Kategorie: Veranstaltungen

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[workshop] Mitdenken in Echtzeit: KI-gestützte ARS in der Hochschullehre #ARS #tugraz

Im Rahmen des KI-Forums in Hannover hat Benedikt einen Workshop zu „Mitdenken in Echtzeit: KI-gestützte ARS in der Hochschullehre“ gehalten:

Welche Chancen bietet Künstliche Intelligenz, um Hochschullehre interaktiver zu gestalten und individuelles Feedback zu fördern? In diesem Workshop erleben die Teilnehmenden den Einsatz von KI-basierten Audience Response Systemen (ARS) am Beispiel des Open-Source-Tools echoQuiz.eu. Sie erfahren, wie explorative Frageformate die aktive Teilnahme in synchronen Lehrveranstaltungen steigern und wie Lehrende durch KI in Echtzeit didaktisch unterstützt werden können. In diesem Workshop werden gemeinsam Fragen entwickelt, praktisch erprobt und didaktisch reflektiert. 

Seine Folien sind hier zugänglich:

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[publication] Empowering Self-Regulated Learning Through Technology and the Teacher’s Role – A Systematic Literature Review #research

This is an impactful contributions, methodological rigor, and exceptional novelty in the research field of AI in education and Self-Regulated Learning.

Our research work titled „Empowering Self-Regulated Learning Through Technology and the Teacher’s Role – A Systematic Literature Review“ is published.

Abstract:
Self-regulated learning (SRL) has been demonstrated in numerous scientific studies as an effective alternative to traditional teaching methods, fostering individual learning processes. The added value of educational technology in supporting SRL has also been widely researched and largely validated. Within this context, the teacher plays a pivotal role. However, much of the existing research has been conducted at universities , while the secondary education level has received comparatively less attention. To gain an overview of the teacher’s influence on students‘ SRL processes, a PRISMA based systematic literature review was conducted. From an initial pool of 553 documents, 27 relevant studies were identified and analyzed. The selected studies were examined to collect data addressing the research questions, focusing on identifying effective teaching methods and essential teacher competencies for fostering SRL in technology-enhanced classrooms. Furthermore, the analysis highlights the evolving role of teachers and underscores the need for additional training to support these changes.

[full article @ publisher’s website]
[draft @ researchgate]

Reference: Geier, G., Ebner, M., Burgsteiner, H. (2025). Empowering Self-Regulated Learning Through Technology and the Teacher’s Role – A Systematic Literature Review. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2025. Lecture Notes in Computer Science, vol 15807. Springer, Cham. https://doi.org/10.1007/978-3-031-93567-1_5

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[publication] Synthetic Educators: Analyzing AI-Driven Avatars in Digital Learning Environments #AIinEducation #tugraz

This is an impactful contributions, methodological rigor, and exceptional novelty in the research field of AI in education.

Our publication „Synthetic Educators: Analyzing AI-Driven Avatars in Digital Learning Environments“ at this year’s HCII conference is published.

Abstract:
Videos can be used in a variety of ways in learning environments today. With advances in generative AI technologies, tools such as HeyGen and ElevenLabs make it easy to create synthetic teachers, promising efficiency and accessibility. This study investigates the impact of AI-generated teaching video avatars on learners‘ emotional responses. A mixed-method approach was adopted, in which 55 participants were shown AI-generated videos and videos with real instructors. Emotional engagement was measured using FaceReader Online, along with quiz questions and follow-up interviews to gauge knowledge retention and perceptions of this educational technology. Results indicate that AI avatars effectively convey content and weakly elicit better recall rates and positive emotional responses comparable to those of real instructors. However, concerns were raised about emotional authenticity and engagement, highlighting the need for improved avatar design. The study concludes with a discussion of the potential and limitations of AI avatars and argues for their thoughtful integration to improve educational equity and learning outcomes.

[full article @ publisher’s homepage]
[draft @ researchgate]

Reference: Struger, P., Brünner, B., Ebner, M. (2025). Synthetic Educators: Analyzing AI-Driven Avatars in Digital Learning Environments. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2025. Lecture Notes in Computer Science, vol 15807. Springer, Cham. https://doi.org/10.1007/978-3-031-93567-1_13

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[publication] InfoFit and Beyond: AI Chatbots as EdTech Tools for Self-Regulated Learning in MOOCs #AIinEducation #research

This is an impactful contributions, methodological rigor, and exceptional novelty in the research field of AI in education.

Our publication titled „InfoFit and Beyond: AI Chatbots as EdTech Tools for Self-Regulated Learning in MOOCs“ at this year’s HCII conference is available.

Abstract:
Massive Open Online Courses (MOOCs) have become essential for the democratization of education by providing accessible learning opportunities to broad audiences. However, their asynchronous and open structure is challenging for learning, especially in terms of maintaining engagement, and self-regulated learning (SRL) is necessary. This study investigates the integration of a retrieval-augmented-generation (RAG) chatbot into a MOOC and uses generative AI (genAI) to enhance learn-ers‘ SRL processes. The chatbot is based on Zimmermann’s SRL framework and is prepared for the MOOC content, basics of computer science. It is designed to support learners in the forethought, performance, and self-reflection phases by providing concise, context-specific responses. A mixed-method evaluation with 79 participants revealed high levels of satisfaction , with over 98% of respondents recommending the chatbot for future courses. The chatbot proved effective in supporting tasks such as summarization and concept clarification; however, its role in maintaining motivation emerged as a key area for further investigation. These findings underscore the transformative potential of AI chatbots in asynchronous learning environments, while also highlighting the importance of incorporating multimodal and motivational features to maximize educational technology (EdTech) impact.

[full article @ publisher’s homepage]
[draft @ ResearchGate]

Reference: Brünner, B., Ebner, M. (2025). InfoFit and Beyond: AI Chatbots as EdTech Tools for Self-Regulated Learning in MOOCs. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2025. Lecture Notes in Computer Science, vol 15807. Springer, Cham. https://doi.org/10.1007/978-3-031-93567-1_4

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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] Implementing multilingual MOOCs in European University Alliances with the help of AI usage, LTI and open licenses: Technical & organizational challenges #tugraz #emoocs2025

We also presented one paper within the Experience Track of the EMOOCs 2025 conference in Paris. This time the presentation was about „Implementing multilingual MOOCs in European University Alliances with the help of AI usage, LTI and open licenses: Technical & organizational challenges (Presentation)„. Our slides are, of course, available online.

[Link to the slides]

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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/.