PERSONALIZED AND ADAPTIVE LEARNING ENVIRONMENTS: PEDAGOGICAL FOUNDATIONS AND TECHNOLOGICAL ARCHITECTURES

Abstract

The faster adoption of AI technology in higher education is changing teaching practices that require a rethink of their traditional pedagogy. A discussion of the socio-technical implications of generative AI and probing the impact on academic integrity, curriculum and educators has been carried on. As machine learning algorithms improve, they offer new possibilities for personalized learning trajectories and administrative efficiencies; yet they also present complex and unprecedented ethical concerns regarding data privacy, algorithmic bias, and potential erosion of critical thinking. This study brings together existing research in order to understand how institutions are balancing the adoption of technology and the maintenance of academic rigour. The present study dives into the shift from automated assessment instruments towards the use of AI-enhanced collaboration platforms. By assessing the effectiveness of new policy frameworks, this study aims to highlight the need for enhancing AI literacy among faculty and students. At the end of the activity, the significance of the work becomes clear. It contributes significantly to a sustainable roadmap for digital transformation, stressing a human-centric approach with the use of computation while ensuring the individual’s intellectual sovereignty, promoting access to a variety of social partners, governments, and organizations. The future of the academy depends not on excluding these, but on realigning values within an ever-more automated global society. Hence, these findings are encouraging.