Generative AI-powered arts-based learning in middle school history: Impact on achievement, motivation, and cognitive load
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.
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Text-to-image systems are employed to enhance visual originality, learning motivation, and awareness of copyright and ethics.
“Text-to-image systems are employed to enhance visual originality, learning motivation, and awareness of copyright and ethics [111-114].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [113]
In visual arts, learners employ Midjourney, DALL·E, and related text-to-image tools, repeatedly adjusting prompts to refine visual detail and aesthetics.
“In visual arts, learners employ Midjourney, DALL·E, and related text-to-image tools, repeatedly adjusting prompts to refine visual detail and aesthetics [111-116,132,143]”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [113]
Teachers play a critical role as facilitators and supporters, working alongside AI to analyze learning data, refine creative or experimental processes, and provide timely guidance for topic selection, content iteration, and project reflection.
“Teachers play a critical role as facilitators and supporters, working alongside AI to analyze learning data, refine creative or experimental processes, and provide timely guidance for topic selection, content iteration, and project reflection [112,113,116,136].”
From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [113]
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- Authors
- Chen, J., Mokmin, N. A. M., & Qi, S.
- Affiliations
- Universiti Sains Malaysia (MY)
- Jiangsu Maritime Institute (CN)
- Corresponding author
- Mokmin, Nur Azlina Mohamed
- Venue
- The Journal of Educational Research
- Publisher
- Informa UK Limited
- Published
- 2025-05-31
- Volume
- 118
- Issue
- 6
- Pages
- 688-700
- ISSN
- 0022-0671 (ISSN-L)
- 1940-0675
- OpenAlex
- W4410916398
- Semantic Scholar
- b8d40348de9a8ca7cf48cb26c3f653bdcd1a7f74
- Cited by
- 15
- References
- 68
- Citations by year
- 2026: 9 · 2025: 6
- FWCI
- 15.53
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Journal of Educational Research (publishedVersion)
- Funders
- Ministry of Higher Education Malaysia (FRGS/1/, /SSI0/USM/02/10)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Sociology and Political Science › Educator Training and Historical Pedagogy
- Keywords
- generative AI, arts-based learning, middle school history education, ChatGPT, DALL-E 3, academic performance, student motivation, cognitive load, personalized learning, history education
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