Generative Artificial Intelligence in Higher Education: An Educational Analysis of Its Implications for Academic Performance and the Role of the University Instructor

Abstract

Higher education has witnessed rapid transformations in recent years due to the advanced development of generative artificial intelligence models, which have become capable of producing sophisticated academic content that closely resembles human output. This development has reshaped the university learning environment, directly influencing students’ academic performance and redefining the role and identity of university instructors. This study aims to examine the impact of generative artificial intelligence models on students’ academic performance in higher education and to analyze the implications of this impact for the pedagogical and professional role of university instructors. The study adopts a descriptive-analytical approach based on a review and analysis of relevant educational literature and recent studies. The findings indicate that generative artificial intelligence can support deep learning and enhance analytical and reasoning skills when appropriately integrated into educational practices. However, excessive or unregulated reliance on these models may undermine authentic learning and reduce students’ independent cognitive effort. The study emphasizes the need to redefine the role of the university instructor as a facilitator of learning and an ethical and cognitive guide for the responsible use of generative artificial intelligence, in order to preserve academic values and ensure the quality of higher education.