Understanding University Students’ Motivation for Using ChatGPT in Learning: A McClelland Theory Perspective

The increasing integration of artificial intelligence (AI) tools in higher education has transformed students’ learning experiences and academic practices. Among these tools, ChatGPT has gained considerable attention for its ability to support academic tasks, enhance learning efficiency, and facilitate student engagement. Guided by McClelland’s Theory of Needs, this study examines university students’ motivation for using ChatGPT in learning, with particular emphasis on the need for achievement, need for power, and need for affiliation. A quantitative research design was employed using a survey questionnaire administered to 123 university students enrolled in Mandarin language courses at a university branch campus. The instrument consisted of six sections measuring critical thinking, learner agency, academic performance, ChatGPT usage, student engagement, and motivational needs. Data were analyzed using descriptive statistics, independent samples t-tests, and Pearson correlation analysis. The findings indicate that students perceive ChatGPT as a useful learning tool that supports assignment completion, enhances learning efficiency, and contributes positively to academic performance. The results further revealed no significant differences in motivational needs based on gender or academic clusters. However, significant positive relationships were identified among the three motivational needs proposed by McClelland’s theory. The study also highlights that despite the increasing role of AI-assisted learning tools, instructor support and human interaction remain important in sustaining student engagement and meaningful learning experiences. The findings suggest that educators should integrate ChatGPT into educational practices in a balanced and pedagogically guided manner to support students’ motivation and learning outcomes in the digital learning environment.

ChatGPT, student motivation, McClelland’s Theory of Needs, AI-assisted learning, higher education

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