From AI readiness to course chatbots: explaining students’ intentions to use instructor-developed generative tools in higher education

This study examines college students’ behavioral intention to use an instructor-developed, course-specific generative artificial intelligence (AI) chatbot for formative feedback. A total of 146 students from Biotechnology and Management courses used the chatbot while completing an assignment. Drawing on the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT), the study tested whether students’ intention to use the course chatbot (BIUC) was predicted by their general intention to use AI tools (BIU), perceived usefulness, perceived value, perceived ease of use, trust, and enjoyment. The findings showed that BIU was the strongest predictor of BIUC, followed by perceived value and perceived usefulness. Trust and enjoyment were positively correlated with BIUC but were not significant predictors in the full regression model. Group comparisons indicated higher adoption intentions among Biotechnology students, native-language speakers, and older students, while no gender differences were found. The findings highlight the importance of distinguishing between general AI readiness and course-specific chatbot adoption in higher education.