Schlagwort: conference

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[publication] Forecasting Education Metrics through Joint Futures Betting – A Study with Austria’s Emerging Scholars #tugraz #research

Our publication about „Forecasting Education Metrics through Joint Futures Betting – A Study with Austria’s Emerging Scholars“ got published in the conference proceedings of the SITE 2026 conference.

Abstract:
Education systems increasingly rely on indicators to guide policy and practice. However, the underlying assumptions of these indicators are rarely discussed collectively. This short article reports on a future-oriented, game-based „future bet“ conducted as part of the „Educational Innovation Needs Educational Research“ (B3) initiative at the eduNexus.at retreat in Austria. Doctoral students, supervisors, and experts placed tokens on measurable hypotheses. We focus on five hypotheses from these funded doctoral programs closely linked to technology policy and practice: teacher training in computer science and digital education; open education resource certificate holders; the school dropout rate; and the number of schools with a STEM quality label.

[draft @ ResearchGate]

Reference: Brünner, B., Geier, G., Schön, S. & Ebner, M. (2026). Forecasting Education Metrics through Joint Futures Betting – A Study with Austria’s Emerging Scholars. In Proceedings of Society for Information Technology & Teacher Education International Conference (pp. 1514-1519). Philadelphia, PA: Association for the Advancement of Computing in Education (AACE). Published at https://www.learntechlib.org/primary/p/2129172/

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[presentation] Developing and Testing a Peer-Review Process for Content Quality Assurance in MOOCs: A Case Study on an E-Assessment Course #tugraz #research

At this year’s ICL conference in Budapest, one of our presentations was about „Developing and Testing a Peer-Review Process for Content Quality Assurance in MOOCs: A Case Study on an E-Assessment Course„

This contribution presents the development and testing of a peer-review process for content quality assurance in MOOCs, implemented in the course “E-Assessment – auf Kurs gebracht”. The process was evaluated regarding complexity, duration, collaboration with external reviewers, and learners’ perception. Results show that the procedure can be smoothly integrated into MOOC development. Reviewers contributed beyond expectations by providing materials, didactic advice, and legal-ethical reflections. Learners rated the videos (very) positively (92.7% positive ratings, 100 participants, n=812 answers), especially for structure and coherence. Slightly lower ratings for ‚visual appearance‘ and ‚use of supportive linguistic elements‘ can be explained by the course’s retro video de-sign and the viewers’ understanding of how linguistic devices can be effectively used in educational videos. The study confirms peer review as a feasible and effective quality as-surance approach that supports both collaboration and content improvement.

Find the slides in TU Graz repository.

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[publication] aicast: Combining AI-Generated and Instructor-Defined Content in Educational Podcasts #research #tugraz

At this year’s ED-Media conference, we introduced a new AI-based concept for educational podcasts: „aicast: Combining AI-Generated and Instructor-Defined Content in Educational Podcasts„.

Abstract:
Generative AI is transforming educational content. In this poster, we present aicast.fyi, an open-source platform for producing personalized educational podcasts that combine AI-generated and instructor-defined content. Each track contains dynamic and fixed segments. Instructors define guiding questions during track design, ensuring alignment with learning objectives. This hybrid approach addresses concerns about maintaining instructional integrity with automation and personalization. The poster provides an architectural overview and demonstrates how the system integrates text generation and voice synthesis to produce audio-based learning experiences. Instructional designers must play an active role in shaping AI-assisted educational tools. This poster invites educators, designers, and researchers to engage with aicast and collaborate on developing high-quality, responsible, and learner-centered audio content. By allowing learners to control content sequences and personalize segments based on their own inputs, aicast.fyi also supports self-regulated learning (SRL), empowering users to take ownership of their educational journey.

