Task-Technology Fit and ChatGPT Utilization: Factors Influencing Academic Performance among University Students

Nowadays, ChatGPT has quickly gained popularity among the generative AI tools used in the educational setting. This ease of access and flexibility have become the reasons for the growing popularity of ChatGPT in higher education. Nevertheless, ChatGPT’s ability to help with students’ academic activities may be determined not only by its technical features but also by the characteristics of the tasks performed and the individual users. The Task Technology Fit (TFF) framework is used in this study since ChatGPT is being utilized by university students as a technology that helps them perform different academic tasks. This study examines the relationships among task characteristics, technology characteristics, individual characteristics, TTF, ChatGPT utilization, and students’ academic performance. A total of 354 university students from UiTM Segamat Campus were involved in this study. The findings indicate that task characteristics, individual characteristics, task–technology fit, and ChatGPT utilization significantly influence students’ academic performance. However, technology characteristics do not significantly influence academic performance. This implies that the efficiency of ChatGPT depends not only on the technology itself but also on how suitable the academic assignments are, the individual qualities of the students, and the skills they must use with it. Consequently, students' proficiency in using ChatGPT effectively and synchronizing its functionalities with their educational requirements may improve academic performance.

ChatGPT utilization, Students’ Academic Performance, Task–technology fit

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