AI Applications for Ancient Art History Education
Open accessAbstract
Recent global surveys (Chegg, 2025; Freeman, 2025) indicate that the vast majority of undergraduates already use generative AI (GenAI) to support their studies, and many want structured, ethical guidance from their institutions. This paper responds from the perspective of ancient art history education. First, it presents a case study of an interdisciplinary course (AI & Us, Arkansas State University, Spring 2024) co-taught by faculty in art history, philosophy, and graphic design, arguing that expert-led, cross-disciplinary framing is decisive for cultivating AI literacy and critical engagement. Second, it proposes classroom applications tailored to ancient art history at different levels: (a) a reverse prompt-engineering exercise that develops recognition and visual-analysis skills using AI-generated images as objects of inquiry; and (b) prompt-driven discussions that surface dataset bias and strengthen students’ search and source-evaluation practices. The activities go beyond prompt engineering alone and are designed to promote reflective, ethical, and academically rigorous uses of GenAI in both classroom learning and research.
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GenAI outputs can function as pedagogical objects that strengthen visual analysis when students interrogate them.
“GenAI outputs can also function as pedagogical objects that strengthen visual analysis when students interrogate why images look persuasive, where bias may appear, and how prompt choices shape interpretation, aligning tool use with critique culture rather than final-product substitution (Smith 2025).”
From A Study on the Role of Midjourney, A Generative Artificial Intelligence Tool, in Enhancing Student Creativity in Illustration Design Classes (2026) · cites this paper as Smith 2025
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He, S. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70305
Gülden, S. (2026) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-032-39734-8_25
- Authors
- Smith, C.
- Affiliations
- Arkansas State University (US)
- Corresponding author
- Smith, Caitlan
- ORCID
- Smith, Caitlan
- Venue
- AI & Antiquity
- Published
- 2025-09-24
- Volume
- 1
- Issue
- 1
- Pages
- 67-92
- ISSN
- 3081-4553 (ISSN-L)
- OpenAlex
- W4414474993
- Cited by
- 3
- References
- 0
- Citations by year
- 2026: 3
- FWCI
- 3.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- AI & Antiquity (publishedVersion, cc-by)
- RACO (Revistes Catalanes amb Accés Obert) (Consorci de Serveis Universitaris de Catalunya) (publishedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art Education and Development
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
- Keywords
- generative AI in education, ancient art history, AI literacy, prompt engineering, interdisciplinary teaching, data bias, source evaluation, visual analysis, AI ethics, AI-generated images
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