From Traditional to Intelligent Systems: Reviewing the Role of AI-Integrated IT Models in Advancing Physics Education in Higher Education Winanda Amilia (a*), Basuki Wibawa (b)
Universitas Negeri Jakarta
Abstract
The rapid evolution of educational technology, particularly advancements driven by Artificial Intelligence (AI), has significantly reshaped the landscape of tertiary physics education. This Systematic Literature Review aims to critically examine the role and impact of AI-integrated technology-based learning models in enhancing university-level physics instruction. Employing the PICOS framework, the review focuses on empirical studies published between 2019 and 2024 that investigate AI-enhanced learning interventions in comparison to traditional and IT-based learning model non-AI. This review synthesizes findings related to conceptual understanding, critical thinking, and student motivation-three key outcomes in physics education. A comprehensive search was conducted across major academic databases, including Scopus, ScienceDirect, and Google Scholar, followed by a rigorous screening process based on predefined inclusion and exclusion criteria. The analysis reveals emerging trends in the adoption of intelligent systems such as adaptive learning environments, AI-driven simulations, and intelligent tutoring systems, which consistently demonstrate improvements in learning effectiveness and student engagement. However, the review also identifies notable research gaps, including the limited availability of longitudinal studies and the need for deeper integration with pedagogical frameworks. The study concludes with recommendations for future research and practical implications for educators and institutions seeking to leverage AI to advance physics instruction in higher education.
