Books. Fewkes, A. M., & McCabe, M. (2012). Facebook: Learning tool or distraction. Journal of Digital Learning in Teacher Education, 28(3), 92–98. Grigoryan, T. (2018). Investigating digital native female learners’ attitudes towards paperless language learning. Learning Technology, 26, 1–27. Jackson, P. W. (1968). Life in classrooms. Holt. Martens, B. K., Bradley, T. A., & Eckert, T. L. (1997). Effects of reinforcement history and instructions on the persistence of student engagement. Journal of Applied Behavior Analysis, 30, 569–572.

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McCoy, B. (2013). Digital distractions in the classroom: Student classroom use of digital devices for non-class related purposes. Faculty Publications, College of Journalism & Mass Communications. Paper 71. Retrieved March 10, 2017, from http://digitalcommons.unl.edu/journalismfacpub/71 Mitchell, M. (1993). Situational interest: Its multifaceted structure in the secondary school mathematics classroom. Journal of Educational Psychology, 85(3), 424–436. https://doi.org/10.1037/0022-­0663.85.3.424 Oblinger, D., & Oblinger, J. (2005). Educating the net generation. https://www. educause.edu/ir/library/pdf/pub7101.pdf Prensky, M. (2001a). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. Prensky, M. (2001b). Digital natives, digital immigrants, part II: Do they really think differently? On the Horizon, 9(6), 1–6. Ramble, P. (2012). Critical discourse analysis of collaborative engagement in Facebook postings. Australasian Journal of Educational Technology, 28(2), 295–314. Rowlands, I., Nicholas, D., Williams, P., Huntington, P., Fieldhouse, M., Gunter, B., Withey, R., Jamali, H.  R., Dobrowolski, T., & Tenopir, C. (2008). The Google generation: The information behavior of the researcher of the future. Aslib Proceedings, 60(4), 290–310. Rubinstein, J. S., Meyer, D. E., & Evans, J. E. (2001). Executive control of cognitive processes in task switching. Journal of Experimental Psychology. Human Perception and Performance, 27(4), 763–797. Seemiller, C. (2017). Curbing digital distractions in the classroom. Contemporary Educational Technology, 8(3), 214–231. https://doi.org/10.30935/ cedtech/6197 Shernoff, D.  J., Csikszentmihalyi, M., Schneider, B., & Shernoff, E.  S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158–176. https://doi.org/10.1521/ scpq.18.2.158.21860 Skok, K. (2019). No teacher without a student … A theoretical analysis and practical implications of educational changes in the era of digital natives. In M.  Kowalczuk-Walêdziak, A.  Korzeniecka-Bondar, W.  Danilewicz, & G.  Lauwers (Eds.), Rethinking teacher education for the 21st century: Trends, challenges, and new directions (pp. 111–126). Verlag Barbara Budrich. Skok, K., & Laszewicz, M. (2014). Usage problems innovative forms of teaching – Qualitative analysis of the classes conducted via Facebook. In M. Suswillo & N. A. Fechner (Eds.), Education of the 21st century. Entities, environments and educational areas. Challenges and threats of the middle of the 21st century (pp. 79–90). Higher Publishing House Security Schools. Smith, A. (2012a). The best (and worst) of mobile connectivity. Pew Research Center. http://pewinternet.org/Reports/2012/Best-­Worst-­Mobile.aspx

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Smith, E. E. (2012b). The digital native debate in higher education: A comparative analysis of recent literature. Canadian Journal of Learning and Technology, 38(3), 1–18. Tapscott, D. (1999). Educating the net generation. Educational Leadership, 56(5), 6–11.

CHAPTER 5

How Do Students and Teachers Respond to Digital Distraction in School?

Abstract  Students and teachers’ responses to digital distraction fluctuate depending on context and variables, so it is not surprising that stakeholders’ reactions are somewhat dependent on whether learning is happening synchronously or asynchronously, and whether the learning setting is in-­ person or remote. It is no surprise that digital distraction is having a major impact on academic performance (Ravizza et al., Computers & Education, 78, 109–114, 2014; Redner et al., Behavior Analysis: Research and Practice, https://doi.org/10.1037/bar0000158, 2019), but what is more concerning is how students, parents, teachers, and administrators are choosing to respond to digital distraction when students are learning and teachers are instructing. The idea of complete mitigation of digital distraction inside school, whether school is happening remotely or in-person, is not feasible, but choices regarding the minimization of digital distraction are far from where they need to be. Educating our student generation, a group of digital natives born into Web 2.0 technology, about the pitfalls of digital distraction and its effects on metacognition is a good starting point. Reinforcing these digital concerns with ongoing and targeted professional development for teachers and staff, coupled with meaningful digital policy across school districts, has to become the gold standard. Keywords  Remote learning • Asynchronous learning • Synchronous learning • 1:1 Learning • Digital literacy • Professional development • Academic performance • Self-regulation • Separation anxiety • Phone © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. C. Schuett, Beyond Digital Distraction, Digital Education and Learning, https://doi.org/10.1007/978-3-031-53215-3_5

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confiscation • Cybersecurity • Digital natives • Google Generation • Web 2.0 • Google Meet Some students do not believe mobile digital technology affects their academic performance (Ravizza et al., 2014; Redner et al., 2019), which this book’s research supports. These feelings of immunity to academic disengagement, coupled with students’ belief in the power of multitasking, sharply contradict teachers’ perceptions. Even though teachers disagree with students, stating that digital technology does influence academic performance, still many choose not to minimize distracted student behavior even when aware of it. Frustration with school digital policy and lack of its enforcement, along with the difficulties of managing mobile technology across synchronous and asynchronous in person, remote, and hybrid instructional settings, likely contribute to this frustration. Students and teachers both identify the importance of self-regulation when using mobile technology for learning, whether learning is happening inside a brick-and-mortar school or remotely from home. The complete mitigation of digital distraction in school, whether schooling is happening inside a traditional or hybrid setting, is unrealistic, but this book provides suggestions for managing it. First and foremost, increasing education over digital distraction for all stakeholders is a must. Adjusting digital literacy curriculum to include digital distraction as part of the student curriculum is another good first step. Providing teachers with professional development while sharing research/findings with parents is also a useful suggestion. Phone confiscation is not a popular choice pertaining to actions taken by school personnel, especially because it often causes separation-­anxiety for many students. But limiting digital device accessibility while increasing cybersecurity are measures school faculty and staff can take, which will likely be more supported by parents in the community. School leaders can also create a uniform digital policy that gives voice to all stakeholders, especially for “in school” learning, which will increase consistency, uniformity, and transparency for all parties involved. This study’s findings confirmed previous research that indicate some students do not believe their mobile digital device use affects their academic performance (Ravizza et al., 2014; Redner et al., 2019, p. 2). Some students felt immune to academic disengagement, claiming that schooling inside a 1:1 learning environment that requires school-issued Chromebooks created a sense of resiliency against digital distraction. Others believed

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their multi-tasking abilities gave them the aptitude to manage personal devices like cell phones without falling behind during class. As previously mentioned, today’s students are digital natives since they were born into the Google Generation, so their task-oriented mindset includes their perceived ability to multitask and multi-process while being attached to technology (Bennett et al., 2008; Joiner et al., 2013; Oblinger & Oblinger, 2005; Prensky, 2001a, 2001b; Skok, 2019; Smith, 2012a, 2012b; Tapscott, 1999). An interesting discovery this book posits is that even when certain participants, especially teachers, acknowledged the opposite sentiment that mobile devices do in fact affect academic performance, it did not cause them to minimize the distraction, even when they were aware of it. In addition, the literature also backs this finding. Even though certain technologies can enhance learning due to increased student interaction and engagement, many people often use these same electronic devices to engage in non-academic behaviors during class time (Bojinova & Oigara, 2013; Redner et  al., 2019, p.  1; Samson, 2010). Teachers, parents, and administration cannot blame adolescent students with undeveloped frontal lobes for inappropriate digital choices on school-­ issued devices. First, school districts are not only putting these devices into the hands of students, but schools are also mandating their use during remote learning. In addition, this study’s research also indicates a lack of soft skills education is provided for school children pertaining to their ongoing appropriate technology use during class. Schooling during the pandemic created a unique instructional situation for students and teachers since a lack of supervision, especially for high school students, was inevitable during remote learning. When students were learning from home, they did not have the same level of supervision during class since they were not physically present in school. Because of this, self-regulation became important, but asking adolescents to regulate their own behaviors when sitting in isolation was a big ask. Alice, a high-­ performing student at the case site, acknowledged this problem, “So, my class rank is number one at the moment, so I know my level of self-regulation, having attention, and being focused may not be universal. I cannot infer other students have the same self-regulation as what I potentially have” (Interview 2). Keith, a senior, discussed in his second interview how the lack of parental supervision at home, coupled with students not being required to have cameras and mics on during Google Meet sessions, increased the potential for digital distraction. Additionally, all three participating teachers identified the lack of parental supervision and the

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likelihood their children were becoming digitally distracted during both synchronous and asynchronous instruction. Mr. Holland, a decorated science teacher who is also a parent, was empathetic toward parents’ situation, especially since most parents were struggling to work their own jobs throughout the pandemic. Even so, Mr. Holland advised parents to be careful not to set their kids up “…for more severe repercussions as they become older” (Interview 2). The nature of remote learning, whether it was happening for students on a daily or modified basis, presented an array of challenges in maintaining focus and engagement during learning. Interestingly, prior research stated how the largest declines in motivation might be occurring inside classes that use a lot of technology (Patall et al., 2018). This was a significant consideration for inclusion in this book since all participants were conducting the entirety of their learning, whether in-person or remote, on mobile digital technology (i.e., Chromebooks). Teachers and parents struggled to foster much needed intrinsic motivation for students because of the unique learning settings and their impact on extended focus and engagement, which in turn affected students’ metacognition and learning transfer, two important elements of cognitivism (Bandura & Walters, 1977; Bandura, 1994, as cited in Bélanger, 2011; Gagné, 1985). Keith, another graduating senior at the top of his class, felt that it depended on how much each individual student cared about her/his educational career. If “getting good grades, getting a good career in life and all that” (Keith, Interview 2) was something students valued inside their quality worlds, then they would be more likely to minimize digital distraction in order to maintain focus during class, even when class was conducted over mobile technology. Participants felt that actions taken by teachers and school officials (e.g., phone confiscation, lockdown browsers, closing multiple tabs, increased cybersecurity, incentives, verbal cues), coupled with policy changes (i.e., consistency, uniformity, transparency) and compromise between all stakeholders regarding digital distraction, might help increase student focus and engagement during both in-person and remote learning. These findings provided meaningful answers for this sub-question. As cited in the literature, even though some academic settings allow open usage (Lam & Tong, 2012), most school and learning environments do not allow unlimited access and free open use of digital devices inside instructional environments. Granted, these suggested actions would therefore likely work best during in-person class sessions as compared to the often-unsupervised remote learning setting, which was happening at home during COVID-19.