[draft @ ResearchGate]
[full article @ conference website]

Reference: Brünner, B., Leitner, P., Geier, G. & Ebner, M. (2025). aicast: Combining AI-Generated and Instructor-Defined Content in Educational Podcasts. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 148-152). Barcelona, Spain: Association for the Advancement of Computing in Education (AACE). Retrieved June 4, 2025 from https://www.learntechlib.org/primary/p/226139/

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[presentation] Synthetic Educators: Analyzing AI-Driven Avatars in Digital Learning Environments #HCII25

Our research about AI-Driven Avatars was presented at 27th International Conference on Human-Computer Interaction, Gothenburg, Sweden.

Struger, P., Brünner, B., & Ebner, M. (2025, Juni 23). Presentation: Synthetic Educators: Analyzing AI-Driven Avatars in Digital Learning Environments. Graz University of Technology. https://doi.org/10.3217/bngt5-p2053

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[publication] Understanding the Core of LLMs as genAI -CollectiveGPT and Human Intelligence #tugraz #workshop

At this year’s ED-Media conference, we also did a workshop on „Understanding the Core of LLMs as genAI -CollectiveGPT and Human Intelligence„. Find a short published summary about it.

Abstract:
This workshop provides an engaging and interactive exploration of Large Language Models (LLMs), with a focus on how they operate at a foundational level. Using CollectiveGPT, an educational chatbot developed by the Ed-Tech Research Community Graz, participants gained firsthand experience understanding the principles behind generative AI (genAI) systems such as ChatGPT. Designed for educators of all disciplines, the workshop demystifies key LLM concepts such as probability-based word prediction, contextual understanding, and the role of training data. Attendees generated texts and compare their results with real-time outputs from ChatGPT, highlighting the differences between human reasoning and AI prediction. Key topics include prompting techniques, context framing, training bias, misinformation, and ethical considerations in AI use. Participants explored system prompt injection techniques and developed advanced prompting skills to optimize responses from AI systems. This workshop empowered educators with the knowledge to critically evaluate and responsibly use AI tools in their teaching. By fostering AI literacy, attendees got clear understanding of how LLMs work and how they can be leveraged to enhance learning experiences across diverse educational settings.

[publication @ conference website]
[draft @ ResearchGate]

Reference: Brünner, B. & Ebner, M. (2025). Understanding the Core of LLMs as genAI – CollectiveGPT and Human Intelligence. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 153-154). Barcelona, Spain: Association for the Advancement of Computing in Education (AACE). Retrieved June 14, 2025 from https://www.learntechlib.org/primary/p/226329/.

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[publication] Rapid Multilingual Video Production utilizing Artificial Intelligence #AI

At this year’s EDMedia conference, we published a publication titled „Rapid Multilingual Video Production utilizing Artificial Intelligence„.

Abstract:
This study presents the Rapid Multilingual Video Production (RMVPro) framework, an optimized process for creating high-quality multilingual educational videos using artificial intelligence (AI). The framework involves three stages: planning, translation, and production, with each stage involving iterative feedback loops with experts and native speakers to ensure linguistic and cultural accuracy of the translations. The framework for the Multilingual Video Sprint was tested during an international conference and the produced multilingual videos showing an AI human avatar were evaluated in a MOOC with feedback from 128 students. Results showed that AI could be utilized to accelerate video production while maintaining the clarity and comprehensibility of educational content. However, feedback indicated mixed perceptions of AI-generated human avatars, with some students preferring human facilitators for reasons of authenticity. The use of AI avatars in multilingual educational videos must be implemented carefully, but the RMVPro framework ensures high quality while utilizing the potential of AI to rapidly produce multilingual educational videos.

[draft @ researchgate]
[full version @ conference website]

Reference: Brünner, B. & Ebner, M. (2025). Rapid Multilingual Video Production utilizing Artificial Intelligence. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 1223-1230). Barcelona, Spain: Association for the Advancement of Computing in Education (AACE). Retrieved May 28, 2025 from https://www.learntechlib.org/primary/p/226280/.