EG 2025 - Education Papers

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Browsing EG 2025 - Education Papers by Subject "Computing methodologies → Artificial intelligence"

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    Computer Graphics Instructors' Intentions for Using Generative AI for Teaching
    (The Eurographics Association, 2025) Magana, Alejandra J.; Felkel, Petr; Žára, Jiří; Kuffner dos Anjos, Rafael; Rodriguez Echavarria, Karina
    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.
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    Harnessing Artificial Intelligence to Expedite Content Creation for the Development of eXtended Reality Experiences
    (The Eurographics Association, 2025) Freitas, André; Borges, João; Marques, Bernardo; Dias, Paulo; Santos, Beatriz Sousa; Kuffner dos Anjos, Rafael; Rodriguez Echavarria, Karina
    Despite eXtended Reality (XR) many benefits and demonstrated potential, the process of creating content specifically designed for distinct applications remains time-intensive and resource-demanding, hindering broader adoption. This study presents a student-driven project that investigates the role of Artificial Intelligence (AI) in streamlining the content creation process of 3D models. The proposed solution enables a user, equipped with an XR headset to use gesture recognition and perform a query via a text prompt, or as an alternative, to use voice recognition. Afterward, a request will be made to an API, which will generate the 3D model. Finally, the model will be added to a local library and become accessible in the XR environment, allowing users to manipulate, position, and other features. Initial findings highlight both opportunities and challenges, confirming it is already possible to integrate AI into a game engine with interesting results, while also showcasing that additional work is still necessary for obtaining more detailed and complex 3D models moving forward.