The impact of generative artificial intelligence on personalized learning: a case study in higher education
Keywords:
Generative Artificial Intelligence, Personalized Learning, Higher Education, Educational Technologies, Adaptive LearningAbstract
This literature review examines the impact of generative artificial intelligence (AGI) on personalized learning in higher education. Drawing on a critical analysis of recent studies published between 2018 and 2022, it examines AGI's ability to adapt learning content, styles, and pace to individual student characteristics and needs. It highlights how tools based on generative models, such as ChatGPT, are being used by instructors and students to foster a more flexible, interactive, and student-centered learning experience, positively influencing motivation, engagement, and academic performance. The article also analyzes various case studies and practical experiences from higher education institutions that have integrated these technologies into their teaching and learning processes. The study finally addresses the main ethical, pedagogical, and technological challenges posed by the implementation of AI in educational settings, such as the protection of personal data, equitable access to technologies, the risk of technology dependency, and the need to train teachers in its effective pedagogical use. The study concludes that, while generative AI is not without its limitations, it represents a transformative opportunity to move toward more personalized, inclusive, and effective educational models. However, its positive impact will largely depend on the development of clear institutional policies, responsible use of technologies, and ongoing training for the educational stakeholders involved
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