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Design+ Da Vinci AI Tutor in art history learning

modalities. Immersive simulations using VR and areas, including peer and professional tutoring programs,
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extended reality (XR) provide an intuitive grasp of spatial demonstrating outcomes comparable to in-person sessions
and material culture in historical contexts, reinforcing when supported by robust technological frameworks.
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Kolb’s experiential learning theory. 24 However, the rapid shift also exposed challenges,
Therefore, this study examines the potential of AI-based particularly in accessibility and equity. Students from
tutoring systems, specifically through the Da Vinci AI underserved or economically disadvantaged backgrounds
Tutor, as innovative and disruptive educational solutions faced significant barriers to remote learning, including
addressing persistent gaps within humanities pedagogy – inconsistent access to reliable internet and digital devices.
particularly the challenges of personalization, accessibility, Educators, too, encountered difficulties, especially when
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and student engagement in art history education. Despite lacking adequate training in digital pedagogical tools.
extensive research validating the efficacy of such tutors Moreover, the impersonal nature of online interactions
within STEM fields, scholarship examining the application highlighted the limitations of digital tutoring in replicating
and effectiveness of such technologies in the humanities the relational benefits of face-to-face engagement, such
remains scarce, leaving critical gaps regarding how as non-verbal communication cues and personalized
intelligent systems can foster analytical and interpretive feedback.
skills in disciplines characterized by nuanced, contextual Nevertheless, these challenges sparked innovation.
analysis. Drawing on disruptive innovation theory, 25-27 this Emerging technologies, such as virtual learning platforms
research positions the tutor as an educational tool capable and algorithm-driven systems, allowed institutions to adapt
of overcoming longstanding pedagogical limitations tutoring practices to the demands of a global pandemic.
related to scalability, individualized instruction, and Many universities implemented blended models,
equitable access. Moreover, this study explores the tutor combining synchronous and asynchronous methods to
as a problem-driven innovation, specifically designed to foster flexibility and engagement. Programs integrating
resolve persistent challenges in higher education, including gamified elements and adaptive learning tools emerged
difficulties in maintaining student engagement within as effective strategies for addressing the motivational and
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large class formats, inequitable access to personalized cognitive needs of diverse learners. These developments,
instruction, and insufficient support for diverse learning however, were not without drawbacks. While the expanded
styles. The research addresses two central questions: (i) In use of algorithmic systems and digital platforms accelerated
what ways can AI tutors enhance student engagement, innovation, they also reinforced systemic inequities, raising
accessibility, and learning outcomes within humanities concerns about accessibility and data privacy. In addition,
curricula? and (ii) What specific technical and pedagogical studies show that students often struggle to adapt to the
challenges arise from integrating AI-driven instructional self-directed nature of online tutoring, underscoring the
systems into art history education? By situating this importance of human intervention and guidance. Despite
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investigation within broader scholarly discussions on these challenges, the pandemic marked a turning point in
technological innovation in education, 28,29 this study tutoring practices, fostering a landscape ripe for further
evaluates the tutor as a scalable and adaptive educational technological integration.
model, complementing traditional methods and Concurrent with advancements in GAI, developments
promoting learner autonomy in higher education. Thus, have increasingly enabled users to engage with historical
insights derived from this research aim to provide practical figures and contexts in innovative and interactive ways.
recommendations for addressing current educational Early explorations of the potential in this domain
challenges through AI-driven pedagogical strategies, include systems such as the hypermedia tools developed
contributing to the emerging discourse on intelligent by Khandelwal et al., which enable the manipulation
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tutoring systems within higher education. of historical narratives through curated web-based
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2. Literature review information samples. Latif et al. expanded this concept
with VisKonnect (https://vis.informatik.uni-due.de/
The COVID-19 pandemic in 2020 catalyzed a significant fileadmin/migratedchairt3assets/file/VisKonnect.pdf),
evolution in tutoring practices as institutions were forced a visualization platform connecting historical figures
to transition to remote learning environments. Traditional via event-based knowledge graphs, paired with GPT-3-
in-person tutoring models gave way to virtual platforms generated textual explanations. Such systems reflect a
designed to ensure continuity of academic support amid broader trend of using intelligent systems for educational
widespread lockdowns and school closures. Many studies enrichment, exemplified by projects such as the historical
underscore that despite initial barriers, remote tutoring character chatbots developed by Haller and Rebedea and
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proved capable of maintaining educational standards in key the virtual assistants tailored for museums by Duguleană

Volume 2 Issue 2 (2025) 4 doi: 10.36922/dp.8365