GENERATIVE ARTIFICIAL INTELLIGENCE IN ERP EDUCATION: THE ROLE OF PERSONALITY TRAITS AND GAI PERCEPTIONS IN ACADEMIC PERFORMANCE

The increasing use of generative artificial intelligence (GenAI) in higher education has raised important questions about its role in student learning and academic performance.While prior research suggests that GenAI tools can enhance learning outcomes, their effectiveness may depend on how students use them and on individual learner characteristics.This study examines the relationship between GenAI usage, personality traits, and academic performance in an enterprise resource planning (ERP) course.Using data from undergraduate students, GenAI usage was measured through survey-based perceptions and reduced into four dimensions using exploratory factor analysis, while personality traits were assessed using the Big Five framework.Student performance was evaluated across conceptual understanding, system operation performance, and overall course learning outcomes.The results suggest that GenAI usage alone does not consistently predict improved academic performance, particularly in highly specialized, complex subject areas such as ERP.In contrast, personality traits show more consistent relationships with performance, and interaction effects indicate that the effectiveness of GenAI depends on its alignment with individual learner characteristics.Overall, the findings highlight that generative AI functions as a context-dependent learning tool whose impact varies across students and learning environments.