This article was downloaded by:[116.227.252.224] On:26 February 2014,At:01:43 Publisher:Routledge Informa Ltd Registered in England and Wales Registered Number:1072954 Registered office:Mortimer House,37-41 Mortimer Street,London W1T 3JH,UK Communication Education Publication details,including instructions for authors and Communication subscription information: Education http://www.tandfonline.com/loi/rced20 The Impact of Mobile Phone Usage on Student Learning Jeffrey H.Kuznekoff Scott Titsworth Published online:12 Feb 2013. To cite this article:Jeffrey H.Kuznekoff Scott Titsworth(2013)The Impact of Mobile Phone Usage on Student Learning,Communication Education,62:3,233-252,DOl: 10.1080/03634523.2013.767917 To link to this article:http://dx.doi.org/10.1080/03634523.2013.767917 PLEASE SCROLL DOWN FOR ARTICLE Taylor Francis makes every effort to ensure the accuracy of all the information(the "Content")contained in the publications on our platform.However,Taylor Francis, our agents,and our licensors make no representations or warranties whatsoever as to the accuracy,completeness,or suitability for any purpose of the Content.Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor Francis.The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information.Taylor and Francis shall not be liable for any losses,actions,claims, proceedings,demands,costs,expenses,damages,and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with,in relation to or arising out of the use of the Content. This article may be used for research,teaching,and private study purposes.Any substantial or systematic reproduction,redistribution,reselling,loan,sub-licensing, systematic supply,or distribution in any form to anyone is expressly forbidden.Terms& Conditions of access and use can be found at http://www.tandfonline.com/page/terms- and-conditions
This article was downloaded by: [116.227.252.224] On: 26 February 2014, At: 01:43 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Communication Education Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/rced20 The Impact of Mobile Phone Usage on Student Learning Jeffrey H. Kuznekoff & Scott Titsworth Published online: 12 Feb 2013. To cite this article: Jeffrey H. Kuznekoff & Scott Titsworth (2013) The Impact of Mobile Phone Usage on Student Learning, Communication Education, 62:3, 233-252, DOI: 10.1080/03634523.2013.767917 To link to this article: http://dx.doi.org/10.1080/03634523.2013.767917 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/termsand-conditions
Communication Education V%l.62,N6.3huy2013,pp.233-252 Routecge Tayfor f.Franxi Ceoup The Impact of Mobile Phone Usage on Student Learning Jeffrey H.Kuznekoff Scott Titsworth In this study,we examined the impact of mobile phone usage,during class lecture,on student learning.Participants in three different study groups (control,low-distraction, and high-distraction)watched a video lecture,took notes on that lecture,and took two learning assessments after watching the lecture.Students who were not using their mobile 名 phones wrote down 62%more information in their notes,took more detailed notes,were able to recall more detailed information from the lecture,and scored a full letter grade and a half higher on a multiple choice test than those students who were actively using their mobile phones.Theoretical and pedagogical implications are discussed. Keywords:Texting;Student Learning;Texting in the Classroom;Technology;Mobile Phone In modern classrooms,instructors face many challenges as they compete for students' attention among a variety of communication stimuli.Rapid growth of mobile computing,including smart phones and tablets,presents a double-edged problem: papeojuMo along with previously unimaginable access to information come previously unfore- seen distractions.Of wide concern to many instructors is the potential distraction caused by students using their mobile devices to text,play games,check Facebook, tweet,or engage in other activities available to them in a rapidly evolving digital terrain.That concern has potential merit;recent statistics from the Pew Foundation show that the median number of daily texts for older teens rose from 60 in 2009 to 100 in 2011 (Lenhart,2012).Moreover,64%of teens who own cell phones have texted during class,even in schools where cell phones are technically banned (Lenhart,Ling,Campbell,Purcell,2010).Those texts potentially come at the expense of learning,as texting during class reduces students'ability to self-regulate and give sustained attention to classroom tasks(Wei,Wang,Klausner,2012). Jeffrey H.Kuznekoff(Ph.D.,Ohio University)is an Adjunct Faculty Member in the School of Communication Studies at Ohio University,where Scott Titsworth(Ph.D.,University of Nebraska)is Dean of the Scripps College of Communication.Jeffrey H.Kuznekoff can be contacted at jk248508@ohio.edu ISSN 0363-4523(print)/ISSN 1479-5795(online)C2013 National Communication Association htp:/dk.doi.org/10.1080/03634523.2013.767917
The Impact of Mobile Phone Usage on Student Learning Jeffrey H. Kuznekoff & Scott Titsworth In this study, we examined the impact of mobile phone usage, during class lecture, on student learning. Participants in three different study groups (control, low-distraction, and high-distraction) watched a video lecture, took notes on that lecture, and took two learning assessments after watching the lecture. Students who were not using their mobile phones wrote down 62% more information in their notes, took more detailed notes, were able to recall more detailed information from the lecture, and scored a full letter grade and a half higher on a multiple choice test than those students who were actively using their mobile phones. Theoretical and pedagogical implications are discussed. Keywords: Texting; Student Learning; Texting in the Classroom; Technology; Mobile Phone In modern classrooms, instructors face many challenges as they compete for students’ attention among a variety of communication stimuli. Rapid growth of mobile computing, including smart phones and tablets, presents a double-edged problem: along with previously unimaginable access to information come previously unforeseen distractions. Of wide concern to many instructors is the potential distraction caused by students using their mobile devices to text, play games, check Facebook, tweet, or engage in other activities available to them in a rapidly evolving digital terrain. That concern has potential merit; recent statistics from the Pew Foundation show that the median number of daily texts for older teens rose from 60 in 2009 to 100 in 2011 (Lenhart, 2012). Moreover, 64% of teens who own cell phones have texted during class, even in schools where cell phones are technically banned (Lenhart, Ling, Campbell, & Purcell, 2010). Those texts potentially come at the expense of learning, as texting during class reduces students’ ability to self-regulate and give sustained attention to classroom tasks (Wei, Wang, & Klausner, 2012). Jeffrey H. Kuznekoff (Ph.D., Ohio University) is an Adjunct Faculty Member in the School of Communication Studies at Ohio University, where Scott Titsworth (Ph.D., University of Nebraska) is Dean of the Scripps College of Communication. Jeffrey H. Kuznekoff can be contacted at jk248508@ohio.edu ISSN 0363-4523 (print)/ISSN 1479-5795 (online) # 2013 National Communication Association http://dx.doi.org/10.1080/03634523.2013.767917 Communication Education Vol. 62, No. 3, July 2013, pp. 233252 Downloaded by [116.227.252.224] at 01:43 26 February 2014