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Research does suggest that 1:1 learning is student-centered and results in improved writing, engagement, information literacy, and test scores (Blikstad-Balas & Davies, 2017; Warschauer & Ames, 2010). However, that research was conducted when 1:1 in-person learning environments were housed physically inside a school building and not in remote learning settings like these participants experienced during COVID-19. One important way in which participants responded to digital distraction in classrooms and school was through the suggestions they offered. While participants gave a variety of recommendations that could potentially help to minimize digital distraction while learning, they felt that complete mitigation of digital distraction during both in-person and remote learning was improbable and unrealistic. Even if stakeholders cannot fully eradicate digital distraction, certain suggestions provided by participants could help to strengthen focus and engagement during learning. This addressed the fourth research sub-question for this book since I was interested in discovering how participants responded to digital distraction during class. Participants suggested that learning setting, digital device proximity, and limiting mobile digital device accessibility during both in-person and remote learning could help to minimize the extent of digital distraction students and teachers deal with during cycles of learning. When students and teachers conduct school in settings that are conducive to learning, in settings with fewer digital and non-digital distractions, focus is maintained for lengthier periods. Additionally, when the accessibility of mobile digital devices is limited, users become less distracted. Participating students and teachers also suggested that self-awareness, self-regulation, and increased parental supervision of digital device use, especially during remote learning, might help to minimize digital distraction during learning. Even though parental supervision is already extensively mentioned throughout this book, here it specifically relates to the supervision of digital devices themselves. The nature of remote learning is individualistic by default. Additionally, student-participants were high school students. This suggests that parents would have been more likely to leave students in this age group unattended at home rather than elementary school aged students. Because of this lack of supervision, high school students had to rely more on intrinsic than extrinsic motivation: an important step in fostering engagement (Bartholomew et  al., 2011; Haerens et al., 2015; Patall et al., 2013, 2018; Reeve & Jang, 2006) because they are often left unsupervised during remote learning. This is significant to

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note since the importance of motivation and engagement to the learning and achievement cycle is well documented (Archambault, et  al., 2009; Hughes et  al., 2008; Lepper et  al., 2005; Murayama et  al., 2013; Willingham et al., 2002; Patall et al., 2018). One of the foundations of engagement theory is active learning inside an academic setting (Reeve et al., 2004; Skinner et al., 2009; Wang et al., 2014). Tapping into students’ intrinsic motivation was difficult to accomplish during pandemic schooling for a variety of reasons, especially since active learning was hard for students and teachers to accomplish in hybrid and remote instructional settings. Even though we are cycling out of the height of COVID-19, many school districts still offer remote and/or hybrid learning. Because of this, stakeholders must be aware of the difficulty in motivating groups of students when they are learning remotely, wherever that may be. This needs to be addressed across the board as some schools are still looking to normalize this kind of remote 1:1 learning because ignoring the data will only lead to more learning transfer mishaps and knowledge retention pitfalls. Students were brazenly honest in their suggestions about proximity and self-awareness, not only for other students but also for teachers. The majority of students believed that when mobile devices were out of sight, there was less temptation to check them. Students offered this same solution for teachers, identifying the importance of device proximity and digital distraction. Bobby, a freshman student who enjoys engaging in scholastic debate, said, “If I were a teacher, I would just try and completely forget about being digitally distracted. You know, out of sight, out of mind. What I’d do is put my cell phone in my backpack and just forget about it” (Interview 2). Another freshman student, Marcia, agreed with Bobby, “When they are teaching me next year, for example, making their phones not visible to them, like putting them in your bag. You’re literally teaching, so you’ll be less likely to stop class and take it out of your bag to look at it” (Interview 2). Marcia’s comments illustrate that proximity is not simply a student issue, as teachers fall victim to checking mobile technology during class too. Simone, an outspoken junior, put it best by saying, “I think maybe having like their phones away inside their desk, or putting it away in a bag that they carry around with them so that they’re setting the example that digital distraction in class is not okay” (Interview 2). From students’ shared observations, we can see that teachers and other instructional staff need to continue to model appropriate digital device etiquette if students are expected to do the same.

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From the pool of participant suggestions, phone confiscation was not a popular solution offered by either students or teachers. Ironically, students believed the confiscation of phones could actually trigger more stress and anxiety for students, causing a further disconnect in both focus and engagement during class. Cindy, a freshman, also felt that calling out students in front of classmates is not what teachers should be doing either, “Not calling out the student in class. That increases anxiety and embarrassment” (Interview 2). A different participant, Jan, an underclass honors student, stated how educating students on the effects of digital distraction could have meaningful long-term effects, I guess that they could if there’s like studies about how digital distraction affects attention and learning, I guess, like show us. So, provide more education. We don’t really talk about it other than when teachers say, “Don’t use your phones,” but they don’t really explain why. I think that’s why a lot of kids think, “What’s wrong with using my phone?” (Jan, Interview 2)

Good pedagogy teaches the importance of explaining “the why,” especially since some students might feel that teachers should be modeling the same appropriate digital device etiquette during learning. This, in turn, could foster positive lines of communication between students and teachers, which would then help to improve focus and engagement during class. Students and teachers were both on the same page about increasing cybersecurity and maintaining uniform mobile device policy at school. Students and teachers suggested some simple actions school officials could take to lessen the potential for distraction, like removing instant messaging for students through G-chat and blocking YouTube during normal school hours. Creating a uniform digital policy that gives voice to all stakeholders involved (students, parents, faculty, staff, and administration) was an important takeaway. Unfortunately, the enforcement of tech policy in a remote setting could be difficult to accomplish, but participants believe digital policy for “in school” learning should be uniform across one’s district. Again, this might be an argument in favor of hive mentality because when digital device policy is misaligned between different classrooms and teachers inside a school building, students and teachers both struggle to maintain and manage focus and engagement during learning. Mr. Holland identified variances in cellphone policy that created a “Wild West” of sorts in school, frustrating students and teachers alike because what some considered “appropriate” cell phone etiquette in one classroom or part of the

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building was different in others. School districts need to do a better job of addressing variances like this because the “all in” mentality regarding in-­ school technology use (i.e., when and where it is appropriate to use technology during school hours) may be the single most important collective decision districts can make in the protection of focus and engagement when learning.

References Archambault, I., Janosz, M., Fallu, J. S., & Pagani, L. S. (2009). Student engagement and its relationship with early high school dropouts. Journal of Adolescence, 32, 651–670. Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York Academic Press. Bandura, A., & Walters, R. H. (1977). Social learning theory (Vol. 1). Prentice Hall. Bartholomew, K.  J., Ntoumanis, N., Ryan, R.  M., Bosch, J.  A., & Thǿgersen-­ Ntoumani, C. (2011). Self-determination theory and diminished functioning: The role of interpersonal control and psychological need thwarting. Personality and Social Psychology Bulletin, 37, 1459–1473. https://doi. org/10.1177/0146167211413125 Bélanger, P. (2011). Learning theories: Discussion. In Theories in adult learning and education (pp.  49–52). Verlag Barbara Budrich. http://www.jstor.org/ stable/j.ctvbkjx77.8 Bennett, S., Maton, K., & Kervin, L. (2008). The “digital natives” debate: A critical review of the evidence. British Journal of Educational Technology, 39(5), 775–786. Blikstad-Balas, M., & Davies, C. (2017). Assessing the educational value of one-­ to-­one devices: Have we been asking the right questions? Oxford Review of Education, 43(3), 311–331. Bojinova, E., & Oigara, J. (2013). Teaching and learning with clickers in higher education. International Journal on Teaching and Learning in Higher Education, 25, 154–165. https://www.learntechlib.org/p/130700/ Gagné, R. (1985). The conditions of learning and theory of instruction. CBS. Haerens, L., Aelterman, N., Vansteenkikiste, M., Soenens, B., & Van Petegem, S. (2015). Do perceived autonomy-supportive and controlling teaching relate to physical education students’ motivational experiences through unique pathways? Psychology of Sport and Exercise, 16, 26–36. https://doi.org/10.1016/j. psychsport.2014.08.013 Hughes, J. N., Luo, W., Kwok, O.-M., & Loyd, L. K. (2008). Teacher-student support, effortful engagement, and achievement: A 3-year longitudinal study.

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Journal of Educational Psychology, 100, 1–14. https://doi.org/10.1037/ 0022-­0663.100.1.1 Joiner, R., Gavin, J., Brosnan, M., Cromby, J., Gregory, H., Guiller, J., Maras, P., & Moon, A. (2013). Comparing first and second-generation digital natives’ internet use, internet anxiety, and internet identification. Cyberpsychology, Behavior, and Social Networking, 16(7), 549–552. Lam, P., & Tong, A. (2012). Digital devices in classroom: Hesitations of teachers-­ to-­be. Electronic Journal of E-Learning, 10(4), 387–395. Lepper, M. R., Corpus, J. H., & Iyengar, S. S. (2005). Intrinsic and extrinsic motivational orientations in the classroom: Age differences and academic correlates. Journal of Educational Psychology, 97, 184–196. https://doi. org/10.1037/0022-­0663.97.2.184 Murayama, K., Pekrun, R., Lichtenfeld, S., & Vom Hofe, R. (2013). Predicting long-term growth in students’ mathematics achievement: The unique contributions of motivation and cognitive strategies. Child Development, 84, 1475–1490. https://doi.org/10.1111/cdev.12036 Oblinger, D., & Oblinger, J. (2005). Educating the net generation. https://www. educause.edu/ir/library/pdf/pub7101.pdf Patall, E. A., Dent, A. L., Oyer, M., & Wynn, S. R. (2013). Student autonomy and course value: The unique and cumulative roles of various teacher practices. Motivation and Emotion, 37, 14–32. https://doi.org/10.1007/s11031-­ 012-­9305-­6 Patall, E.  A., Steingut, R.  R., Vasquez, A.  C., Trimble, S.  S., Pituch, K.  A., & Freeman, J. L. (2018). Daily autonomy supporting or thwarting and students’ motivation and engagement in the high school science classroom. Journal of Educational Psychology, 110(2), 269–288. https://doi.org/10.1037/ edu0000214 Prensky, M. (2001a). Digital natives, digital immigrants. On the Horizon, 9(5), 1–6. Prensky, M. (2001b). Digital natives, digital immigrants, part II: Do they really think differently? On the Horizon, 9(6), 1–6. Ravizza, S. M., Hambrick, D. Z., & Fenn, K. M. (2014). Non-academic internet use in the classroom is negatively related to classroom learning regardless of intellectual ability. Computers & Education, 78, 109–114. https://doi. org/10.1016/j.compedu.2014.05.007 Redner, R., Lang, L.  M., & Brandt, K.  P. (2019). Evaluation of an electronics intervention on electronics use in a college classroom. Behavior Analysis: Research and Practice. https://doi.org/10.1037/bar0000158 Reeve, J., & Jang, H. (2006). What teachers say and do to support students’ autonomy during a learning activity. Journal of Educational Psychology, 98, 209–218. https://doi.org/10.1023/B:MOEM.0000032312.95499.6f

