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Managing Student Digital Distraction in the College Classroom: a Self-Determination Theory Perspective.

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Title: Managing Student Digital Distraction in the College Classroom: a Self-Determination Theory Perspective.
Authors: Flanigan, Abraham E. (AUTHOR), Brady, Anna C. (AUTHOR), Dai, Yan (AUTHOR), Ray, Emily (AUTHOR)
Source: Educational Psychology Review. Jun2023, Vol. 35 Issue 2, p1-19. 19p.
Abstract: Undergraduate student misuse of mobile technology (e.g., smartphones, laptops, tablets) for non-class purposes (e.g., texting, scrolling social media, playing games) has become ubiquitous in college classrooms across the globe. In addition, research has suggested that these digital distractions can negatively impact learning and performance. The prevalence and negative consequences of student digital distraction in the classroom require college instructors to proactively regulate student use of digital devices to protect the integrity of the learning environment. The present article aims to provide college instructors with a framework of strategies to curb student digital distraction. Specifically, the present article draws from the tenets of Self-Determination Theory (SDT) to illustrate how and why common policies and strategies intended to curb student digital distraction can inadvertently threaten students’ basic psychological needs for autonomy, competence, and relatedness in the classroom and, subsequently, alienate students against instructors. The article concludes by presenting evidence-based digital distraction prevention strategies that can buffer against student digital distraction without threatening students’ basic psychological needs or alienating students against their instructors. [ABSTRACT FROM AUTHOR]
Copyright of Educational Psychology Review is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Managing Student Digital Distraction in the College Classroom: a Self-Determination Theory Perspective.
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  Data: Undergraduate student misuse of mobile technology (e.g., smartphones, laptops, tablets) for non-class purposes (e.g., texting, scrolling social media, playing games) has become ubiquitous in college classrooms across the globe. In addition, research has suggested that these digital distractions can negatively impact learning and performance. The prevalence and negative consequences of student digital distraction in the classroom require college instructors to proactively regulate student use of digital devices to protect the integrity of the learning environment. The present article aims to provide college instructors with a framework of strategies to curb student digital distraction. Specifically, the present article draws from the tenets of Self-Determination Theory (SDT) to illustrate how and why common policies and strategies intended to curb student digital distraction can inadvertently threaten students’ basic psychological needs for autonomy, competence, and relatedness in the classroom and, subsequently, alienate students against instructors. The article concludes by presenting evidence-based digital distraction prevention strategies that can buffer against student digital distraction without threatening students’ basic psychological needs or alienating students against their instructors. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Educational Psychology Review is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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