234 J.H.Kuznekoff and S.Titsworth Cell phones,and the broader array of digital mobile devices,pose unique communication challenges for both users and those with whom they interact.Some critics argue that texting and other digital communication behavior potentially diminish key social skills like effective listening.As one commentator noted,"We think of phones as a communication tool,but the truth is they may be just the opposite"(Skenazy,2009,np).Other views suggest that people are adapting to new communication norms in an increasingly digital world,learning to quickly attend to, process,and respond to multiple and sometimes simultaneous messages (Davidson, 2011).Given the many possible ways that digital communication tools will continue to influence practices of teaching and learning(Schuck Aubusson,2010),instructional communication scholars should enact programmatic research to understand how these tools impact classroom communication and subsequent learning outcomes. The present study builds on past research by examining whether texting or posting to a social network site has negative impacts on students'note-taking behaviors and subsequent performance on exams.Participants took part in simulated classroom conditions where they watched a recorded lecture,took notes over the lecture,and were then tested over lecture content.There were three conditions in the study:a control group and two experimental groups.The control group simply watched the lecture,took notes on the lecture,and answered exam questions over lecture content. Et:I0 The other two groups engaged in the same activities as the control group,but also took part in simulated texting/Facebook interactions during the lecture;one group had a low frequency of texts/posts,and another had a high frequency.By using simulated text messages and Facebook posts,the objective of the study was to determine what effects,if any,these distractions had on student learning. Literature Review Mobile Phone Usage and Features papeojuMo Modern phones have a variety of features that simply were not possible years ago: Mobile phones are not just for voice communication anymore(Ishii,2006).College students can access the Internet,send or receive text messages,check email,and even video chat with others quite literally from the palm of their hand.In addition, students can access a variety of social network sites(SNS)from their mobile phones. Scholars boyd and Ellison (2008)explain that SNS are online services that allow people to create a profile,create a list of other users who share a connection with the user,and view the lists of connections created by others within that system.For the purposes of the current study,we use the technical term SNS in place of other terminology (e.g.,social networking sites)because SNS better conveys the way in which users communicate with others via these systems.boyd and Ellison note that other terms,like social networking sites,emphasize relationship initiation and users forming connections with others with whom they might not normally have come in contact.However,the term SNS better conveys the way in which users communicate with other people they have connected with.As boyd and Ellison put it,"They are
Cell phones, and the broader array of digital mobile devices, pose unique communication challenges for both users and those with whom they interact. Some critics argue that texting and other digital communication behavior potentially diminish key social skills like effective listening. As one commentator noted, ‘‘We think of phones as a communication tool, but the truth is they may be just the opposite’’ (Skenazy, 2009, np). Other views suggest that people are adapting to new communication norms in an increasingly digital world, learning to quickly attend to, process, and respond to multiple and sometimes simultaneous messages (Davidson, 2011). Given the many possible ways that digital communication tools will continue to influence practices of teaching and learning (Schuck & Aubusson, 2010), instructional communication scholars should enact programmatic research to understand how these tools impact classroom communication and subsequent learning outcomes. The present study builds on past research by examining whether texting or posting to a social network site has negative impacts on students’ note-taking behaviors and subsequent performance on exams. Participants took part in simulated classroom conditions where they watched a recorded lecture, took notes over the lecture, and were then tested over lecture content. There were three conditions in the study: a control group and two experimental groups. The control group simply watched the lecture, took notes on the lecture, and answered exam questions over lecture content. The other two groups engaged in the same activities as the control group, but also took part in simulated texting/Facebook interactions during the lecture; one group had a low frequency of texts/posts, and another had a high frequency. By using simulated text messages and Facebook posts, the objective of the study was to determine what effects, if any, these distractions had on student learning. Literature Review Mobile Phone Usage and Features Modern phones have a variety of features that simply were not possible years ago: Mobile phones are not just for voice communication anymore (Ishii, 2006). College students can access the Internet, send or receive text messages, check email, and even video chat with others quite literally from the palm of their hand. In addition, students can access a variety of social network sites (SNS) from their mobile phones. Scholars boyd and Ellison (2008) explain that SNS are online services that allow people to create a profile, create a list of other users who share a connection with the user, and view the lists of connections created by others within that system. For the purposes of the current study, we use the technical term SNS in place of other terminology (e.g., social networking sites) because SNS better conveys the way in which users communicate with others via these systems. boyd and Ellison note that other terms, like social networking sites, emphasize relationship initiation and users forming connections with others with whom they might not normally have come in contact. However, the term SNS better conveys the way in which users communicate with other people they have connected with. As boyd and Ellison put it, ‘‘They are 234 J. H. Kuznekoff and S. Titsworth Downloaded by [116.227.252.224] at 01:43 26 February 2014
