Artificial Intelligence in Higher Education: Examining Its Impact on Student Learning, Engagement, and Academic Performance

Artificial Intelligence (AI) is increasingly integrated into higher education to support various learning activities, yet its overall impact on students remains inconsistently reported across the literature. This article reviews existing studies to examine the impact of AI on three interrelated aspects of higher education: student learning, student engagement, and academic performance. A literature review method was used, drawing on systematic reviews and meta-analyses that discuss AI applications and outcomes in higher education settings. The review shows that AI can support student learning through explanations, personalized feedback, and access to learning resources, while also raising concerns about overreliance and reduced critical thinking. Regarding engagement, evidence is relatively strong for behavioral engagement but more mixed for emotional and cognitive engagement. For academic performance, several systematic reviews and meta-analyses report positive effects of AI, particularly in STEM-related areas, although the specific impact of AI adoption still requires further investigation in certain learning contexts such as open and distance learning. Taken together, these findings suggest that the impact of AI in higher education should be examined not only through academic outcomes but also through how it shapes students' learning process and engagement, with AI functioning best as a supporting tool rather than a replacement for students' active involvement in learning.