Personalized Learning Through Generative AI

Generative Artificial Intelligence (GenAI), driven by large language models (LLMs), is reshaping education through adaptive explanations, tailored content, and interactive learning environments. This study investigates how students perceive and experience these capabilities in practice. A quantitative survey was conducted among learners at Ibn Zohr University, Morocco, between February 25 and April 14, 2025, using an anonymous Google Forms questionnaire with acceptable reliability (Cronbach’s alpha = 0.71). Construct validity was confirmed through factor analysis, and the data were analyzed using descriptive and inferential statistical techniques, including correlation, t-tests, Analysis of Variance (ANOVA), and regression analysis. The study explored students’ views on GenAI’s effectiveness in personalizing learning, adapting to individual styles and pace, and enhancing satisfaction. Results show that most participants acknowledged GenAI’s positive role in improving personalization, clarifying complex topics, and enriching learning experiences, though perceptions varied in consistency. By centering student perspectives, this research fills a gap in the literature largely focused on educators or systems and provides empirical insights into how GenAI can support personalized learning in higher education.