Mobile Devices and Learning 235 primarily communicating with people who are already part of their extended social network"(2008,p.211).Thus far,survey data indicate that young adults are highly active users of SNS and other communication tools like text messaging. Texting,the ability to send short messages to another person,is perhaps one of the more popular features of modern cell phones.Roughly 94%of 18-34-year-olds report that they send or receive text messages using their phones,and 63%of this age group access the Internet using their phone(Zickuhr,2011).There is little question that students'communication habits regularly lead them to text while in class. Research conducted by the Pew Internet American Life Project found that 14-17- year-olds who text typically send and/or receive roughly 60 text messages a day. Furthermore,64%of teens with mobile phones have texted in class,and 23%access SNS via their phone(Lenhart,2010).Indeed,researchers at one university found that 62%of students admitted that they had texted while in class (Ransford,2009). Campbell(2006)reported that young people ages 18-23 are more tolerant of mobile phones in the classroom when compared to older age brackets.Essentially,"Young people tend to have very positive perceptions of mobile phones and regard the technology as an important tool for social connection"(Campbell,2006,p.290). Besides texting,accessing the Internet and SNS has become a prolific commu- nication activity among college students.Research shows that roughly 75%of online Et:I0e adults (18-24 year olds)have profiles on an SNS,and 89%of online adults use those sites to keep in touch with friends (Lenhart,2009).In regard to teens,77%of teens report that they contact their friends daily via text messaging,and 33%do so via SNS (Lenhart,2010).Statistics from Facebook,which as of June 2011 had over 500 million active users,documents that over 50%of the users log in each day(Facebook,2011). According to Facebook's own statistics,over 250 million active users access Facebook through a mobile device,and "People that use Facebook on their mobile devices are twice more active on Facebook than non-mobile users"(Facebook,2011,p.1).In 五 short,one might reasonably conclude that students'use of Facebook during class peojuM would be similar to rates of texting.However,posting to Facebook and sending a text message do serve different purposes.For example,a text message is typically sent to one recipient and is inherently interpersonal in nature.A Facebook post,or a status update,is generally viewable by a wider audience or even publicly available.Although texting and posting can serve different purposes,the physical act of both activities on a mobile device is fundamentally the same(i.e.,users engaging in communication activities via their mobile device).Because texting and posting both require the user to actively interact with her/his mobile device,these potentially distinct commu- nication activities would reasonably manifest in similar ways and with similar effects. As such,the remainder of this article will use the term texting/posting to refer to both activities.This labeling approach provides conceptual clarity while also incorporating both forms of communication. Clearly,texting/posting offers new communication channels that are frequently used by young adults to stay in contact with others.This ability to stay connected with others has allowed today's college students to remain constantly connected to other people,something that was not the case even a decade ago.As a practical
primarily communicating with people who are already part of their extended social network’’ (2008, p. 211). Thus far, survey data indicate that young adults are highly active users of SNS and other communication tools like text messaging. Texting, the ability to send short messages to another person, is perhaps one of the more popular features of modern cell phones. Roughly 94% of 1834-year-olds report that they send or receive text messages using their phones, and 63% of this age group access the Internet using their phone (Zickuhr, 2011). There is little question that students’ communication habits regularly lead them to text while in class. Research conducted by the Pew Internet & American Life Project found that 1417- year-olds who text typically send and/or receive roughly 60 text messages a day. Furthermore, 64% of teens with mobile phones have texted in class, and 23% access SNS via their phone (Lenhart, 2010). Indeed, researchers at one university found that 62% of students admitted that they had texted while in class (Ransford, 2009). Campbell (2006) reported that young people ages 1823 are more tolerant of mobile phones in the classroom when compared to older age brackets. Essentially, ‘‘Young people tend to have very positive perceptions of mobile phones and regard the technology as an important tool for social connection’’ (Campbell, 2006, p. 290). Besides texting, accessing the Internet and SNS has become a prolific communication activity among college students. Research shows that roughly 75% of online adults (1824 year olds) have profiles on an SNS, and 89% of online adults use those sites to keep in touch with friends (Lenhart, 2009). In regard to teens, 77% of teens report that they contact their friends daily via text messaging, and 33% do so via SNS (Lenhart, 2010). Statistics from Facebook, which as of June 2011 had over 500 million active users, documents that over 50% of the users log in each day (Facebook, 2011). According to Facebook’s own statistics, over 250 million active users access Facebook through a mobile device, and ‘‘People that use Facebook on their mobile devices are twice more active on Facebook than non-mobile users’’ (Facebook, 2011, p. 1). In short, one might reasonably conclude that students’ use of Facebook during class would be similar to rates of texting. However, posting to Facebook and sending a text message do serve different purposes. For example, a text message is typically sent to one recipient and is inherently interpersonal in nature. A Facebook post, or a status update, is generally viewable by a wider audience or even publicly available. Although texting and posting can serve different purposes, the physical act of both activities on a mobile device is fundamentally the same (i.e., users engaging in communication activities via their mobile device). Because texting and posting both require the user to actively interact with her/his mobile device, these potentially distinct communication activities would reasonably manifest in similar ways and with similar effects. As such, the remainder of this article will use the term texting/posting to refer to both activities. This labeling approach provides conceptual clarity while also incorporating both forms of communication. Clearly, texting/posting offers new communication channels that are frequently used by young adults to stay in contact with others. This ability to stay connected with others has allowed today’s college students to remain constantly connected to other people, something that was not the case even a decade ago. As a practical Mobile Devices and Learning 235 Downloaded by [116.227.252.224] at 01:43 26 February 2014
236 J.H.Kuznekoff and S.Titsworth matter,instructors remain concerned that such connection to the social world disconnects students from learning,leading some to ban all electronic communica- tion devices from lectures(Steinfatt,2009).Both theoretical and empirical evidence supports this concern,suggesting that students potentially split their attention in ways that cause them to miss important details presented during class,an outcome that could have potentially damaging effects on their achievement (Kraushaar Novak,2010;Wei et al.,2012). Classroom Attention Recent studies exploring the effects of texting/posting on student learning outcomes have relied on information processing theory (see Mayer,1996)as a basis for arguing that texting can cause distractions that hamper student learning.Briefly,information processing identifies attention,working memory,short-term memory,long-term memory,and metacognition as key resources used by individuals when they learn new information.Because learning is a process,diminished capacity with any single resource can impact other resources.Thus,in the case of texting/posting,students' attention can be