The Information Age for Education via Artificial Intelligence and Machine Learning: A Bibliometric and Systematic Literature Analysis

Abstract

The subject of integrating AI and ML into education is booming, but we still need more research on the real effects on students’
learning outcomes and the long-term consequences of this trend. Our work fills this need by proposing a new technique that
follows the PRISMA guidelines and combines bibliometric analysis with a Systematic Literature Review (SLR). The first step
was a thorough bibliometric investigation, which uncovered important countries, schools, publications, keywords, and writers
working in the field of artificial intelligence and machine learning for educational purposes. This stage highlighted the international
and multidisciplinary character of AI/ML research in education by providing a bird’s-eye view of the field’s current state.
A careful SLR of 22 chosen academic publications was the next step. This comprehensive analysis clarifies the present uses, new
tendencies, difficulties, and potential future paths of AI and ML in the classroom. Results from this mixed-method study highlight
the revolutionary potential of AI and ML for education and provide a thorough road map for academics, policymakers, and
teachers. Predicting academic success, improving e-learning experiences, and preparing future generations for AI’s integration in
various fields like healthcare are just a few of the many areas where AI has had a profound and varied influence on education, as
explored in this review’s extensive article collection. Not only does this research provide a foundation for successfully using AI
and ML technologies in education, but it also highlights the revolutionary potential of AI in changing educational environments.