Examining Predictive Factors and Effects of In-Class Multitasking with Mobile Phones
Purpose: The study aims to give a descriptive account of university students' engagement with non-learning-related activities during class time and explore the relationship between off-task multitasking and learning. The predictive factors for off-task multitasking from individual, social and c...
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Veröffentlicht in: | Interactive Technology and Smart Education 2019-01, Vol.16 (1), p.49-58 |
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description | Purpose: The study aims to give a descriptive account of university students' engagement with non-learning-related activities during class time and explore the relationship between off-task multitasking and learning. The predictive factors for off-task multitasking from individual, social and class-related dimensions are also examined. Design/methodology/approach: Contextualized in a comprehensive university in Hong Kong, the study adopts a survey design and involves 79 samples. Findings: The data show that Hong Kong university students are avid users of mobile phones and heavily engage with digital devices. Off-task multitasking with mobile phones is a common phenomenon, yet not related to learning performance. Among the various media and apps on mobile phones, instant messenger stands out as the most frequently used app on a daily basis and inside the classroom. The individual device-use habit and classroom engagement are significant predictors for off-task multitasking during class time. Practical implications: This paper will allow teachers and students to be more aware of the causes and effects of off-task multitasking behaviors during class time and derive practical guidance and strategies to pay heed to and resist the disruptive influence of technologies on learning. Originality/value: The existing scholarly work show a mixed and incomplete picture regarding the effects and determining factors of students' multitasking. This study includes three variables from individual, social and teaching/learning dimensions and seeks to evaluate their predictive strengths. The results of the study will deepen our understanding of the patterns of off-task multitasking. |
doi_str_mv | 10.1108/ITSE-08-2018-0056 |
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The predictive factors for off-task multitasking from individual, social and class-related dimensions are also examined. Design/methodology/approach: Contextualized in a comprehensive university in Hong Kong, the study adopts a survey design and involves 79 samples. Findings: The data show that Hong Kong university students are avid users of mobile phones and heavily engage with digital devices. Off-task multitasking with mobile phones is a common phenomenon, yet not related to learning performance. Among the various media and apps on mobile phones, instant messenger stands out as the most frequently used app on a daily basis and inside the classroom. The individual device-use habit and classroom engagement are significant predictors for off-task multitasking during class time. Practical implications: This paper will allow teachers and students to be more aware of the causes and effects of off-task multitasking behaviors during class time and derive practical guidance and strategies to pay heed to and resist the disruptive influence of technologies on learning. Originality/value: The existing scholarly work show a mixed and incomplete picture regarding the effects and determining factors of students' multitasking. This study includes three variables from individual, social and teaching/learning dimensions and seeks to evaluate their predictive strengths. 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Practical implications: This paper will allow teachers and students to be more aware of the causes and effects of off-task multitasking behaviors during class time and derive practical guidance and strategies to pay heed to and resist the disruptive influence of technologies on learning. Originality/value: The existing scholarly work show a mixed and incomplete picture regarding the effects and determining factors of students' multitasking. This study includes three variables from individual, social and teaching/learning dimensions and seeks to evaluate their predictive strengths. 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Ku, Kelly Yee Lai ; Kong, Qiuyi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c369t-389fcc15b18d3f4dc816ecf37cda170a2a73d8aa2a7f670201874c852ee6e023</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Academic achievement</topic><topic>Applications programs</topic><topic>Attention</topic><topic>Behavior</topic><topic>Cell phones</topic><topic>Cellular telephones</topic><topic>Classrooms</topic><topic>College Students</topic><topic>Electronic devices</topic><topic>Foreign Countries</topic><topic>Grade Point Average</topic><topic>Handheld Devices</topic><topic>Internet</topic><topic>Learner Engagement</topic><topic>Learning</topic><topic>Multitasking</topic><topic>Preschool Children</topic><topic>Social factors</topic><topic>Social Influences</topic><topic>Social networks</topic><topic>Social research</topic><topic>Student Behavior</topic><topic>Students</topic><topic>Teaching</topic><topic>Telecommunications</topic><topic>Time Management</topic><topic>Time on Task</topic><topic>Undergraduate Students</topic><topic>University students</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Deng, Liping</creatorcontrib><creatorcontrib>Ku, Kelly Yee Lai</creatorcontrib><creatorcontrib>Kong, Qiuyi</creatorcontrib><collection>ERIC</collection><collection>ERIC (Ovid)</collection><collection>ERIC</collection><collection>ERIC</collection><collection>ERIC (Legacy Platform)</collection><collection>ERIC( SilverPlatter )</collection><collection>ERIC</collection><collection>ERIC PlusText (Legacy Platform)</collection><collection>Education Resources Information Center (ERIC)</collection><collection>ERIC</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection (ProQuest)</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Education Database</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Interactive Technology and Smart Education</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Deng, Liping</au><au>Ku, Kelly Yee Lai</au><au>Kong, Qiuyi</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><ericid>EJ1207416</ericid><atitle>Examining Predictive Factors and Effects of In-Class Multitasking with Mobile Phones</atitle><jtitle>Interactive Technology and Smart Education</jtitle><date>2019-01-01</date><risdate>2019</risdate><volume>16</volume><issue>1</issue><spage>49</spage><epage>58</epage><pages>49-58</pages><issn>1741-5659</issn><eissn>1758-8510</eissn><abstract>Purpose: The study aims to give a descriptive account of university students' engagement with non-learning-related activities during class time and explore the relationship between off-task multitasking and learning. 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subjects | Academic achievement Applications programs Attention Behavior Cell phones Cellular telephones Classrooms College Students Electronic devices Foreign Countries Grade Point Average Handheld Devices Internet Learner Engagement Learning Multitasking Preschool Children Social factors Social Influences Social networks Social research Student Behavior Students Teaching Telecommunications Time Management Time on Task Undergraduate Students University students |
title | Examining Predictive Factors and Effects of In-Class Multitasking with Mobile Phones |
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