divided,which can distract attention from on-task behavior.In turn, information processed in working/short-term memory may be incomplete or Et:I0e inaccurate,which could lead to inaccurate or insufficient storage of information in long-term memory. A variety of studies outside of the educational setting provide evidence that texting/posting can impede information processing.For instance,Just,Keller,and Cynkar (2008)found that simulated mobile telephone conversations disrupted driving performance by diverting attention away from the task of driving.Other researchers found that drivers talking on a mobile phone experienced visual distractions,such as failing to notice important visual cues like traffic lights or the environment surrounding road intersections(Trbovich Harbluk,2003).In general, papeojuMo these researchers concluded that "distracting cognitive tasks compete for drivers' attentional resources"(Harbluk,Noy,Trbovich,Eizenman,2007,p.378).Given the evidence surrounding dangers associated with using mobile devices while driving, many states now have laws penalizing drivers who text behind the wheel. Although not life-threatening in the classroom,texting/posting produces negative consequences for students and instructors.Burns and Lohenry (2010)found that both students and instructors identified mobile phone use as a distraction in class, and Campbell(2006)found that students and instructors perceived the ringing of cell phones in class as a problem.Although texting is considerably more covert than actual telephone conversations,a growing body of literature suggests that it is equally problematic. Kraushaar and Novak (2010)explored connections between classroom laptop usage and course achievement.The authors recruited students who voluntarily installed activity-monitoring software onto their laptops.This software recorded what programs were running and the times that each program was in use.Kraushaar and Novak developed a rubric to classify programs as productive or distractive
matter, instructors remain concerned that such connection to the social world disconnects students from learning, leading some to ban all electronic communication devices from lectures (Steinfatt, 2009). Both theoretical and empirical evidence supports this concern, suggesting that students potentially split their attention in ways that cause them to miss important details presented during class, an outcome that could have potentially damaging effects on their achievement (Kraushaar & Novak, 2010; Wei et al., 2012). Classroom Attention Recent studies exploring the effects of texting/posting on student learning outcomes have relied on information processing theory (see Mayer, 1996) as a basis for arguing that texting can cause distractions that hamper student learning. Briefly, information processing identifies attention, working memory, short-term memory, long-term memory, and metacognition as key resources used by individuals when they learn new information. Because learning is a process, diminished capacity with any single resource can impact other resources. Thus, in the case of texting/posting, students’ attention can be divided, which can distract attention from on-task behavior. In turn, information processed in working/short-term memory may be incomplete or inaccurate, which could lead to inaccurate or insufficient storage of information in long-term memory. A variety of studies outside of the educational setting provide evidence that texting/posting can impede information processing. For instance, Just, Keller, and Cynkar (2008) found that simulated mobile telephone conversations disrupted driving performance by diverting attention away from the task of driving. Other researchers found that drivers talking on a mobile phone experienced visual distractions, such as failing to notice important visual cues like traffic lights or the environment surrounding road intersections (Trbovich & Harbluk, 2003). In general, these researchers concluded that ‘‘distracting cognitive tasks compete for drivers’ attentional resources’’ (Harbluk, Noy, Trbovich, & Eizenman, 2007, p. 378). Given the evidence surrounding dangers associated with using mobile devices while driving, many states now have laws penalizing drivers who text behind the wheel. Although not life-threatening in the classroom, texting/posting produces negative consequences for students and instructors. Burns and Lohenry (2010) found that both students and instructors identified mobile phone use as a distraction in class, and Campbell (2006) found that students and instructors perceived the ringing of cell phones in class as a problem. Although texting is considerably more covert than actual telephone conversations, a growing body of literature suggests that it is equally problematic. Kraushaar and Novak (2010) explored connections between classroom laptop usage and course achievement. The authors recruited students who voluntarily installed activity-monitoring software onto their laptops. This software recorded what programs were running and the times that each program was in use. Kraushaar and Novak developed a rubric to classify programs as productive or distractive 236 J. H. Kuznekoff and S. Titsworth Downloaded by [116.227.252.224] at 01:43 26 February 2014
Mobile Devices and Learning 237 towards the student.Productive programs were those programs that were course- related (e.g.,Microsoft Office),while distractive programs included web surfing, entertainment,email,instant messaging,and computer operations."Using a browser to view an active window containing a course-related PowerPoint slide would be considered productive,while viewing an active window for a Web site that was unrelated to the course would be considered distractive"(Kraushaar Novak,2010, p.244).Their study found that 62%of the programs that students had open on their laptops were considered distracting.In addition,and of particular relevance to the current study,the researchers found that instant messaging was negatively correlated with quiz averages,project grades,and final exam grades. In an experiment testing whether texting negatively impacts students'ability to learn information,Wood and colleagues (2012)observed a small but consistent negative effect on exam performance when students engaged in simulated texting, emailing,or Facebook posting.They reasoned that when students engage in multiple simultaneous tasks,like texting and listening to lectures,one or both behaviors suffer. Similarly,Wei et al.(2012)found support for a causal model identifying texting as a significant mediating variable in the relationship between students'self-regulation,a key aspect of metacognition,and cognitive learning.Specifically,when higher rates Et:I0e of texting behavior are present,students tend to be less able to self-regulate their behaviors in ways that allow them to succeed on performance assessments.Although each of these studies concluded that texting can diminish learning because students' attention is divided,they did not identify specific mechanisms through which the diminished attention/diminished achievement link is made.By providing specific analysis of these mechanisms,teachers will have a greater ability to explain to students how their grades could be impacted when they text or post to Facebook during class.For example,when teachers want to explain the negative impact of texting in class,they can perhaps be more detailed by noting specific ways in which papeojuMo texting impacts student note taking and recall,and perhaps even work towards mitigating these negative effects. Lecture Listening and Note Taking Note taking is one of the most commonly practiced student behaviors;it is also one of the most important.In a meta-analysis of 33 separate studies,Kobayashi(2006) observed a large average weighted effect size of.77 when comparing the exam scores of students who take and review notes with those who do not.Practically speaking, students can score nearly one and one-half letter grades higher on exams when they take notes (Titsworth Kiewra,2004).The types of notes students take are also important.Makany,Kemp,and Dror (2009)found that when students took time to construct visual non-linear notes,they recorded more complete notes and had a 20%jump in comprehension assessment performance.Stated plainly,the quantity and quality of students'notes has dramatic impact on their ability to retain and use information
