Computer Graphics Instructors' Intentions for Using Generative AI for Teaching

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Computer Graphics Instructors' Intentions for Using Generative AI for Teaching

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Computer Graphics Instructors' Intentions for Using Generative AI for Teaching

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Eurographics 2025 - Education Papers

ISBN

978-3-03868-266-0

ISSN

1017-4656

e-ISSN

—

Počet stran výsledku

8

Strana od-do

1-8

Název nakladatele

Eurographics Association

Místo vydání

Aire-la-Ville

Místo konání akce

Londýn

Datum konání akce

12. 5. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001511711300001