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Reeve, J., Jang, H., Carrell, D., Jeon, S., & Barch, J. (2004). Enhancing students’ engagement by increasing teachers’ autonomy support. Motivation and Emotion, 28, 147–169. Samson, P. J. (2010). Deliberate engagement of laptops in large lecture classes to improve attentiveness and engagement. Computers & Education, 1, 1–19. Skinner, E.  A., Kindermann, T.  A., Connell, J.  P., & Wellborn, J.  G. (2009). Organizational constructs in the dynamics of motivational development. In K.  Wentzel & A.  Wigfield (Eds.), Handbook of motivation at school (pp. 223–245). Lawrence Erlbaum. Skok, K. (2019). No teacher without a student… A theoretical analysis and practical implications of educational changes in the era of digital natives. In M.  Kowalczuk-Walêdziak, A.  Korzeniecka-Bondar, W.  Danilewicz, & G.  Lauwers (Eds.), Rethinking teacher education for the 21st century: Trends, challenges, and new directions (pp. 111–126). Verlag Barbara Budrich. Smith, A. (2012a). The best (and worst) of mobile connectivity. Pew Research Center. http://pewinternet.org/Reports/2012/Best-­Worst-­Mobile.aspx Smith, E. E. (2012b). The digital native debate in higher education: A comparative analysis of recent literature. Canadian Journal of Learning and Technology, 38(3), 1–18. Tapscott, D. (1999). Educating the net generation. Educational Leadership, 56(5), 6–11. Wang, Z., Bergin, C., & Bergin, D. A. (2014). Measuring engagement in fourth to twelfth grade classrooms: The classroom engagement inventory. School Psychology Quarterly, 29(4), 517–535. https://doi.org/10.1037/spq0000050 Warschauer, M., & Ames, M. (2010). Can one laptop per child save the world’s poor? Journal of International Affairs, 64, 35–51. Willingham, W. W., Pollack, J. M., & Lewis, C. (2002). Grades and test scores: Accounting for observed differences. Journal of Educational Measurement, 39, 1–37.

CHAPTER 6

What Types of Experiences Do Students and Teachers Have with Digital Distraction in School?

Abstract  One of the initial strengths of 1:1 learning was its ability to foster greater collaboration. For example, students and teachers were able to electronically cooperate through certain apps like Google Docs when working on their writing. But remote learning during Covid was a game-­ changer, and the lack of quality collaboration during learning time was a major problem stakeholders experienced. In addition to this lack of quality collaboration, time-management for self-paced learning and students and parents’ over-reliance on multitasking compounded digital distraction, especially during asynchronous learning. Not to mention, the definitive lack of student supervision during remote learning, coupled with the aforementioned examples, all created and sustained extended periods of unfocused learning. Synchronous in-person learning was not without its own problems, though. Students and teachers suffered bouts of digital distraction even when learning physically together in person. Unsurprisingly, these distractions stemmed from social media, gaming, and communication with friends (e.g., texting). Interestingly, one of the greatest instigators of digital distraction during in-person learning arose from communication with family, which might not be too surprising for adult teachers, many of whom are parents. But the amount of incoming communication in the form of texts from parents to students during class time is a definitive concern, especially if focused attention during learning is ever to occur.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024 K. C. Schuett, Beyond Digital Distraction, Digital Education and Learning, https://doi.org/10.1007/978-3-031-53215-3_6

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Keywords  Asynchronous learning • Synchronous learning • Texting • Social media • Pandemic • Self-paced learning • Face-to-face learning • Social-emotional learning • Videoconferencing • Self-reporting interactive frequency log Digital distraction diverts attention and focus during class for non-­ academic activities during synchronous and asynchronous learning. Asynchronous work, especially in “remote” learning, has greater potential for distraction and less engagement than synchronous work. Some of the most common problems associated with asynchronous learning include time management for self-paced learning, lack of supervision during remote learning, student and parent over-reliance on multitasking, and lack of collaboration. Synchronous learning is not without its own problems and challenges, too. All avenues of communication, whether teacher-to-student, student-­ to-­student, student-to-parent, or teacher-to-parent, suffer at times due to mobile digital technology, especially when school districts and students’ households allow open access to certain apps and platforms when instruction is occurring. In this study, both students and teachers shared experiences that expressed how digital distraction diverts attention and focus from learning for non-academic activities. These types of activities often included communicating with family and friends through texting on personal cell phones. In addition to texting, participants stated that students routinely conducted non-academic communication during learning through social media apps like Snapchat. Shirley, a graduating senior, witnessed classmates routinely communicating through text and social media apps during class. Another graduating senior, Keith, noted how these digital conversations often spilled outside of the classroom into hallways and other parts of the school. Cindy, a freshman student, even referenced how her mother did not allow her to download the Snapchat app until she graduated from junior high because of its potential for distraction. This book has already provided an array of perspectives, each of which help to answer the final overarching research question of “What types of experiences do teachers and students have with digital distraction inside the school setting?” Because of this, the final section’s concentration will center on the two types of learning participants experienced throughout the pandemic: synchronous learning and asynchronous learning.

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Throughout this inquiry into digital distraction, both students and teachers identified the impact of asynchronous and synchronous work during learning. When restrictions started to loosen during the COVID-19 pandemic, this case site instituted a hybrid class schedule where students were allowed to attend class “in person” up to four times a week. Students could also choose to come for in-person learning for just 2 days a week or stay entirely at home. No matter which schedule students selected at the case site, all students and teachers were required to work remotely from home on Wednesdays so a deep cleaning of the building and grounds could be conducted. When students and teachers were “at home” on Wednesdays, or for students who opted to stay home remotely for the other days of the week, school leadership allowed asynchronous instruction and learning to be an option for students and teachers. Participants cited that both asynchronous and synchronous work affected focus and engagement during learning, but the impact was typically greater when students and teachers were instructing and learning remotely from locations outside of the brick-and-mortar school building. Even though participating students and teachers both felt that synchronous and asynchronous learning affected focus and engagement, most participants believed that asynchronous work, especially in remote learning settings, had a greater potential for distraction and less engagement during learning than synchronous work did. Instructional factors like self-­ paced learning, coupled with certain phenomenological factors (i.e., instructional relevance and perceived control), could have led to less buy­in from students when conducting asynchronous academic work they felt was not authentic (Shernoff et al., 2003). The literature states the importance of facilitating informal learning beyond the typical classroom setting (Breen, 2018; Cook & Pachler, 2012; Kennedy et al., 2017), but participants felt like this could not be achieved due to the lack of authenticity in asynchronous work during the COVID-19 pandemic. Students and teachers both said the primary reasons for this were that many students struggled with time management for self-paced learning, coupled with a lack of supervision during at-home learning. Some student-participants felt that multitasking could help manage self-paced learning across asynchronous channels; however, multitasking is only beneficial for low-hanging academic tasks (Kahneman, 2011). Too often multitasking leads to insignificant chunks of knowledge and educational mistakes (De Neys, 2006; Skok, 2019). This finding provides important insight into how students and teachers respond to the digital distractions that occur during

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instructional class time and the contributing factors to these digital distractions. Because of time-management lapses, in conjunction with extended unsupervised periods in a learning setting that likely had more digital devices in close proximity for users to become distracted on, remote asynchronous learning was a struggle for many students during the pandemic. Tracy, a straight-A sophomore student with immigrant parents, discussed the difficulty with self-paced independent work, “But if the class is more self-paced, and they just rely on you to do your own work, then it’s easier to get caught up in other distractions like your phone and losing track of what you’re trying to learn. Yeah, I feel it’s easier to become distracted during asynchronous work because it’s self-paced” (Interview 1). Jan reinforced this confusion many students felt, especially when classes were not meeting on a regular basis, “But it is a little bit confusing, especially with health class because we only get to do health once a week, and it’s completely remote where other classes you have for a few days. It’s just hard to work and not procrastinate and manage time a lot more than if we were just completely in school” (Interview 1). Another student named Cindy, a multilingual freshman, discussed how hard it was for visual learners in a remote setting, So, it works better when learners are “in person” versus “remote.” I’m a visual learner, more like I can’t learn anything unless I have it in front of me and like someone’s teaching me. I cannot just look at a video. (Interview 2)

Social studies teacher Mr. Keating identified the lack of collaboration between all stakeholders during asynchronous work as being a functional obstacle, I would say the biggest thing is the lack of collaboration in terms of teaching. And then functionality, there’s just a lot that’s different, too. But yeah, everything this year has felt very much more individual, like you’re doing everything by yourself… (Interview 2)

Working inside the asynchronous vacuum was a unique experience for all educational stakeholders during COVID. From this inquiry’s shared perspectives, readers can discern that asynchronous learning would not be the primary choice for most students and teachers, whether the context is happening during a pandemic or not. Even though asynchronous learning was a more challenging experience for students, synchronous learning was not without its own distractions.

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Alice, a multilingual student who is among the top of her class, defined synchronous learning as, “An environment in which the teacher interacts with students, focuses on their wellbeing and their understanding of the class, and asks questions to ensure they’re engaged. Just the teacher-to-student communication going on inside the classroom” (Interview 1). Interestingly, Alice felt caught off guard when she first reported to school for synchronous learning during the pandemic because she expected it to be closer to her shared definition. It was not. When I was first coming to school for “in person” learning, I was expecting more teacher-to-student communication to be going on, but it was exactly the same thing as at home learning since teachers had to adapt to the situation and still needed to focus on the students at home. So, we were basically doing the same thing we did at home, but I felt more engaged in the classroom since I didn’t have as many distractions around me. (Alice, Interview 1)

Even though Alice was not pleased with the instructional delivery of her lessons, she at least felt more engaged when physically present inside a classroom setting. This poses a consideration for future studies when comparing “in person” versus remote synchronous instruction because face-­ to-­face virtual learning may not afford students the same social-emotional engagement that learning inside a brick-and-mortar classroom does. Since students at this site learn in a 1:1 environment on school-issued Google Chromebooks, students have instant access to everything the Chromebook offers that is not blocked by school cybersecurity. Students and teachers acknowledged a series of open apps that participants used to become digitally distracted on, even during synchronous learning. Some of these applications included Google Chat (G-chat), a form of instant messenger on one’s Google email account, Google Docs, and Google Meet, which is a videoconferencing application similar to Zoom. Ms. Johnson, a tenured mathematics teacher who is open-minded about digital technology, stated how there was just less instruction and learning achieved during synchronous sessions operating throughout the pandemic. She described how students often procrastinated during synchronous learning sessions because they felt like they could catch up and “get it done later” during asynchronous learning time. This simply compounded stress for both students and teachers, both in terms of shortterm achievement (i.e., formative assessments), long-term achievement (i.e., summative assessments), planning, and classroom management.