towards the student. Productive programs were those programs that were courserelated (e.g., Microsoft Office), while distractive programs included web surfing, entertainment, email, instant messaging, and computer operations. ‘‘Using a browser to view an active window containing a course-related PowerPoint slide would be considered productive, while viewing an active window for a Web site that was unrelated to the course would be considered distractive’’ (Kraushaar & Novak, 2010, p. 244). Their study found that 62% of the programs that students had open on their laptops were considered distracting. In addition, and of particular relevance to the current study, the researchers found that instant messaging was negatively correlated with quiz averages, project grades, and final exam grades. In an experiment testing whether texting negatively impacts students’ ability to learn information, Wood and colleagues (2012) observed a small but consistent negative effect on exam performance when students engaged in simulated texting, emailing, or Facebook posting. They reasoned that when students engage in multiple simultaneous tasks, like texting and listening to lectures, one or both behaviors suffer. Similarly, Wei et al. (2012) found support for a causal model identifying texting as a significant mediating variable in the relationship between students’ self-regulation, a key aspect of metacognition, and cognitive learning. Specifically, when higher rates of texting behavior are present, students tend to be less able to self-regulate their behaviors in ways that allow them to succeed on performance assessments. Although each of these studies concluded that texting can diminish learning because students’ attention is divided, they did not identify specific mechanisms through which the diminished attention/diminished achievement link is made. By providing specific analysis of these mechanisms, teachers will have a greater ability to explain to students how their grades could be impacted when they text or post to Facebook during class. For example, when teachers want to explain the negative impact of texting in class, they can perhaps be more detailed by noting specific ways in which texting impacts student note taking and recall, and perhaps even work towards mitigating these negative effects. Lecture Listening and Note Taking Note taking is one of the most commonly practiced student behaviors; it is also one of the most important. In a meta-analysis of 33 separate studies, Kobayashi (2006) observed a large average weighted effect size of .77 when comparing the exam scores of students who take and review notes with those who do not. Practically speaking, students can score nearly one and one-half letter grades higher on exams when they take notes (Titsworth & Kiewra, 2004). The types of notes students take are also important. Makany, Kemp, and Dror (2009) found that when students took time to construct visual non-linear notes, they recorded more complete notes and had a 20% jump in comprehension assessment performance. Stated plainly, the quantity and quality of students’ notes has dramatic impact on their ability to retain and use information. Mobile Devices and Learning 237 Downloaded by [116.227.252.224] at 01:43 26 February 2014
238 J.H.Kuznekoff and S.Titsworth The link between note taking and learning is established through two functions: the encoding and external storage hypotheses(see Rickards,1979).First,note taking allows students to create an external repository for information.After hearing a lecture,students can later go back to review information in preparation for an exam or other performance measure(Kiewra,1987).The encoding hypothesis assumes that the act of taking notes helps students process information into long-term memory.In describing the encoding function,Kiewra and colleagues(1991)note that the external storage and encoding functions complement one another and act in unison to promote learning. Despite the importance of taking notes,the classroom poses many obstacles to attaining a great set of notes."During lecture learning,students must continuously and simultaneously listen,select important ideas,hold and manipulate lecture ideas, interpret the information,decide what to transcribe,and record notes"(Kiewra et al., 1991,p.241).The challenge of these tasks can be compounded in situations with difficult subject matter,large enrollment classes that offer little opportunities for interaction,or student learning preferences for non-auditory presentation of materials (see Boyle,2012).In fact,numerous studies show that students are not very good note takers,generally recording less than 40%of the details contained in a lecture (e.g.,Boyle,2011;Kiewra,1985;Titsworth Kiewra,2004). Et:I0e Synthesis and Hypotheses In the current study,we posit that,like driving,engaging in classroom activity is a cognitively intensive task that requires vigilance and active listening (Titsworth, 2004).If students split attention between lecture listening and actively communicat- ing on an SNS or by texting,they may miss important cues and information from classroom lectures or discussion.Although previous research has shown that texting impedes learning (Kraushaar Novak,2010;Wei et al.,2012),few scholars have attempted to document specific processes through which such degradation in papeojuMo learning occurs. The goal of the present study is to ascertain the potential impact of texting/posting on students'note taking behaviors,and ultimately on student learning.The design used in this study called for dividing participants into one of three groups:a control group who listened and took notes and two groups who listened,took notes,and engaged in simulated texting/posting-one with a moderate level and another with a higher level of texting.We predicted that,like Kraushaar and Novak (2010),we would observe significant differences in students'test scores when comparing the control group against the moderate and high texting groups. HI:Students'scores on a multiple-choice test covering lecture material will be greatest for the group that does not text/post,followed by the group with moderate texting/posting and then the group with frequent texting/posting behaviors. H2:Students'scores on a free recall test will be greatest for the group that does not text/post,followed by the group with moderate texting/posting and then the group with frequent texting/posting
