Document Type
Article
Publication Title
Design+
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.
DOI
https://dx.doi.org/10.36922/dp.8365
Publication Date
4-2025
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Recommended Citation
Hutson, James and Barner, Tiffani, "Development and evaluation of the Da Vinci AI Tutor: Enhancing accessibility and personalized learning in art history education" (2025). Faculty Scholarship. 733.
https://digitalcommons.lindenwood.edu/faculty-research-papers/733
Included in
Artificial Intelligence and Robotics Commons, History of Art, Architecture, and Archaeology Commons