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One of the most interesting data collection methods for this book that illustrated participant experiences with digital distraction was the self-­ reporting interactive frequency log that each participant completed over the course of 2 instructional days for a preselected period 2 class. Both student and teacher participants completed this interactive log by hand to reduce the chance for increased digital distraction. The log, which was formatted as a checklist, allowed participants to track the type and frequency of digital distraction. Because participants were in the midst of pandemic learning, each student and teacher tracked their data on subsequent in-person and remote learning days with academic periods that lasted 75 minutes. The majority of case study participants completed both days of the interactive frequency log. The purpose of the log was for triangulation. Trends shown from these self-reporting logs matched patterns that emerged from the primary interview source data. In addition to identifying the class, grade level, day of the week, and learning location, participants had to identify the type and tally the frequency of each kind of digital distraction. Participants had nine different categories of digital distraction to choose from: cell phone, iPad or tablet, school-issued Chromebook, personal computer/laptop, television, smart watch, gaming system (i.e., Xbox, PlayStation, Nintendo Switch), virtual assistant AI technology (i.e., Amazon Alexa, Amazon Echo), and other (i.e., digital netbook, digital media player). The pie charts provided over the next several pages illustrate these trends. Eleven of the twelve student-participants opted to complete the self-reporting logs while all three teachers participated. Figure 6.1 illustrates how student-participants identified three different devices they experienced being digitally distracted by during in-person learning: cell phones, school-issued Google Chromebooks, and smartwatches. Of the 107 tally marks, 60 were cell phones (56%), 25 were Google Chromebooks (23%), and 22 were smartwatches (21%). Therefore, the majority of student-participants identified the cell phone as the most popular device for digital distraction during in-person learning. This data point reinforced the interview data, which showed the cell phone as the most likely digital device for students to become distracted with at school. All three teachers participating in the case study contributed to the interactive frequency log (see Fig. 6.2). Similar to students, teacher-participants identified the cell phone and Chromebook as devices they became digitally distracted with during in-person learning. Unlike students,

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Fig. 6.1  This chart illustrates the digital distraction frequency for in-person student learning during a 75-minute instructional period

teachers did not select the smartwatch as a likely device to become digitally distracted with during in-person learning. Instead, teachers picked the personal computer or laptop. From the 72 data points, there were 38 tallies for Google Chromebooks (53%), 27 tallies for cell phones (38%), and 7 tallies for personal computers or laptops (10%). When comparing teachers’ frequency charts against student-participants, school-issued Google Chromebooks were a greater source of digital distraction for teachers at school, whereas the cell phone was a greater source of personal digital distraction for in-person learning for students. Since learning requires the collaborative efforts of both students and teachers, Fig. 6.3 provides a visual representation into the combined frequency of digital distraction for in-person learning for both sets of stakeholders: students and teachers. When combining the 179 data points,

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Fig. 6.2  This chart illustrates the digital distraction frequency for in-person teacher learning during a 75-minute instructional period

there were 87 instances of cell phone distraction (49%), 63 occurrences of Chromebook distraction (35%), 24 smartwatch distractions (13%), and 7 personal computer/laptop distractions (4%). Since there were only 3 teacher-participants, compared to 11 participating students, and because each group selected a different device for the third type of digital distraction, these percentages were likely not as relevant as those for the cell phone and school-issued Chromebook. This supported the primary data source findings from the semi-structured in-depth interviews. Specifically, participants felt that cell phone and school-issued Google Chromebooks were the two most likely mobile digital devices students and teachers became digitally distracted by during in-person learning. A unique element of this book’s study is the fact that it was conducted during the COVID-19 pandemic. Because of this, stakeholders attended school with a hybrid schedule. Just as the previous figures illustrated digital distraction frequency for in-person learning, case study participants also logged the types and rates of digital distraction they experienced when

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Fig. 6.3  This chart illustrates the combined digital distraction frequency for in-­ person student and teacher learning during a 75-minute instructional period

learning remotely from home or other non-school locations. Of the 12 student-participants, 11 opted to submit their self-reporting logs for analysis (see Fig. 6.4). One of the first trends shown was the increase in digital distraction when learning remotely. This supports findings from the interview source data that the risk of digital distraction was greater during at-­ home learning. Specifically, the interview data showed how student-participants felt that digital distraction was more likely to occur during remote at-home learning since it was usually unsupervised. Students identified 7 different types of digital distraction occurring at home: 100 instances for cell phones (60%), 19 occurrences on Google Chromebooks (11%), 17 distractions on video game consoles (10%), 15 occurrences on smartwatches (9%), 8 distractions on TVs (5%), 4 instances on personal computers or laptops (2%), and 4 distractions on iPads or tablets (2%). Similar to the collected interview data, cell phones and Chromebooks were still the two most popular digital devices to become distracted on whether learning was occurring at school or remotely from home. In

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Fig. 6.4  This chart illustrates the digital distraction frequency for remote student learning during a 75-minute instructional period

addition, the self-reporting logs also indicated that students became distracted on twice the number of potential devices at home as they did at school, which was also supported by the primary interview source data. When teachers logged the frequency of digital distraction from home during remote learning (see Fig. 6.5), cell phone distraction became more of a disruption. The Chromebook was more of a disruption at school. Other than this difference, teachers experienced the same three devices during remote learning that were included for in-person learning, in addition to including the television. Interestingly, teachers logged fewer digital distractions when working remotely from home than at school, but this anomaly may have stemmed from in-person learning because teachers were simultaneously juggling classroom management for both in-person

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Fig. 6.5  This chart illustrates digital distraction frequency for remote teacher learning during a 75-minute instructional period

and remote students. Of the 46 collected data points, 22 were for cell phones (49%), 14 for school-issued Google Chromebooks (30%), 9 for personal computers/laptops (20%), and 1 instance of television distraction (2%). Again, teacher-participants’ collected data for remote learning supported the interview data pattern that cell phones and Chromebooks were the two most popular devices for stakeholders to become distracted on when learning from home. The final figure (Fig. 6.6) includes both student and teacher totals for digital device frequency during remote learning. From the combined 213 total data points, 7 different digital devices were identified: 122 cell phone distractions (57%), 33 school-issued Google Chromebook distractions (15%), 17 video game distractions (8%), 15 smartwatch distractions (7%), 13 personal computer/laptop distractions (6%), 9 television distractions (4%), and 4 iPad or tablet distractions (2%). Again, the participant frequency data for remote learning supported this inquiry’s finding that cell phones and Chromebooks were the most popular devices for digital

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Fig. 6.6  This chart illustrates the combined digital distraction frequency for remote student and teacher learning during a 75-minute instructional period

distraction during remote learning, and that digital distraction occurred more frequently during remote learning. In tandem with the self-reporting logs (secondary source data) and in-­ depth semi-structured interview data (primary source data), a formal research journal helped to triangulate this study’s collected findings. The research journal was ongoing and provided an organizational system through which the primary researcher could experience participant input through reflection. The formal research journal also allowed for the reflection of potential biases and the revisiting of findings as needed.

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References Breen, P. (2018). Resources and technology use. In Developing educators for the digital age: A framework for capturing knowledge in action (pp.  101–114). University of Westminster Press. http://www.jstor.org/stable/j.ctv5vddjh.10 Cook, J., & Pachler, N. (2012). Online people tagging: Social (mobile) network(ing) services and work-based learning. British Journal of Educational Technology, 43(5), 711–725. De Neys, W. (2006). Dual processing in reasoning: Two systems but one reasoner. Psychology Science, 17(5), 428–433. Kahneman, D. (2011). Thinking fast and slow. Farrar, Straus & Giroux. Kennedy, E., Neumann, T., Rowett, S., & Strawbridge, F. (2017). Digital education and the connected curriculum: Towards a connected learning environment. In B.  Carnell & D.  Fung (Eds.), Developing the higher education curriculum: Research-based education in practice (pp. 188–202). UCL Press. Shernoff, D.  J., Csikszentmihalyi, M., Schneider, B., & Shernoff, E.  S. (2003). Student engagement in high school classrooms from the perspective of flow theory. School Psychology Quarterly, 18(2), 158–176. https://doi.org/10.1521/ scpq.18.2.158.21860 Skok, K. (2019). No teacher without a student… A theoretical analysis and practical implications of educational changes in the era of digital natives. In M.  Kowalczuk-Walêdziak, A.  Korzeniecka-Bondar, W.  Danilewicz, & G.  Lauwers (Eds.), Rethinking teacher education for the 21st century: Trends, challenges, and new directions (pp. 111–126). Verlag Barbara Budrich.

CHAPTER 7

Implications for Theory and Research

Abstract  Since this book’s findings focus on stakeholder (i.e., students and teachers) engagement during learning, this chapter provides insight into the three predominant types of engagement analyzed during this case study analysis: behavior engagement, cognitive engagement, and emotional engagement. Findings indicate the importance of all three types of engagement. Case in point, behavioral engagement includes stakeholder actions like time on task, classroom participation, and questioning, behaviors that can all derail learning focus and engagement inside any learning setting. Likewise, emotional engagement (i.e., interest, enjoyment, and enthusiasm) works in tandem with behavioral engagement to foster meaningful and active learning, which culminates in increased cognitive engagement as students and teachers’ academic concentration and cognitive processing improves metacognition. Five themes emerged from this study: loss of learning focus and engagement due to digital distraction, most popular devices used for digital distraction during learning, non-digital and digital influences on digital distraction when learning, digitally distracted behaviors during both synchronous and asynchronous learning, and the difficulties in mitigating digital distraction when learning. Subsequently, one of this book’s biggest takeaways is the importance of creating meaningful digital policy regarding the use and misuse of mobile technology in school.

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Keywords  Multilingual learner • Digital policy • Traditional 1:1 learning • Hybrid schedule • Cognitive variance in learning • Behavioral interventions • Learning interventions • Affective (emotional) engagement • Behavioral engagement • Cognitive engagement • Cognitivist theory • Digital instructional approaches • Non-digital instructional approaches 1:1 learning increased across the globe with COVID-19, and this warranted more attention about fostering relationships with behavior, thinking, and learning engagement among educational stakeholders. Moving forward, more research is needed to better understand how to manage emotional, behavioral, and cognitive engagement when actively learning (Reeve et al., 2004; Skinner et al., 2009a, b; Wang et al., 2014), whether learning is happening remotely or in person. As mentioned previously, there is a failure by teachers to minimize digital distraction during learning, even when aware of it. This presents an interesting quandary for digital policy makers: Since so many schools are requiring 1:1 learning on mandated school-issued devices, should students be punished for non-­ academic digital choices, especially when a lack of ongoing “soft skills” education for appropriate technology use during learning is evident? Probably not, so stakeholders inside school districts need to figure this out if equitable digital policy is ever to take root. This seismic shift in traditional 1:1 learning, primarily because of COVID-19, prompted other significant considerations, too. Educational stakeholders must continue to learn how to best adapt in order to plan and prepare for supporting the inner cognitive processes of students inside these evolving 1:1 learning environments. In order to do this, educational stakeholders need better to understand how students and teachers envision digital distraction when learning. Additionally, these same educators need to reflect over these shared cognitive variances and unique learning struggles (Allal, 1998, and Astolfi, 1997, as cited in Bélanger, 2011), both of which can occur due to lapses in focus and engagement when using digital technology during class. Educational researchers have stated that engagement often fosters relationships with behavior and learning interventions (Finn & Zimmer, 2012). Learning engagement inside the classroom, whether the classroom is physically inside a school building or remotely located at home or in another non-traditional setting, is multidimensional in nature when

