Authors: Mrs, Seema Amol More, Professor Dr. Swati Nitin Sayankar
Abstract: Education 5.0 represents a paradigm shift toward human-centric, ethical, and sustainable learning ecosystems by synergizing advanced digital technologies with societal needs. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as key enablers in transforming higher education through personalized learning, predictive analytics, and intelligent decision support. However, the absence of a unified and scalable framework often leads to fragmented adoption and ethical concerns. This paper proposes a comprehensive AI–ML framework tailored for higher education institutions from an Education 5.0 perspective. The framework integrates data-driven learning analytics, adaptive instructional systems, student performance prediction, and automated academic administration while emphasizing transparency, inclusivity, and data privacy. The proposed architecture consists of layered modules encompassing data acquisition, intelligent processing, decision intelligence, and stakeholder interaction. A conceptual case study demonstrates the applicability of the framework in a university environment. Comparative analysis highlights improvements in academic outcomes, operational efficiency, and learner engagement. The proposed framework provides a structured pathway for institutions seeking sustainable and ethical AI adoption, contributing to the evolving discourse on next-generation higher education systems.
DOI: http://doi.org/10.5281/zenodo.18204804
