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Generative AI-powered arts-based learning in middle school history: Impact on achievement, motivation, and cognitive load

Author

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  • Jing Chen
  • Nur Azlina Mohamed Mokmin
  • Shen Qi

Abstract

This study explores the potential of integrating generative artificial intelligence (GAI) technologies into middle school history education. Aiming to move beyond traditional teacher-led, text-based instruction, the study examines how GAI can support interactive, personalized, and arts-based learning experiences. Conducted in a 7th-grade history classroom with 66 participants, the study employed a quasi-experimental design. Participants were divided into an experimental group, which utilized an arts-based learning system incorporating ChatGPT and DALL-E 3, and a control group, which followed traditional learning methods. Results highlighted the effectiveness of the GAI-powered ABL learning system in enhancing students’ historical knowledge and motivation and reducing cognitive load. These results provide empirical support for the use of GAI tools in educational settings and highlight their potential to transform history instruction. The study offers broader implications for integrating GAI into K-12 curricula, emphasizing its role in fostering creative expression, personalized learning, and students’ overall development.

Suggested Citation

  • Jing Chen & Nur Azlina Mohamed Mokmin & Shen Qi, 2025. "Generative AI-powered arts-based learning in middle school history: Impact on achievement, motivation, and cognitive load," The Journal of Educational Research, Taylor & Francis Journals, vol. 118(6), pages 688-700, November.
    • Handle: RePEc:taf:vjerxx:v:118:y:2025:i:6:p:688-700
    DOI: 10.1080/00220671.2025.2510395
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