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coupled with targeted cooperative and digital learning activities (Christenson et  al., 2012; Fredricks et  al., 2004; Skinner et  al., 2008, 2009a, 2009b; Muenks et  al., 2017). Subsequently, a one size fits all approach is problematic from the onset. In addition, sometimes the use of technology is required, especially when learning remotely, so educational stakeholders are already behind the eight ball from the get go when attempting to manage distraction on digital devices. But if certain management strategies and learning expectations can be fostered and implemented during “in person” learning, maybe some positive fallout could be more student self-­ management on digital technology when learning remotely. Throughout this knowledge pursuit, participant perspectives reinforced the importance of engagement as part of the learning process. Participant feedback regarding engagement was not limited to students. The impact of engagement for teachers was just as important as it was for students, especially when participants were conducting remote learning outside of the traditional school building. Since classroom engagement equates to students actively learning inside an academic setting (Reeve et al., 2004; Skinner et al., 2009; Wang et al., 2014), the COVID-19 pandemic introduced a new and truly unique active learning environment set outside the traditional brick-and-mortar school building that was universal in scope. Because engagement can be organized into three sub-categories, affective (emotional), behavioral, and cognitive (Archambault et  al., 2009; Fredricks et  al., 2004; Wang et  al., 2014), students and teachers were tasked with the challenge of not only triggering engagement, but also sustaining it inside two vastly different learning settings throughout the COVID-19 pandemic, which was a significant undertaking since this presented the first time in educational history where the majority of school systems across the globe had to operate remotely for an extended period. Educational stakeholders had to simultaneously juggle emotional engagement (i.e., interest, enjoyment, enthusiasm), behavior engagement (i.e., time on task, classroom participation, questioning), and cognitive engagement (i.e., cognitive processing, concentration, metacognition) in two uniquely different learning settings without much experience, which makes the findings posited inside this book significant. After analyzing this case’s data, five unique themes emerged from the findings: loss of learning focus and engagement due to digital distraction, most popular devices used for digital distraction when learning, non-digital and digital influences on digital distraction when learning, digital

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distraction during synchronous and asynchronous learning, and difficulties of mitigating digital distraction when learning. Engagement played a significant role in each of these five themes. Participants felt that the definition of digital distraction included the loss of engagement for non-academic purposes during both in-person and remote learning. Students and teachers felt that cell phones and school-issued Google Chromebooks were both catalysts for initiating and sustaining breaks in engagement during the learning process. Additionally, participating students and teachers believed that a combination of digital and non-digital contributors affected engagement, all of which influenced stakeholders’ emotional, behavioral, and cognitive engagement during learning. The digital medium provided an opportunity for students and teachers to engage in learning that was outside the typical instructional circle (Kennedy et al., 2017), but this was done out of necessity not choice because of the pandemic. Because all learning during this case study occurred over a hybrid schedule, sustained engagement over extended periods invariably suffered. This was an obstacle for both students and teachers throughout COVID-19 as learning could be taking place in person for some and remotely for others. Engagement with digital technology does not directly equate with in-person engagement, so depending on the diverse needs of some student learners, technological classroom engagement could have become more difficult for some students to achieve and retain over a meaningful length of time than others. The inner cognitive processes of organizing, handling, and interpreting information (i.e., reasoning), often non-observable mental activities (Bélanger, 2011) played a significant role in the analysis of this book’s findings as participants struggled to find a comfortable medium in two uniquely different learning settings. The basic principles and pedagogical connotations of cognitivist theory include procedural know-how, non-­ procedural knowledge, short and long-term memory, knowledge transfer, and metacognition (Bélanger, 2011). These are all cognitive processes that play important roles in this inquiry because of their effects on attention, focus, and engagement during learning. Since learning transcended the traditional school building due to COVID-19, this study provided participant insight and personal experiences of student learning processes during both in-person and remote learning environments. Cognitivism helps stakeholders to understand how students and teachers envisioned digital distraction, and how they viewed their own behaviors and personal reactions to digital device use and misuse inside two

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entirely different instructional settings. Cognitivist theory also provided a theoretical construct through which I was able to reflect over shared cognitive variances and unique learning struggles (Allal, 1998, and Astolfi, 1997, as cited in Bélanger, 2011), obstacles that occurred due to lapses in focus and engagement while learning. Research indicates that at least half of problem behaviors associated during the school day occur inside non-classroom settings (Colvin et al., 1997; Cash et al., 2019; Nelson & Colvin, 1996). This includes problem behaviors such as using digital devices for non-academic purposes. If students and teachers can work to identify these problematic choices, it may help to minimize breaks in focus and lapses in engagement while learning. Generally speaking, navigating traditional 1:1 learning may or may not be a relatively new concept for some school districts, but navigating 1:1 learning inside a remote or hybrid structure was an entirely new venture for all school districts throughout the COVID-19 pandemic. Teachers had to use both synchronous and asynchronous instructional strategies to help meet the needs of various student learners: a challenge compounded because some learners eventually committed to “in person” schooling while others opted to stay remote. After conducting this case study analysis into digital distraction, this book’s findings support previous literature’s stance that stakeholder “buy in” relating to the benefits of 1:1 learning and the leniency of mobile digital device usage inside the classroom varies widely on context and variables (Berdik, 2018; Berry & Westfall, 2015; Blikstad-Balas & Davies, 2017; Brazeau & Brazeau, 2009; Cho & Littenberg-Tobias, 2016; Fewkes & McCabe, 2012). Participants cited that leniency towards digital device use for non-academic purposes during learning, whether in person or remote, was likely a consequence of pandemic learning. Additionally, when students learned remotely, the lack of supervision at home coupled with the accessibility and proximity of digital technology shifted stakeholders’ opinions about the stringency and enforcement of prior digital device policy, whether expectations stemmed from school-mandated policy or parental expectations. Since this case study was a knowledge pursuit, the implication for practice is the hope that educational researchers and stakeholders can use this book’s findings to discover and test methods to minimize the potential for digital distraction when learning, no matter the instructional medium. In addition, stakeholders can use this research to better prepare for both in-­ person and remote learning scenarios in the future. Mobile technology is not going away, nor should it. The positives it provides in the learning

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setting outweigh the potential negatives. As is the case with most things, an appropriate balance of digital and non-digital instructional approaches is necessary to pique learners’ curiosity, maximize their engagement, support students’ metacognition, and foster knowledge transfer during learning. Creating meaningful policy regarding the use and or misuse of digital technology is an important takeaway from this book. Even though most schools have written and publicly published policies, the lack of consistency across school districts is concerning. When teachers are unaware of mandated policies inside their own districts, or when said policies have become antiquated, the enforcement and follow through of those policies are unlikely to happen. In addition, when students receive mixed messages between different classrooms and teachers throughout different parts of the building, frustration builds for everyone involved (i.e., students, parents, teachers, school security, support staff, and administration). Building consensus with provided input from all interested parties is key. Sometimes, school leadership builds policy without the input of all stakeholders. Hive mentality regarding digital policies in school may lead to stronger and longer-lasting gains in mitigating digital distraction, but this “hive consensus” cannot occur without first giving students and parents a voice in the creation of said meaningful digital policy and its enforcement during school. This in turn will provide more collective buy-in and build greater long-term sustainability of digital policy for stakeholders across school districts nationwide. Since this book wanted to capture the narrative essence of participants’ experiences with digital distraction, the qualitative method was the appropriate research approach for this work. This educational inquiry was a deep exploratory dive, so it was important for me to capture viewpoints and perspectives through in-depth interviewing in order to hear each participant’s unique voice. Moving forward, a mixed-methods approach might provide even more credibility to this book’s findings. For example, a survey could add another layer of statistical relevance by dramatically increasing the scope of participant input. Additionally, if participants completed a survey designed for the quantitative method, statistical analysis of the survey data through SPSS could provide detailed visuals in the form of charts and graphs that might further triangulate the primary source data collected from the qualitative semi-structured interviews. By adding a quantitative layer, it would be easier to extend this book’s exploratory formula to other sample sites with additional researchers.

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If further studies were done on digital distraction and its impact on 1:1 learning, conducting naturalistic observations (which could not be performed due to COVID-19) might provide another layer of qualitative data. Naturalistic observations could also assist researchers in discovering real time management strategies for appropriate digital device use for in-­ person learning settings. Now is the time for stakeholders to dig deeper into the exploration of digital distraction inside these evolving 1:1 learning environments, especially since the traditional classroom landscape has forever changed because of the recent pandemic. This inquiry had 15 participants, 12 of whom were students. The three teachers who participated in this case study provided a wealth of detailed information, but for further studies, it might be beneficial to incorporate more teacher-participants while also increasing the timeline of the study (e.g., full semester, entire school year). Further teacher perspectives, especially after a year of back-to-school in-person learning, may provide some unique insights into the evolution and minimization of digital distraction during school. In addition, since over half of this book’s student-­ participants were multilingual, a future inquiry that includes the shared perspectives of multilingual teacher-participants might provide another useful layer of research.

References Allal, L. (1998). Processus difficultés d’ apprentissage. Université de Genève. Archambault, I., Janosz, M., Fallu, J. S., & Pagani, L. S. (2009). Student engagement and its relationship with early high school dropouts. Journal of Adolescence, 32, 651–670. Astolfi, J. P. (1997). L’ erreur, un outil our enseigner.. ESF Editeur. Bélanger, P. (2011). Learning theories: Discussion. In Theories in adult learning and education (pp.  49–52). Verlag Barbara Budrich. http://www.jstor.org/ stable/j.ctvbkjx77.8 Berdik, C. (2018). Dealing with digital distraction. Education Digest, 84(1), 40–45. http://search.ebscohost.com.cucproxy.cuchicago.edu/login.aspx?Dir ect=tr ue&AuthType=cookie,ip,cpid&custid=s8419239&db=tfh&A N=131039574&site=ehost-­live Berry, M. J., & Westfall, A. (2015). Dial D for distraction: The making and breaking of cell phone policies in the college classroom. College Teaching, 63(2), 62–71. https://doi.org/10.1080/03054985.2017.1305045 Blikstad-Balas, M., & Davies, C. (2017). Assessing the educational value of one-­ to-­one devices: Have we been asking the right questions? Oxford Review of Education, 43(3), 311–331.

