Impact of GPT Chatbot Integration on Student Competencies and Outcomes in University Entrepreneurship Education

This study aimed to empirically examine the impact of a GPT-based knowledge chatbot on students’ learning experiences and the quality of outcomes in a university-level entrepreneurship education course. A quasi-experimental design was applied to 80 students, divided into two groups, enrolled in the general elective course “University Entrepreneurship” at University A. The experimental group participated in an interactive class utilizing a GPT chatbot, while the control group received traditional lecture- and project-based instruction. Post-surveys were conducted to quantitatively assess five dimensions of learning experience—learning motivation, class satisfaction, creativity, self-directed learning, and teamwork experience. In addition, team deliverables were evaluated by entrepreneurship experts through both quantitative and qualitative analyses. The results indicated that the experimental group showed statistically significant improvements over the control group in creativity, self-directed learning, and teamwork experience. Expert assessments also revealed higher performance in problem definition, logical structure, and creativity for the chatbot-integrated group. Qualitative analysis suggested that the GPT chatbot provided meaningful support in idea generation, information organization, and logical development, thereby enhancing learners’ cognitive engagement and overall task performance. These findings imply that GPT-based chatbots can be pedagogically effective in instructional contexts that demand complex thinking and creativity beyond disciplinary knowledge, such as entrepreneurship education. This study offers empirical evidence on the educational potential of generative AI tools in higher education and provides practical insights for future instructional design and implementation. Limitations regarding information reliability, long-term effects, and learner overreliance are also discussed, with suggestions for future research directions.