From Textbooks to Algorithms: The Impact of AI-Powered Personalized Learning on Historical Thinking Skills

Abstract

The rapid integration of artificial intelligence (AI) into education has transformed traditional history instruction from textbook-centered delivery to algorithm-driven personalized learning environments. AI-powered systems now adapt content, pacing, and assessment to individual learner profiles, offering new opportunities to cultivate historical thinking skills such as sourcing, contextualization, corroboration, and critical interpretation. However, the pedagogical implications of algorithmic mediation in history education remain underexamined, particularly regarding its influence on students’ cognitive engagement and disciplinary reasoning. Drawing on recent scholarship on AI in education and emerging research in AI-enhanced history learning, this study explores how personalized AI systems reshape historical thinking processes. The paper investigates the potential, limitations, and ethical considerations of AI-driven personalization in fostering higher-order historical reasoning. It argues that while AI technologies can enhance motivation and adaptive feedback, careful pedagogical design is essential to preserve the interpretive and humanistic dimensions central to historical inquiry.

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