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Brazeau, G. A., & Brazeau, D. A. (2009). The challenge of educating in a highly-­ connected and multitasking world. American Journal of Pharmaceutical Education, 73(7), 1–2. https://doi.org/10.5688/aj7307125 Cash, A. H., Debnam, K. J., Waasdorp, T. E., Wahl, M., & Bradshaw, C. P. (2019). Adult and student interactions in non classroom settings. Journal of Educational Psychology, 111(1), 104–117. https://doi.org/10.1037/edu0000275 Cho, V., & Littenberg-Tobias, J. (2016). Digital devices and teaching the whole student: Developing and validating an instrument to measure educators’ attitudes and beliefs. Educational Technology Research & Development, 64(4), 643–659. https://doi.org/10.1007/s11423-­016-­9441-­x Christenson, S., Reschly, A. L., & Wylie, C. (2012). Handbook of research on student engagement. Springer. https://doi.org/10.1007/978-­1-­4614-­2018-­7 Colvin, G., Sugai, G., Good, R. H., & Lee, Y. (1997). Using active supervision and precorrection to improve transition behaviors in an elementary school. School Psychology Quarterly, 12, 344–363. https://doi.org/10.1037/h0088967 Fewkes, A. M., & McCabe, M. (2012). Facebook: Learning tool or distraction. Journal of Digital Learning in Teacher Education, 28(3), 92–98. Finn, J. D., & Zimmer, K. S. (2012). Student engagement: What is it? Why does it matter? In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp.  97–131). Springer Science + Business Media. https://doi.org/10.1007/978-­1-­4614-­2018-­7_5 Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School engagement: Potential of the concept, state of the evidence. Review of Educational Research, 74, 59–109. https://doi.org/10.3102/00346543074001059 Kennedy, E., Neumann, T., Rowett, S., & Strawbridge, F. (2017). Digital education and the connected curriculum: Towards a connected learning environment. In B.  Carnell & D.  Fung (Eds.), Developing the higher education curriculum: Research-based education in practice (pp. 188–202). UCL Press. Muenks, K., Wigfield, A., Yang, J. S., & O’Neal, C. R. (2017). How true is grit? assessing its relations to high school and college students’ personality characteristics, self-regulation, engagement, and achievement. Journal of Educational Psychology, 109(5), 599–620. https://doi.org/10.1037/mot0000076 Nelson, J. R., & Colvin, G. (1996). Designing supportive school environments. Special Services in the Schools, 11, 169–186. https://doi.org/10.1300/ J008v11n01_05 Reeve, J., Jang, H., Carrell, D., Jeon, S., & Barch, J. (2004). Enhancing students’ engagement by increasing teachers’ autonomy support. Motivation and Emotion, 28, 147–169. Skinner, E., Furrer, C., Marchand, G., & Kindermann, T. (2008). Engagement and disaffection in the classroom: Part of a larger motivational dynamic? Journal of Educational Psychology, 100, 765–781. https://doi.org/10.1037/a0012840

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Skinner, E.  A., Kindermann, T.  A., Connell, J.  P., & Wellborn, J.  G. (2009a). Organizational constructs in the dynamics of motivational development. In K.  Wentzel & A.  Wigfield (Eds.), Handbook of motivation at school (pp. 223–245). Lawrence Erlbaum. Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009b). A motivational perspective on engagement and disaffection: Conceptualization and assessment of children’s behavioral and emotional participation in academic activities in the classroom. Educational and Psychological Measurement, 69, 493–525. https:// doi.org/10.1177/0013164408323233 Wang, Z., Bergin, C., & Bergin, D. A. (2014). Measuring engagement in fourth to twelfth grade classrooms: The classroom engagement inventory. School Psychology Quarterly, 29(4), 517–535. https://doi.org/10.1037/spq0000050

CHAPTER 8

Key Takeaways and Conclusions

Abstract  Appropriate in-school digital behavior(s) happens as much outside of the classroom as it does inside the classroom setting. School districts and their stakeholders (i.e., school board members, administration, faculty, staff, students, parents) must all work together to foster more collective “buy in” pertaining to appropriate digital device usage at school. Just because school districts have policies in place does not guarantee their efficacy. Consequently, school districts should be spending time incorporating digital distraction and its effects into digital literacy education and curriculum. Without accomplishing this, mobile technology’s ill effects on time-on-task attention, learning focus, knowledge retention, learning transfer, and metacognition will continue to plague students and school districts across the globe. Students will never achieve anything remotely close to learning in the flow with today’s in-class digital distractions, and with artificial intelligence like ChatGPT building momentum, our students’ learning potential is in jeopardy. Keywords  1:1 Asynchronous learning • 1:1 Synchronous learning • In-person learning • Remote learning • Hybrid learning • Covid-19 • Learning focus • Learning engagement • Google Chromebook • Cellphone • Generalizability • Digital literacy education • Digital classroom management • Flow theory • AI (artificial intelligence) • ChatGPT

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Educational stakeholders need to discover how to minimize problems with focus and engagement caused by inappropriate behaviors outside the classroom as much as those inside the classroom. Half of problem behaviors associated during the school day occur inside non-classroom settings (Colvin et al., 1997; Nelson & Colvin, 1996; Cash et al., 2019). When students are engaged with non-academic digital distraction outside of the classroom, they bring this distraction with them into the learning environment. Because stakeholder “buy in” to the benefits of 1:1 learning and leniency of mobile digital device use during learning vary widely on context and other variables (Blikstad-Balas & Davies, 2017; Brazeau & Brazeau, 2009; Berry & Westfall, 2015; Berdik, 2018; Fewkes & McCabe, 2012; Cho & Littenberg-Tobias, 2016), we must learn how to better navigate 1:1 synchronous and asynchronous learning, especially when remotely delivering instruction. Subsequently, educational practitioners and policy makers can use this book’s findings to better prepare for future in-person, remote, and hybrid learning scenarios by creating an appropriate balance of digital to non-digital instructional approaches. Researchers can also use these findings to discover and test new methods for minimizing the potential for digital distraction when learning. Parents and teachers can reflect on how to better educate their children and students about why digital distraction affects instruction and learning while school leaders can create more targeted professional development that educates stakeholders about the influence of technology on focus and engagement during learning. This book suggests five themes that relate to students and teachers’ definitions of and experiences with digital distraction inside 1:1 in-person and remote learning environments. Even though mobile technology can increase student-to-student and student-to-teacher interaction and participation during learning, it can also prompt non-academic behaviors. This book includes pinpointed and practiced suggestions for the minimization of digital distraction during learning in order to maintain or increase student and practitioner focus and engagement. This case study also supports the perceived theory that digital distraction affects focus and engagement during learning. Digital distraction not only affects learning; it also plays a unique role when 1:1 learning is integrated. This study’s findings are significant because they capture student and teacher perspectives of digital distraction in a 1:1 learning environment that occurred in two distinctive settings: in-person learning at school and remote learning from home. Because of the COVID-19 pandemic,

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instructional settings for schooling across the globe have undergone a permanent transformation. Because of this, it is important for educational stakeholders to continue to research how in-person and remote learning could improve with an appropriate balance of digital technology integration. As more school districts move toward 1:1 learning across the United States and abroad, stakeholders must continue to search for ways to minimize digital distraction during school while maximizing the potential for learning offered by mobile digital technology. Even though digital technology can increase student interaction and active participation, students and teachers can also use those same technologies to engage in disruptive, non-academic behaviors during learning (Bojinova & Oigara, 2013; Samson, 2010). When this occurs, active participation, learning engagement, and academic performance can diminish (Redner et  al., 2019). Managing the impact of digital distraction on focus and engagement during learning without the collaborative efforts of students, parents, and educators is difficult. Providing voice to all potential stakeholders impacted by digital distraction in a 1:1 learning environment is necessary if the minimization of digital distraction is to occur. The results of this study suggested five themes that relate to students and teachers’ definitions and experiences with digital distraction during learning. These five themes represent study participants’ perspectives of causes and contributions to digital distraction happening inside the 1:1 in-person and remote learning environments: (a) participants perceived digital distraction as a loss of focus and engagement for non-academic purposes; (b) participants felt that cell phones and school-issued Chromebooks were the most popular devices used for digital distraction; (c) participants felt that non-digital factors impacted digital distraction more than digital influences did; (d) participants identified asynchronous remote learning to be more challenging than synchronous in-person learning; and (e) participants felt that complete mitigation of digital distraction was improbable, so suggestions were made to help minimize digital distraction in order to better maintain focus and engagement during learning. Study participants shared a variety of in-person and remote learning experiences with digital distraction. They also provided personalized definitions of digital distraction that all supported the same subject: the loss of focus and engagement using mobile digital devices for non-­ academic behaviors during learning. In addition to sharing what digital distraction looked like during in-person and remote learning,

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participating students and teachers discussed what they felt contributed to digital distraction. Both students and teachers also communicated their own observed and experienced responses to digital distraction when learning. Participants universally agreed that the loss of focus and engagement during learning was the most compelling issue with digital distraction. Oftentimes, participants became digitally distracted by communication, social media, and entertainment, which was easy since remote learning provided an unencumbered setting. Digital devices were readily accessible with little or no supervision. Students and teachers identified the cellphone as the most popular device used for digital distraction. The school-­ issued Google Chromebook was a close second, illustrating that school-mandated technology, even with the best cybersecurity and policy, can be used for non-academic purposes during learning. Both digital and non-digital factors played significant roles in contributing to digital distraction for students and teachers during in-person and remote learning throughout the pandemic. Interestingly, participants felt that non-digital influences triggered digital distraction more often than digital influences did. This discovery is pedagogically significant because it supports many of the widely practiced non-digital instructional approaches used by teachers to engage students and maximize learning inside the classroom. For example, when teachers deliver instruction with energy and enthusiasm, students are less likely to become bored. Boredom was one of the most widely recognized and discussed non-digital influences participants felt contributed to digital distraction during learning. Since this case study was conducted during the height of the COVID-19 pandemic, students and teachers experienced a combination of synchronous and asynchronous learning in two completely different environments: inside a socially distanced classroom at school and remotely from home. Even when students were learning in person, the school environment was far different from what students had previously experienced because of mandatory safety protocols. Both students and teachers felt that asynchronous learning proved to be more challenging since it was self-paced. Another challenge participants noted was the lack of supervision during remote learning at home. Because of this, many students struggled with procrastination and focus since there were fewer checks and balances with remote learning, compared to when students were physically inside a school building.