The link between note taking and learning is established through two functions: the encoding and external storage hypotheses (see Rickards, 1979). First, note taking allows students to create an external repository for information. After hearing a lecture, students can later go back to review information in preparation for an exam or other performance measure (Kiewra, 1987). The encoding hypothesis assumes that the act of taking notes helps students process information into long-term memory. In describing the encoding function, Kiewra and colleagues (1991) note that the external storage and encoding functions complement one another and act in unison to promote learning. Despite the importance of taking notes, the classroom poses many obstacles to attaining a great set of notes. ‘‘During lecture learning, students must continuously and simultaneously listen, select important ideas, hold and manipulate lecture ideas, interpret the information, decide what to transcribe, and record notes’’ (Kiewra et al., 1991, p. 241). The challenge of these tasks can be compounded in situations with difficult subject matter, large enrollment classes that offer little opportunities for interaction, or student learning preferences for non-auditory presentation of materials (see Boyle, 2012). In fact, numerous studies show that students are not very good note takers, generally recording less than 40% of the details contained in a lecture (e.g., Boyle, 2011; Kiewra, 1985; Titsworth & Kiewra, 2004). Synthesis and Hypotheses In the current study, we posit that, like driving, engaging in classroom activity is a cognitively intensive task that requires vigilance and active listening (Titsworth, 2004). If students split attention between lecture listening and actively communicating on an SNS or by texting, they may miss important cues and information from classroom lectures or discussion. Although previous research has shown that texting impedes learning (Kraushaar & Novak, 2010; Wei et al., 2012), few scholars have attempted to document specific processes through which such degradation in learning occurs. The goal of the present study is to ascertain the potential impact of texting/posting on students’ note taking behaviors, and ultimately on student learning. The design used in this study called for dividing participants into one of three groups: a control group who listened and took notes and two groups who listened, took notes, and engaged in simulated texting/posting*one with a moderate level and another with a higher level of texting. We predicted that, like Kraushaar and Novak (2010), we would observe significant differences in students’ test scores when comparing the control group against the moderate and high texting groups. H1: Students’ scores on a multiple-choice test covering lecture material will be greatest for the group that does not text/post, followed by the group with moderate texting/posting and then the group with frequent texting/posting behaviors. H2: Students’ scores on a free recall test will be greatest for the group that does not text/post, followed by the group with moderate texting/posting and then the group with frequent texting/posting. 238 J. H. Kuznekoff and S. Titsworth Downloaded by [116.227.252.224] at 01:43 26 February 2014
Mobile Devices and Learning 239 Whereas the first two hypotheses replicate patterns already observed in the literature,our primary objective was to explore mechanisms through which texting/ posting disrupts learning.Because note taking helps students encode information and serves as an external storage mechanism,we reasoned that any distraction caused by texting/posting would be apparent in the notes taken by students.Scholars have previously examined the number of details from the lecture that are also contained in the students'notes (see Titsworth Kiewra,2004;Titsworth,2004).If students' attention is diminished when texting/posting,the number of details recorded in their notes should be higher in the control group,followed by the two texting/posting groups. H3:Details recorded in students'notes will be greatest for the group that does not text/post,followed by the group with moderate texting/posting and then the group with frequent texting/posting. Finally,we predicted that note taking will be positively related to achievement levels on the two tests.This prediction is based on previous research showing a significant positive relationship between the number of details contained in notes and scores on both multiple-choice and open-ended tests (see Titsworth Kiewra,2004). H4:There will be a positive correlation between the number of details recorded in Et:I0 e ltt'tSt'LEZ' students'notes and their scores on multiple choice(H4a)and open-ended(H4b) tests over lecture material. Method Recruitment of Participants Participants in the study were students enrolled in one of several communication courses at a large Midwestern university.In those courses,students are required to participate in a research participation pool for a small amount of course credit. papeojuMo Following established departmental policies,students in the research pool were randomly assigned to one of several research projects being conducted within the department,of which this project was one.All students in the research participation pool completed a brief screening questionnaire when they initially registered for the overall research pool.The questionnaire posed several questions that helped the research pool administrator ascertain which participants met conditions to partici- pate in particular studies.Students assigned to our study needed to meet three requirements,which were included in the screening questionnaire.First,students needed to be 18 years of age or older and a current university student.Second, students needed to have access to a mobile phone capable of accessing the Internet. Finally,students needed to have not taken two specific classes:the Introduction to Human Communication course and the Interpersonal Communication course. Students who took either of the courses were excluded because those courses address theories covered in the lecture materials used for the study.Excluding students who had taken those courses minimized the risk of including participants with previous knowledge of the theories used in the stimulus materials.Both the research pool
Whereas the first two hypotheses replicate patterns already observed in the literature, our primary objective was to explore mechanisms through which texting/ posting disrupts learning. Because note taking helps students encode information and serves as an external storage mechanism, we reasoned that any distraction caused by texting/posting would be apparent in the notes taken by students. Scholars have previously examined the number of details from the lecture that are also contained in the students’ notes (see Titsworth & Kiewra, 2004; Titsworth, 2004). If students’ attention is diminished when texting/posting, the number of details recorded in their notes should be higher in the control group, followed by the two texting/posting groups. H3: Details recorded in students’ notes will be greatest for the group that does not text/post, followed by the group with moderate texting/posting and then the group with frequent texting/posting. Finally, we predicted that note taking will be positively related to achievement levels on the two tests. This prediction is based on previous research showing a significant positive relationship between the number of details contained in notes and scores on both multiple-choice and open-ended tests (see Titsworth & Kiewra, 2004). H4: There will be a positive correlation between the number of details recorded in students’ notes and their scores on multiple choice (H4a) and open-ended (H4b) tests over lecture material. Method Recruitment of Participants Participants in the study were students enrolled in one of several communication courses at a large Midwestern university. In those courses, students are required to participate in a research participation pool for a small amount of course credit. Following established departmental policies, students in the research pool were randomly assigned to one of several research projects being conducted within the department, of which this project was one. All students in the research participation pool completed a brief screening questionnaire when they initially registered for the overall research pool. The questionnaire posed several questions that helped the research pool administrator ascertain which participants met conditions to participate in particular studies. Students assigned to our study needed to meet three requirements, which were included in the screening questionnaire. First, students needed to be 18 years of age or older and a current university student. Second, students needed to have access to a mobile phone capable of accessing the Internet. Finally, students needed to have not taken two specific classes: the Introduction to Human Communication course and the Interpersonal Communication course. Students who took either of the courses were excluded because those courses address theories covered in the lecture materials used for the study. Excluding students who had taken those courses minimized the risk of including participants with previous knowledge of the theories used in the stimulus materials. Both the research pool Mobile Devices and Learning 239 Downloaded by [116.227.252.224] at 01:43 26 February 2014
240 J.H.Kuznekoff and S.Titsworth generally,and the procedures of this study in particular,were approved by the university's Institutional Review Board. A total of 54 students meeting the screening criteria signed up for and attended one of the meeting times for the present study.Participants were divided into one of three groups:a control group,a low-distraction group,and a high-distraction group. Seven participants experienced technical problems that did not allow them to fully participate.These participants did receive credit for participating in the study,but because they were not able to complete all of the required steps,their information was excluded from the study.This left a total of 47 participants,19 in the control group,14 in the low-distraction group,and 14 in the high-distraction group.The age of the participants ranged from 18 to 22,with the average age being 18.The majority of participants(55.3%)were first-year students,38.3%were sophomores,and 6.4% were juniors.The mean self-reported GPA of the participants was 3.33(SD=0.380). No statistically significant difference in age,GPA,or year in school was found between the three experimental conditions.All other aspects of the participants' demographics (e.g,sex and ethnicity)appeared consistent with the general student population of the university. Et:I0e Procedures and Manipulation After students had been assigned to this study,they were contacted by email and provided with basic directions for participation.They were asked to sign up,through the research participation system,to attend one of six meeting times in order to participate in the study and receive course credit.To achieve maximum participation, follow-up reminder emails were sent.Each timeslot was scheduled to last no longer 911] than one hour,and timeslots were scheduled for Monday through Thursday of the fifth week of the term.All study timeslots were scheduled for the early evening,and 五 each timeslot was randomly assigned to one of the three conditions:control,low- peojuM distraction,or high-distraction. All meeting sessions for the study occurred in a standard university classroom designed to accommodate approximately 30 people.Prior to participant arrival,an envelope was placed on each desk containing materials used in the study;each envelope was marked with a unique identification number.After questions had been answered and informed consent was obtained,students were shown a video lecture and instructed to take notes over the lecture using paper provided in the packets;they were instructed to take notes as they normally would in a typical class.Students were informed that at the end of the lecture they would be given a 3-min review period, during which they should review their notes as if they were studying for a test or quiz, and after this review they would take several learning assessments. After receiving initial instructions from the researcher,students in groups randomly assigned as the control condition were instructed to put their mobile phones away and then started watching the video lecture.Those groups assigned to either the low-or high-distraction conditions had two additional steps.First, students were instructed to take out their mobile phone capable of accessing the
generally, and the procedures of this study in particular, were approved by the university’s Institutional Review Board. A total of 54 students meeting the screening criteria signed up for and attended one of the meeting times for the present study. Participants were divided into one of three groups: a control group, a low-distraction group, and a high-distraction group. Seven participants experienced technical problems that did not allow them to fully participate. These participants did receive credit for participating in the study, but because they were not able to complete all of the required steps, their information was excluded from the study. This left a total of 47 participants, 19 in the control group, 14 in the low-distraction group, and 14 in the high-distraction group. The age of the participants ranged from 18 to 22, with the average age being 18. The majority of participants (55.3%) were first-year students, 38.3% were sophomores, and 6.4% were juniors. The mean self-reported GPA of the participants was 3.33 (SD0.380). No statistically significant difference in age, GPA, or year in school was found between the three experimental conditions. All other aspects of the participants’ demographics (e.g., sex and ethnicity) appeared consistent with the general student population of the university. Procedures and Manipulation After students had been assigned to this study, they were contacted by email and provided with basic directions for participation. They were asked to sign up, through the research participation system, to attend one of six meeting times in order to participate in the study and receive course credit. To achieve maximum participation, follow-up reminder emails were sent. Each timeslot was scheduled to last no longer than one hour, and timeslots were scheduled for Monday through Thursday of the fifth week of the term. All study timeslots were scheduled for the early evening, and each timeslot was randomly assigned to one of the three conditions: control, lowdistraction, or high-distraction. All meeting sessions for the study occurred in a standard university classroom designed to accommodate approximately 30 people. Prior to participant arrival, an envelope was placed on each desk containing materials used in the study; each envelope was marked with a unique identification number. After questions had been answered and informed consent was obtained, students were shown a video lecture and instructed to take notes over the lecture using paper provided in the packets; they were instructed to take notes as they normally would in a typical class. Students were informed that at the end of the lecture they would be given a 3-min review period, during which they should review their notes as if they were studying for a test or quiz, and after this review they would take several learning assessments. After receiving initial instructions from the researcher, students in groups randomly assigned as the control condition were instructed to put their mobile phones away and then started watching the video lecture. Those groups assigned to either the low- or high-distraction conditions had two additional steps. First, students were instructed to take out their mobile phone capable of accessing the 240 J. H. Kuznekoff and S. Titsworth Downloaded by [116.227.252.224] at 01:43 26 February 2014
