Title:
GENERATIVE ARTIFICIAL INTELLIGENCE IN HISTORY EDUCATION: FROM CONTENT GENERATION TO SUPPORTING HISTORICAL THINKING COMPETENCE

Authors:
Phan Thi Thu, Pham Van Gieng, Do Thi Ngoc Hien and Nguyen Thi Viet Ha

Abstract:
Generative artificial intelligence (GenAI) is changing the cognitive environment and creating new demands for History education. Undirected use of GenAI may increase dependence on AI outputs and reduce opportunities for independent thinking. Drawing on theories of historical thinking, cognition and AI in education, this article proposes the AI-Historical Thinking Competence Model (AI-HCTM). The study uses a conceptual approach, drawing on existing theories and research to develop the proposed model. The model shifts the focus from using GenAI to generate content to using it to support historical inquiry and reasoning, while learners retain an active role. AI-HCTM emphasizes three directions: prompting grounded in evidence and context; tasks that require verification of AI outputs against historical sources; and assessment of the reasoning process rather than only the final product. In the model, the pedagogical value of GenAI lies in its capacity to support learners in sourcing, contextualization, corroboration, information verification and evidence-based reasoning.

Keywords:
Generative artificial intelligence (GenAI), History learning, historical thinking, AIHCTM, AI output verification

DOI:
https://doi.org/10.37500/IJESSR.2026.9521

Date of Publication: 20-10-2026