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Both students and teachers were candidly honest about the likelihood of mitigating digital distraction. After having to adapt traditional school settings and instructional methods because of the COVID-19 pandemic, both students and teachers experienced the need for mobile digital technology when learning in real time. Subsequently, there was no question about the importance of digital device use, especially during this unprecedented time. Even with stakeholders’ reliance on digital devices, for educational purposes, students and teachers were honest about not only the potential for digital distraction, but also that the complete mitigation of digital distraction during in-person and/or remote learning was improbable and unrealistic. The accessibility, proximity, and freedom of digital devices and their use afforded to both students and teachers were too extensive and complex to manage. In addition, the lack of consistency in digital device policy in school and between individual teachers (including parental parameters or lack thereof), made the probability of complete mitigation impossible. Instead, students and teachers shared a variety of suggestions. Some of these suggestions were theoretical while others were attempted and/or implemented. Participants shared these perspectives and experiences, however, in an effort to help minimize the potential for digital distraction, hoping to maintain better focus and engagement during learning. As previously indicated, digital distraction during learning is something that is not going away, nor will it ever be eradicated by some chance circumstance. There is no one-size-fits-all solution, no magic bullet. However, becoming more educated while sharing viewpoints and perspectives with other stakeholders is a good starting point. More research on the impact of digital distraction on focus and engagement during learning is an important takeaway this book provides. In addition, students must continue to be included in the conversation. It is good pedagogical practice to explain why something is so important for a student to learn, especially when it pertains to a particular new concept or idea inside the classroom. Similarly, students and teachers need to be educated over how digital distraction affects instruction and learning. Just as teachers cannot assume students always know the why, school leaders cannot assume all teachers understand the importance of comprehending digital distraction and its impact on learning focus and active engagement. Digital distraction is a topic that warrants further research and education, both of which can be accomplished through facilitating targeted professional development, providing updated research literature for professional reading/reflection, and sharing personal experiences through small group

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discussions during in-service and other professional development workshops. It is my hope that educational researchers and school leadership will continue to proactively grow, adapt, and meet the digital needs of students and teachers, whether learning is happening in person or remotely. This study’s findings have strong generalizability. If digital distraction is happening in a district like this, a pioneer in 1:1 learning with years of experience managing 1:1 and remote e-learning (i.e., state-approved pilot e-learning school for weather-related cancellations), then the management of digital distraction in schools with far less 1:1 and remote e-learning experience must be even more difficult. The power of digital technology, especially in the classroom when managed appropriately, is a formidable learning tool. With this influence, though, there comes accountability on the parts of all stakeholders. Some schools require a compulsory digital literacy course for students. At this school, many freshmen opt to take their district-required digital literacy class during summer school before first semester. Now, this school is no longer alone as its state recently passed a media literacy law that went into effect during the 2022–23 school year, which requires schools to provide instruction over the communication and analysis of information through a variety of mediums, including digital/interactive and audio/visual channels. What this means for this study’s research is that the definition of digital distraction, along with its digital/non-digital influences and suggestions for minimization, must be included in digital literacy education. If school districts are ever going to help students learn how to better manage their emotional, behavioral, and cognitive engagement when actively learning on mobile technology, especially inside potentially different academic environments, students must be educated on the how, the why, and the potential results of digital distraction during class. As ironic as it sounds, traditional modes of 1:1 learning have become antiquated, especially due to the COVID-19 pandemic. Because of this, digital literacy education must change to include digital distraction as part of the curriculum to best meet the needs of students and teachers operating in these new 1:1 in-person and remote synchronous/asynchronous learning environments. Unfortunately, too many school leaders continue to dodge the elephant in the room by adopting overtly lax digital in-class policy that puts the whole of digital management onto the backs of teachers. For example, when districts state things like “phones are expected to be away in the

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classroom, only allowable per teacher discretion,” the policy is too vanilla, too vague. Coupling examples of the aforesaid with non-specific policy like “teachers can create their own classroom expectations,” which might include the use of cellphone holders/homes per teacher discretion inside classrooms, sends the wrong message. In addition, when high school students traverse 7–8 different learning settings on a daily basis with “modified” expectations per each space, the anxiety and confusion of staying abreast of digital management requirements is a losing battle from the onset. For one classroom, no cell phones allowed in sight while in another, students will place phones in a cell home, or inside their backpacks, or maybe flipped over atop their desks, or possibly out of sight in their pockets. But what if they don’t have pockets, or backpacks? What if all seven classrooms a student visits throughout the day all have a different rule? What if students visit a classroom that has no required mobile device expectation(s)? And guess what, many school policies only include personal mobile technology, not school-issued devices, which students are expected to complete the onus of their daily work on. What about the management of Chromebooks inside a 1:1 school? In order to be effective, school leadership must have the confidence to make a top-down decision that is the expectation for all shareholders when learning, especially when it’s on site and in person. Specific, targeted policy must begin on the local level for the effective management of such devices to occur, and it has to be an “all hands-on deck” approach. Some might argue that this approach pushes back a little against student voice and choice, but students will never achieve anything remotely close to “learning in the flow” if learning engagement and focus are not sustained inside the classroom setting. A seismic shift occurred in November of 2022 with the introduction of ChatGPT, which introduces another layer of potential distraction for students operating inside today’s classrooms. Before parents, teachers, and administrators turn all of their attention toward artificial intelligence, stakeholders must be cognizant of the ongoing struggles we are still facing today with digital distraction—on school-issued and personal devices, no less—that is plaguing our schools. The fact that these digital distractions and their negative effects on learning focus, knowledge retention, and engagement are only building momentum should scare every parent and educational practitioner out there.

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References Berdik, C. (2018). Dealing with digital distraction. Education Digest, 84(1), 40–45. http://search.ebscohost.com.cucproxy.cuchicago.edu/login.aspx?Direct=true &AuthType=cookie,ip,cpid&custid=s8419239&db=tfh&AN=131039574&site =ehost-­live Berry, M. J., & Westfall, A. (2015). Dial D for distraction: The making and breaking of cell phone policies in the college classroom. College Teaching, 63(2), 62–71. https://doi.org/10.1080/03054985.2017.1305045 Blikstad-Balas, M., & Davies, C. (2017). Assessing the educational value of one-­ to-­one devices: Have we been asking the right questions? Oxford Review of Education, 43(3), 311–331. Bojinova, E., & Oigara, J. (2013). Teaching and learning with clickers in higher education. International Journal on Teaching and Learning in Higher Education, 25, 154–165. https://www.learntechlib.org/p/130700/ Brazeau, G. A., & Brazeau, D. A. (2009). The challenge of educating in a highly-­ connected and multitasking world. American Journal of Pharmaceutical Education, 73(7), 1–2. https://doi.org/10.5688/aj7307125 Cash, A. H., Debnam, K. J., Waasdorp, T. E., Wahl, M., & Bradshaw, C. P. (2019). Adult and student interactions in non classroom settings. Journal of Educational Psychology, 111(1), 104–117. https://doi.org/10.1037/edu0000275 Cho, V., & Littenberg-Tobias, J. (2016). Digital devices and teaching the whole student: Developing and validating an instrument to measure educators’ attitudes and beliefs. Educational Technology Research & Development, 64(4), 643–659. https://doi.org/10.1007/s11423-­016-­9441-­x Colvin, G., Sugai, G., Good, R. H., & Lee, Y. (1997). Using active supervision and precorrection to improve transition behaviors in an elementary school. School Psychology Quarterly, 12, 344–363. https://doi.org/10.1037/h0088967 Fewkes, A. M., & McCabe, M. (2012). Facebook: Learning tool or distraction. Journal of Digital Learning in Teacher Education, 28(3), 92–98. Nelson, J. R., & Colvin, G. (1996). Designing supportive school environments. Special Services in the Schools, 11, 169–186. https://doi.org/10.1300/ J008v11n01_05 Redner, R., Lang, L.  M., & Brandt, K.  P. (2019). Evaluation of an electronics intervention on electronics use in a college classroom. Behavior Analysis: Research and Practice. https://doi.org/10.1037/bar0000158 Samson, P. J. (2010). Deliberate engagement of laptops in large lecture classes to improve attentiveness and engagement. Computers & Education, 1, 1–19.



Terms to Know

Backchannel—a twenty-first century learning tool that is a conversation held in a separate location (often through a digital communicative platform) from the primary discussion happening inside a classroom setting (Engel & Green, 2011; Oliveira, 2018, p. 10). Classroom management—a practice whereby a classroom teacher organizes “students, space, time, and materials” so meaningful and effective learning can take place on a daily basis, ensuring appropriate learning, social-emotional, and behavioral actions are happening inside a learning environment (Blikstad-Balas & Davies, 2017; Wong et al., 2018, p. 34). Digital citizenship—understanding the digital medium through which youth can act as full citizens of online communities in a way they often cannot in their offline lives, resulting in the development of certain rights and responsibilities that include online safety, advocacy, empathy, ethics, and activism (Johnson, 2015, pp.  342–343). In addition, the elements and actions taught through digital literacy extend courtesy and respect throughout school and the workplace. Examples from the realm of digital citizenship include the employment of business etiquette, interpersonal and teamwork skills, professionalism and work ethic, responsibility, and a positive work attitude. This is all in relation to the use of digital devices and electronic communications inside school and the workplace (Seemiller, 2017).

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Digital device—smartphones, smartwatches, tablets, and personal laptop computers that use apps, data, and features (e.g., survey app, GPS, camera, Bluetooth, internet) to enhance personal/professional communication, work-related tasks, and entertainment (Antoun, 2015, p. 100). Digital distraction—students using technology for non-course related purposes (often in the form of personal mobile digital devices like smartphones), causing students to not pay attention in class, which triggers serious learning and behavioral concerns like poor learning transfer, weak knowledge retention, and low academic achievement (Berdik, 2018; Berry & Westfall, 2015; Seemiller, 2017, p. 214). Digital immigrant—an adult who has adapted to a life that includes technology (Oliveira, 2018, p. 10; Prensky, 2006). Digital literacy—the technical fluency required for engagement with computers and the internet, coupled with recognition of how people understand digital media and its positive/negative impact in the development of digitally self-created content inside the world of work and school (Johnson, 2015, p. 341; Seemiller, 2017). Digital natives—students today who are growing up fully immersed in technology (Oliveira, 2018, p. 10; Prensky, 2006). Digital technology—the gamut of electronic communications used in both personal and professional life, including but not limited to smartphones, smartwatches, laptops, texts, emails, phone apps, etc. (Berdik, 2018). Generation Z—the generation born between 1996–2010, a generation fully immersed in technology and social media (Oliveira, 2018, p.  10; Williams, 2015). Google Chromebook—mobile notebook computer built for fast web browsing that is unlike a traditional laptop since it runs on a cloud-based system (Chrome OS) with cloud-based apps (i.e., Google Drive, Google Docs) that store data online (Beal, n.d.). Internet—electronic computer network that connects digital and communicative computer networks from around the world (Oliveira, 2018, p. 10). Millennial–those born after 1980 and the first generation to come of age in the new millennium, often having led older generations in the adoption and use of modern communication technologies (Pew Research Center, 2019). Mobile device—mobile devices like iPads, tablets, or smartphones that connect to the internet wirelessly while downloading apps and content (Oliveira, 2018, p. 11).

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Mobile learning—the use of mobile devices for participation in learning activities (Asiimwe & Gronlund, 2015). One-on-one (1:1) digital device—any personal or school-issued mobile device that an individual has sole ownership of, ranging from smartphones and smartwatches to laptops and tablets (Berdik, 2018; Berry & Westfall, 2015). Smartphone—a handheld device that runs an operating system similar to a computer, but it is mobile, can make phone calls, send texts/emails, and connects wirelessly to the internet (Oliveira, 2018, p. 11). Social media—on-line communication mediums through which individuals, schools/other learning environments, and companies can share information, including sites like Facebook, Instagram, Snapchat, and Twitter (Berdik, 2018; Oliveira, 2018, p. 11). Student engagement—the degree of attention, participation, focus, and enthusiasm students emit in any given learning activity. Twenty-first century learning—participating and facilitating in the incorporation and operational management of computer system devices and software packages as producing tools per word processing, database management, spreadsheet applications, and communication platforms to explore, evaluate, and use technological resources in educational settings. These actions help to develop twenty-first century skills (e.g., problem solving, collaboration, connection-making, computational practices) inside the classroom that will be required in order for students to be successful in the workplace (Blikstad-Balas & Davies, 2017). Ubiquitous learning—the ability to learn anytime and anywhere without restriction. This type of learning often requires the use of mobile digital technologies. Wi-Fi—wireless technology that connects computers and mobile devices to each other and the internet.

