The rapid integration of Artificial Intelligence (AI) into education has created unprecedented opportunities for developing adaptive teaching and learning environments. This systematic research review synthesises findings from peer-reviewed empirical studies published between 2020 and 2025, sourced from databases including Scopus, Web of Science, IEEE Xplore, and ERIC. The review examines the key AI technologies driving adaptive learning—machine learning, deep learning, natural language processing (NLP), reinforcement learning, and generative AI—and evaluates their impact on personalised instruction, learner engagement, academic performance, and pedagogical effectiveness. Findings reveal that AI-enabled adaptive systems consistently produce moderate-to-large positive effect sizes on learning outcomes (g = 0.70), with generative AI tools such as ChatGPT catalysing a significant acceleration in research activity from 2022 onward. The review also identifies persistent challenges including algorithmic bias, data privacy concerns, teachers' resistance to adoption, equity gaps, and the relative scarcity of longitudinal studies. Recommendations for researchers, educators, and policymakers are provided. The paper concludes that AI holds transformative potential for adaptive pedagogy but requires carefully designed human-centred frameworks to realise equitable and sustainable educational outcomes.
Patil et al. (2026) studied this question.
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