Motivations and Affordances of ChatGPT Usage for College Students’ Learning

Sun Kyong Lee, Jongsang Ryu, Yeowon Jie and Dong Hoon Ma
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Sun Kyong Lee: College of Media and Communication, Korea University, South Korea
Jongsang Ryu: College of Media and Communication, Korea University, South Korea
Yeowon Jie: College of Media and Communication, Korea University, South Korea
Dong Hoon Ma: College of Media and Communication, Korea University, South Korea

Media and Communication, 2025, vol. 13

Abstract: This study explored college students’ experiences and evaluations of using ChatGPT for class-related activities including essay writing, exam preparation, and homework. Students from two classes on the same subject were surveyed, and quantitative data on their motivations and usage of ChatGPT were collected (Class 1, n = 48; Class 2, n = 106; N = 154). Hierarchical regression analysis revealed that using ChatGPT as a study guide and for active interaction were significant predictors of actual usage level, while its usage for entertainment and study guide was associated with higher trust in the tool. We further collected qualitative data through open-ended surveys (Class 1, n = 154; Class 2, n = 106). Responses were manually coded and thematically analyzed, with comparisons drawn between the two classes. Students’ perceptions varied, with many acknowledging the affordances of ChatGPT, such as helping to organize thoughts, clarifying concepts, and structuring essays. However, some participants raised concerns about the tool’s limitations—particularly its potential to inhibit critical and creative thinking—as well as issues related to the reliability, accuracy, and quality of information provided. The implications of these findings are discussed in relation to the uses and gratifications theory, the technology acceptance model, and the concept of media affordances.

Keywords: affordances; ChatGPT; ChatGPT usage; generative AI; higher education; motivation (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:cog:meanco:v13:y:2025:a:9508

DOI: 10.17645/mac.9508

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