Computer Graphics Instructors' Intentions for Using Generative AI for Teaching
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00383425" target="_blank" >RIV/68407700:21230/25:00383425 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.2312/eged.20251006" target="_blank" >https://doi.org/10.2312/eged.20251006</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2312/eged.20251006" target="_blank" >10.2312/eged.20251006</a>
Alternative languages
Result language
angličtina
Original language name
Computer Graphics Instructors' Intentions for Using Generative AI for Teaching
Original language description
Background: Generative AI has significant potential to support learning processes, such as generating personalized content matching individual student needs. It also has the potential to support teaching processes by assisting instructors in generating content, assessing students, or supporting practice. This study investigates how computer graphics instructors have used generative AI or are planning to use generative AI to support their teaching. We implemented an anonymous online survey based on the Unified Theory of Acceptance and Use of Technology (UTAUT) methodology and distributed it among Eurographics members. The research questions were: (1) What are computer graphics instructors' ways of integrating generative AI for teaching and learning purposes? (2) What are the influencing factors computer graphics instructors have considered for integrating generative AI for teaching and learning purposes? Results: Between October 2024 and January 2025, we received 12 responses. Findings suggest that while some instructors have integrated generative AI into some aspects of their teaching, others have not and are hesitant to adopt them in the future, particularly as related to generating content for creating assignments such as lecture notes, summaries, teaching examples, etc., and supporting their assessment processes such as providing feedback, evaluating assignments, or grading exams. However, instructors were more open to using generative AI to support their teaching practices, particularly as related to pedagogy, such as providing students with interactive practice problems and supporting their creative content generation. Conclusion: Findings from the study identified the level of acceptance among computer graphics instructors, primarily full professors, and their experiences and intentions for using generative AI. To get a better understanding of the adoption of generative AI in the field of computer graphics education, we would like to invite the community to share their experiences and future intentions via the survey, which will remain open for additional input.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Eurographics 2025 - Education Papers
ISBN
978-3-03868-266-0
ISSN
1017-4656
e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
Eurographics Association
Place of publication
Aire-la-Ville
Event location
Londýn
Event date
May 12, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001511711300001