Research Hotspots and Emerging Trends in AI-Powered Personalized Learning and Academic Performance in Higher Education Using CiteSpace (2015–2025)

Abstract

Artificial intelligence (AI) is increasingly used to personalize learning and support academic performance in higher education, yet the field’s intellectual structure and emerging directions remain fragmented. This study maps the evolution of research hotspots and trends through a scientometric analysis of 193 Web of Science records published between 2015 and 2025. CiteSpace 7.0.1 was used to examine publication growth, country and institutional collaboration, keyword co-occurrence and clustering, timeline patterns, citation bursts, and reference co-citation networks. The findings show rapid expansion after 2023, with China contributing the largest number of publications. Major research themes include intelligent tutoring systems, learning analytics, adaptive learning interventions, deep learning, university transformation, and positive student outcomes. Keyword bursts indicate a shift from rule-based and fuzzy-logic approaches toward adaptive learning, performance evaluation, and generative-AI-supported personalization. Overall, the field is moving toward data-intensive, learner-centred, and outcome-oriented research, while causal evidence, equity, privacy, theoretical integration, and cross-institutional validation remain important priorities.