THE PREDICTORS OF STUDENTS’ INTENTIONS TO USE LARGE LANGUAGE MODELS FOR ACADEMIC PURPOSES: EVIDENCE FROM HIGHER EDUCATION IN NIGERIA

Abstract

As Large Language Model (LLM) technology continues to evolve with its potential to revolutionise the field of education, students are becoming increasingly reliant on them to complete their academic tasks. This pilot study targeted university students and predicted their intentions to use LLMs through perceptions and academic self-efficacy. Relying on a correlational survey design, 89 first-year students was purposefully used as the sample frame for the study. The validity and reliability of the adopted instruments were both confirmed by experts in the field and with appropriate tools respectively. The assumed hypothetical associations were analysed using regression and Hayes moderation analyses. Findings revealed that students’ perceptions of LLMs (r2 = 0.719) and their academic self-efficacy (r2 = 0.146) are both positive, and are significant predictors of their intentions to use LLMs. Also, both variables jointly predicted 11.08% of students’ intention to use LLMs. Conclusion, limitations and future research directions are presented.