References

Antoun, C. (2015). Who are the internet users, mobile internet users, and mobile-­ mostly internet users? Demographic differences across internet-use subgroups in the U.S. In D. Toninelli, R. Pinter, & P. De Pedraza (Eds.), Mobile research methods: Opportunities and challenges of mobile research methodologies (pp. 99–118). Ubiquity Press. http://www.jstor.org/stable/j.ctv3t5r9n.12 Asiimwe, E., & Gronlund, A. (2015). MLCMS actual use, perceived use, and experiences of use. International Journal of Education and Development Using Information and Communications Technology, 11(1), 101–121. https://eric. ed.gov/?id=EJ1061487 Beal, V. (n.d.). Chromebook. https://www.webopedia.com/TERM/C/ chromebook.html Berdik, C. (2018). Dealing with digital distraction. Education Digest, 84(1), 40–45. http://search.ebscohost.com.cucproxy.cuchicago.edu/login.aspx?Direct=true &AuthType=cookie,ip,cpid&custid=s8419239&db=tfh&AN=131039574&site =ehost-­live Berry, M. J., & Westfall, A. (2015). Dial D for distraction: The making and breaking of cell phone policies in the college classroom. College Teaching, 63(2), 62–71. https://doi.org/10.1080/03054985.2017.1305045 Blikstad-Balas, M., & Davies, C. (2017). Assessing the educational value of one-­ to-­one devices: Have we been asking the right questions? Oxford Review of Education, 43(3), 311–331. Engel, G., & Green, T. (2011). Cell phones in the classroom: Are we dialing up disaster? Tech Trends, 55(2), 39–45.

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Johnson, M. (2015). Digital literacy and digital citizenship: Approaches to girls’ online experiences. In J. Bailey & V. Steeves (Eds.), EGirls, eCitizens: Putting technology, theory and policy into dialogue with girls’ and young women’s voices (pp.  339–360). University of Ottawa Press. http://www.jstor.org/stable/ j.ctt15nmj7f.17 Oliveira, P. J. (2018). Teacher and student perceptions of the effect of smartphones on student engagement: A case study (Publication Number 134187220). Doctoral Dissertation, ProQuest Dissertations & Theses Global. Pew Research Center [Millennials]. (2019). https://www.pewresearch.org/topics/ millennials/ Prensky, M. (2006). Don’t bother me mom—I’m learning. Paragon House. Seemiller, C. (2017). Curbing digital distractions in the classroom. Contemporary Educational Technology, 8(3), 214–231. https://doi.org/10.30935/cedtech/6197 Williams, A. (2015, September 18). Move over millennials, here comes generation z. NY Times. https://www.nytimes.com/2015/09/20/fashion/move-­over-­ millennials-­here-­comes-­generation-­z.html Wong, H.  K., Wong, R.  T., Nuccio, L., Allred, S., & David-Lang, J. (2018). Implementation guide for The first days of school: How to be an effective teacher (5th ed.). https://www.effectiveteaching.com/userfiles/uploads/Guides/ Implementation_Guide_for_THE_First_Days_of_School_5th_Edition.pdf

Index

A Academic performance, 86, 87, 121 Addiction, 40, 51, 74, 78 Anxiety, 29, 30, 60, 74, 78, 79, 91, 125 separation-anxiety, 74, 86 Artificial intelligence (AI) technology Amazon Alexa, 100 Amazon Echo, 100 ChatGPT, 125 Asynchronous learning, 80, 96–99, 112, 120, 122, 124 Attention, 4, 9–12, 16–18, 21, 22, 25, 27, 28, 40, 42, 45, 47, 60–62, 74, 76, 79, 81, 82, 87, 91, 96, 110, 112, 125, 128, 129 B Backchannel, 3, 18, 19, 21, 127 Behavior learning interventions, 10, 110 Boredom, 4, 7, 9, 40, 47, 74–78, 80, 122

C Cellphone, 3–5, 7, 19, 20, 23, 40, 41, 45, 48, 50, 54–66, 69, 70, 80, 87, 90, 91, 96, 100–105, 112, 121, 122, 125 Cellphone accessibility, 54–56, 70 Classroom management, 5, 17, 18, 44, 82, 99, 104, 127 digital, 5, 17, 18 Cognitive overload, 74 Cognitive variance(s) in learning, 110, 113 Cognitivism, 16–18, 88, 112 cognitivist theory, 9, 10, 16–18, 27, 112, 113 COVID-19, 3, 21, 22, 50, 55, 75, 79, 88–90, 110, 112, 115 pandemic, 3, 12–14, 16, 28, 32, 48, 65, 71, 76, 80, 97, 102, 111, 113, 120, 122–124 Cybersecurity, 86, 88, 91, 99, 122

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INDEX

D Device accessibility, 66, 70, 75, 79, 86, 89, 123 Device leniency, 79, 113, 120 Digital apps Google Docs, 66, 67, 99, 128 Google Meet, 40, 41, 51, 57, 66–69, 75, 79, 81, 87, 99 Otter.ai, 21 Zoom, 51, 75, 99 Digital citizenship, 3, 6, 8, 18, 127 Digital device cellphone, 3–5, 7, 19, 20, 23, 40, 41, 45, 48, 50, 54–66, 69, 70, 80, 87, 90, 91, 96, 100–105, 112, 121, 122, 125 digital media player, 100 digital notebook, 128 gaming system; Nintendo Switch, 100; PlayStation, 47, 49, 65, 100; Xbox, 64, 65, 100 Google Chromebook, 6, 19, 23, 26, 28, 40, 48, 54, 55, 65, 67, 69, 79, 99–103, 105, 112, 122, 128 iPad, 19, 47, 55, 62, 63, 65, 66, 100, 103, 105, 128 laptop, 21, 55, 63, 64, 68, 100–103, 105, 128, 129 mobile device, 22, 54, 55, 79, 87, 90, 91, 125, 128, 129 mobile phone, 23, 57, 59–61 mobile technology, 4, 7, 8, 19, 22, 27, 32, 40, 41, 62, 74, 75, 81, 86, 88, 90, 113, 120, 124, 125 personal computer, 64, 100–103, 105 smartphone, 65, 66, 128, 129 smartwatch, 3, 59, 61–65, 100–103, 105, 128, 129 tablet, 3, 55, 65, 100, 103, 105, 128, 129

Digital distraction cellphone distraction, 7, 50, 57, 58, 60, 102, 104, 105 Chromebook distraction (school-­ issued), 65 digital media player distraction, 100 digital netbook distraction, 100 Gaming system distraction (Xbox, PlayStation, Nintendo Switch), 47, 49, 64, 65, 100 iPad distraction, 47, 55, 62, 63, 66, 100, 103, 105 mobile phone distraction, 23, 57, 59–61 personal computer distraction, 64, 100–103, 105 personal laptop distraction, 64, 68 smartwatch distraction, 59, 62, 100–103, 105 tablet distraction, 100, 105 television distraction, 50, 63, 64, 100, 103–105 virtual assistant AI technology distraction (Amazon Alex, Amazon Echo), 100 Digital entertainment, 7, 8, 48, 62, 63, 80 Digital immigrant, 128 Digital literacy, 5, 6, 124, 127, 128 curriculum, 51, 86 Digital native, 74, 87, 128 Digital policy, 86, 91, 110, 114 enforcement, 86, 114 Digital technology, 3–5, 9, 10, 12, 13, 15–17, 19, 20, 22, 23, 30, 40, 41, 55, 62, 65, 66, 76, 77, 79, 80, 86, 88, 96, 99, 110–114, 121, 123, 124, 128, 129 Digital variety, 64

 INDEX 

E Electronic notifications, 80 Engagement affective (emotional), 11, 111 behavioral, 11, 110, 112, 124 cognitive, 12, 110–112, 124 learning, 10, 57, 75, 110, 112, 121, 125 student, 3, 10, 12–15, 21, 28, 77, 80, 129 theory, 9–16, 80, 90 F Face-to-face learning, 4, 99 Fear of missing out (FOMO), 40, 74, 78 Flow theory, 14 Focus, 6, 10, 19, 25, 39–43, 45–47, 49, 50, 55, 57, 58, 60, 62, 63, 69, 74–78, 80–82, 88, 89, 91, 92, 96, 97, 99, 110–113, 120–123, 125, 129 Formal research journal, 16, 21, 25, 26, 31, 106 G Generalizability, 54, 61, 124 Generation Z, 128 Google Chat (G-chat), 66, 67, 69, 70, 79–81, 91, 99 Google Chromebook, 6, 19, 23, 26, 28, 40, 54, 55, 65, 67, 69, 79, 99–103, 105, 112, 122, 128 Google Generation, 74, 87 H Hybrid learning, 3, 26, 48, 51, 90, 120

135

I iGeneration, 74 In-person learning, 4, 12, 13, 28, 40, 51, 55, 57, 59, 62, 63, 65, 70, 74, 81, 88, 89, 97, 99–102, 104, 111–113, 115, 120–123 Instant gratification, 22, 69, 74, 79 Internet, 3, 43, 51, 76, 128, 129 Intrinsic motivation, 80, 88, 90 K Knowledge retention, 8, 21, 23, 42, 90, 125, 128 L Learning transfer, 8, 9, 20, 21, 23, 42, 88, 90, 128 M Metacognition, 12, 16–18, 80, 88, 111, 112, 114 Millennial, 8, 128 Multiple tabs/windows, 67–70, 81, 88 Multiprocessing, 74 Multitasking, 4, 40, 74, 86, 87, 96, 97 N Non-academic communication, 3, 40–43, 45, 62, 69, 96 Non-digital distraction, 89 O One-on-one (1:1) learning, 4, 7, 9, 16, 19, 22, 26, 28, 32, 75, 86, 89, 90, 110, 113, 115, 120, 121, 124

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P Phone confiscation, 86, 88, 91 Professional development, 50, 86, 120, 123, 124 R Remote learning, 8, 10, 12, 13, 16, 28, 29, 40, 42, 45, 47, 49, 51, 55–57, 59, 62–66, 74, 79, 81, 87–89, 96, 97, 100, 104–106, 111–113, 120–123 S Self-paced learning, 96, 97 Self-regulation, 11, 86, 87, 89 Self-reporting interactive frequency log interactive frequency log, 100 interactive log, 27 self-reporting log, 16, 100, 103, 104, 106 Social-emotional learning, 5 Social media Facebook, 4, 129 Instagram, 40, 45, 46, 129 Snapchat, 40, 43–45, 79, 96, 129 Twitter, 4, 46, 75, 129

Stress, 57, 78, 91, 99 Supervision, 49, 51, 64, 75, 79, 80, 87, 89, 96, 97, 113, 122 Synchronous learning, 40, 96–99, 112, 120, 122, 124 T Texting, 3, 40–45, 50, 51, 59, 61, 78, 80, 96 Time-management, 49, 98 Twenty-first (21st) century learning, 5, 6, 15, 16, 127, 129 U Ubiquitous learning, 129 V Video conferencing, 99 W Web 2.0 technology, 70, 74 Wi-Fi, 20, 129