AccScience Publishing / DP / Online First / DOI: 10.36922/dp.8365
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ARTICLE

Development and evaluation of the Da Vinci AI Tutor: Enhancing accessibility and personalized learning in art history education

James Hutson1* ,  Tiffani Barner2
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1 Art History, AI, and Visual Culture, College of Arts and Humanities, Lindenwood University, Saint Charles, Missouri, United States of America
2 Game Design, College of Arts and Humanities, Lindenwood University, Saint Charles, Missouri, United States of America
DP, 8365 https://doi.org/10.36922/dp.8365
Submitted: 2 January 2025 | Revised: 14 March 2025 | Accepted: 24 March 2025 | Published: 17 April 2025
© 2025 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
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Abstract

This study examines the implementation of the Da Vinci AI Tutor, an innovative artificial intelligence (AI)-based tutoring platform designed specifically for enhancing personalized and accessible learning in art history within higher education. Launched in Fall 2024 at a private liberal arts institution in the Midwest, the system integrates a conversational AI avatar modeled after Leonardo da Vinci, incorporating immersive virtual reality environments and multimodal interaction capabilities to engage students across undergraduate survey courses, advanced Renaissance classes, and graduate comprehensive exam preparations. Addressing significant gaps in existing humanities education research, the current study explores two primary research questions: (i) How AI-driven tutors can enhance student engagement, accessibility, and learning outcomes within the humanities; and (ii) what technical and pedagogical limitations arise when integrating such solutions. Initial findings indicate measurable improvements in student engagement, comprehension, and accessibility, positioning the Da Vinci AI Tutor as a promising model for scalable, adaptable instruction in higher education contexts. However, technical challenges such as avatar realism and system compatibility across various devices highlight areas for continued refinement. The results underscore both the theoretical potential of AI-driven tutoring solutions in humanities education and practical implications for managerial and policy considerations, including platform compatibility and ethical deployment.

Keywords
AI tutor for humanities
Art history education
Accessibility in learning
Personalized education
Virtual reality in pedagogy
Funding
None.
Conflict of interest
The authors declare that they have no competing interests.
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