The Future of Learning with AI: A Systematic Review on Transforming Student Education and Competencies

Abstract

Artificial Intelligence in Education (AIED) has evolved into a substantial research field, generating a diverse body of literature with varied perspectives and applications. This review synthesizes empirical studies published between 2014 and 2024, examining AIED’s integration across secondary and higher education with a focus on pedagogical strategies and tools, ethical considerations, institutional collaboration, and the application of machine learning models in teaching, learning, and assessment. An initial mapping of 4,076 research articles, refined through an in-depth analysis of 62 selected studies, provides a robust conceptual framework of the current knowledge landscape. The findings highlight AIED’s transformative role in secondary and higher education by enhancing pedagogy, addressing ethical challenges, fostering institutional collaboration, and leveraging machine learning applications. These insights provide strategic direction for teachers, administrators, and policymakers in shaping effective, ethical, and inclusive integration of AIED in education. Future research should emphasize enhancing explainable AI, mitigating ethical risks, and evaluating AI tools in diverse real-world classroom contexts.

Keywords:  Artificial Intelligence in Education, Machine Learning Models,  Ethical Challenge, pedagogical strategies,   Explainable AI, Secondary and Higher Education

https://doi.org/10.5281/zenodo.18270365