Mobile Devices and Learning 241 Internet and to open their mobile web browser to a specific URL shown on the projection screen.The webpage to which they were directed provided a link to an online survey that was used to simulate texting/posting activity.The first question of the survey asked students to input the unique code found on their envelope.After this was completed,the survey proceeded to the second page that instructed students to wait while others entered their identification code.After everyone in the timeslot had arrived at this landing page,the researcher instructed the students to hit "Continue"and that they would automatically be presented with simulated texts/ posts following a predetermined schedule.For instance,one text/post asked parti- cipants,"What is your favorite restaurant for dinner?"and another asked participants to "Comment on this photo (the simulated text/post showed an actual photo)." Participants were instructed to respond to the texts/post presented to them by the survey.Aside from language describing the simulated communication as a text or a post,the simulated texts/posts were rather similar in nature.Of course,students were instructed to listen to the lecture and take notes as this was occurring. The two randomly assigned experimental groups represented low-and high- distraction conditions.In the low-distraction condition,participants were auto- matically given a new simulated text/post approximately every 60 seconds.The Et:I0e second condition,the high-distraction group,automatically received a simulated text/post approximately every 30 seconds.Students in the low-distraction group viewed roughly 12 texts/posts,while those students in the high-distraction group viewed roughly 24 texts/posts.The actual response to the simulated texts/post was left to the participants. Prior literature offers little guidance on how often students receive texts/posts during the course of a day,let alone during a class lecture.Survey research indicates that 18-to 24-year-olds send or receive nearly 110 text messages per day,and this is greater than the average of all other age groups combined(Smith,2011).Given these papeojuMo research findings,responding to 12 or 24 text messages in a short span of time is not outside the usual experience of many students.Though some participants may have found it overly distracting,it is important to note that students were instructed to respond to each interruption as best they could;the texts/posts merely comprised an element of the learning environment. Lecture The lecture used in this study lasted roughly 12 min and covered four communica- tion theories:uncertainty reduction theory,social penetration theory,social exchange theory,and relational dialectics theory.Within each theory,the lecture covered four topics:general explanation of the theory,assumptions of the theory,how the theory explains relationship formation,and how the theory explains relationship dissolu- tion.A male instructor not involved in this study was recruited to present the lecture from a script and to have this lecture recorded.Procedures called for each group to view the exact same lecture;thus,the content students viewed did not change,and
Internet and to open their mobile web browser to a specific URL shown on the projection screen. The webpage to which they were directed provided a link to an online survey that was used to simulate texting/posting activity. The first question of the survey asked students to input the unique code found on their envelope. After this was completed, the survey proceeded to the second page that instructed students to wait while others entered their identification code. After everyone in the timeslot had arrived at this landing page, the researcher instructed the students to hit ‘‘Continue’’ and that they would automatically be presented with simulated texts/ posts following a predetermined schedule. For instance, one text/post asked participants, ‘‘What is your favorite restaurant for dinner?’’ and another asked participants to ‘‘Comment on this photo (the simulated text/post showed an actual photo).’’ Participants were instructed to respond to the texts/post presented to them by the survey. Aside from language describing the simulated communication as a text or a post, the simulated texts/posts were rather similar in nature. Of course, students were instructed to listen to the lecture and take notes as this was occurring. The two randomly assigned experimental groups represented low- and highdistraction conditions. In the low-distraction condition, participants were automatically given a new simulated text/post approximately every 60 seconds. The second condition, the high-distraction group, automatically received a simulated text/post approximately every 30 seconds. Students in the low-distraction group viewed roughly 12 texts/posts, while those students in the high-distraction group viewed roughly 24 texts/posts. The actual response to the simulated texts/post was left to the participants. Prior literature offers little guidance on how often students receive texts/posts during the course of a day, let alone during a class lecture. Survey research indicates that 18- to 24-year-olds send or receive nearly 110 text messages per day, and this is greater than the average of all other age groups combined (Smith, 2011). Given these research findings, responding to 12 or 24 text messages in a short span of time is not outside the usual experience of many students. Though some participants may have found it overly distracting, it is important to note that students were instructed to respond to each interruption as best they could; the texts/posts merely comprised an element of the learning environment. Lecture The lecture used in this study lasted roughly 12 min and covered four communication theories: uncertainty reduction theory, social penetration theory, social exchange theory, and relational dialectics theory. Within each theory, the lecture covered four topics: general explanation of the theory, assumptions of the theory, how the theory explains relationship formation, and how the theory explains relationship dissolution. A male instructor not involved in this study was recruited to present the lecture from a script and to have this lecture recorded. Procedures called for each group to view the exact same lecture; thus, the content students viewed did not change, and Mobile Devices and Learning 241 Downloaded by [116.227.252.224] at 01:43 26 February 2014