Paper Type

ERF

Abstract

This study examines the unintended consequences of generative artificial intelligence (GenAI) use on student engagement in classroom settings. Grounded in social cognitive theory, the study proposes that student–GenAI interaction reduces engagement with peers and instructors through the mechanism of help-seeking avoidance. It further incorporates cognitive load theory to explain how task complexity strengthens this relationship. Personality traits are also considered as moderating factors shaping students’ reliance on GenAI versus interpersonal interaction. Using survey data from university students, this study aims to highlight the social implications of excessive GenAI use and contribute to understanding how AI-driven learning environments influence behavioral and emotional engagement.

Paper Number

1586

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Aug 15th, 12:00 AM

When GenAI Usage Backfires: A Help-Seeking Avoidance Model of Student Engagement

This study examines the unintended consequences of generative artificial intelligence (GenAI) use on student engagement in classroom settings. Grounded in social cognitive theory, the study proposes that student–GenAI interaction reduces engagement with peers and instructors through the mechanism of help-seeking avoidance. It further incorporates cognitive load theory to explain how task complexity strengthens this relationship. Personality traits are also considered as moderating factors shaping students’ reliance on GenAI versus interpersonal interaction. Using survey data from university students, this study aims to highlight the social implications of excessive GenAI use and contribute to understanding how AI-driven learning environments influence behavioral and emotional engagement.

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