Schlagwort: publication

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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] Digitaler Überblick statt Datenfragmentierung: Ein Studienfortschritts-Dashboard für die TU Graz

Für das fnma-Magazin 02/25 haben wir einen kurzen Beitrag zu „Digitaler Überblick statt Datenfragmentierung: Ein Studienfortschritts-Dashboard für die TU Graz“ geschrieben. Dieser bzw. das gesamte Magazin ist online erhältlich.

Abstract:
Transparenz, Selbststeuerung und digitale Unterstützung sind zentrale Faktoren für Studierbarkeit im digitalen Zeitalter. In diesem Beitrag zeigen wir, wie an der TU Graz gemeinsam mit Studierenden ein datenbasiertes Studienfortschritts-Dashboard entwickelt wird, das Orientierung schafft, Planung erleichtert und neue Impulse für ein nachhaltiges Digital Wellbeing im Student-Life-Cycle setzt.

[fnma Magazin 02/25]
[Beitrag @ ResearchGate]

Zitation: Brünner, B., Leitner, P., Pranter, P.-P. & Ebner, M. (2025) Digitaler Überblick statt Datenfragmentierung: Ein Studienfortschritts-Dashboard für die TU Graz, fnma-Magazin 02/25, S. 16-19, https://www.fnma.at/content/download/3220/21290?version=2

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[publication] Pedagogical Infrastructures of MOOC Design for Employees Training in Leading Organizations #mooc

Our research paper, „Pedagogical Infrastructures of MOOC Design for Employees Training in Leading Organizations,“ has been published:

Abstract:
As the most promising form of education, Massive Open Online Courses (MOOCs) have recently received lots of attention, especially in the leading organizations, requiring closer attention to be paid to the MOOCs’ implementation platforms before their execution. This qualitative study aims to analyze the pedagogical infrastructures in MOOCs designed for employee training in leading organizations. The research population includes documents retrieved by searching authentic Persian and Latin databases. Out of 142 studies (2013–2023), 73 were selected using a criterion sampling method. Data were gathered using the library research method and then analyzed via thematic analysis. The model validation process was presented using expert judgment. The researcher-made questionnaire for content validation of the conceptual model was then sent to the experts and the final model was approved after the modifications were made. Finally, eight sub-categories (i.e., application of learning paradigms and theories, motivational strategies in the educational environment, application of evaluation module strategies and criteria, provision of an interactive platform, infrastructure for developing the content of the course selection, setting the educational and learning goals, determining the learners’ activity in learning, application of the learners engagement types) were obtained.

[draft @ ResearchGate]
[final publication @ publisher’s website]

Reference: Fathi Hafshejani, F., Ebner, M. (2025). Pedagogical Infrastructures of MOOC Design for Employees Training in Leading Organizations. In: Auer, M.E., May, D. (eds) 2024 Yearbook Emerging Technologies in Learning. Learning and Analytics in Intelligent Systems, vol 44. Springer, Cham. https://doi.org/10.1007/978-3-031-80388-8_12

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[publication] Ensuring Quality in AI-Generated Multiple-Choice Questions for Higher Education with the QUEST Framework #AI #tugraz #research

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

Another research paper about the use of AI for education – titled „Ensuring Quality in AI-Generated Multiple-Choice Questions for Higher Education with the QUEST Framework“ – was published.

Abstract:
With the rise of generative AI models, such as large language models (LLMs), in educational settings, there is a growing demand to ensure the quality of AI-generated multiple-choice questions (MCQs) used in higher education. Traditional quiz development methods fall short in addressing the unique challenges posed by AI-generated content, such as consistency, cognitive demand, and question uniqueness. This paper presents the QUEST framework, a structured approach designed specifically to evaluate the quality of LLM-generated MCQs across five dimensions: Quality, Uniqueness, Effort, Structure, and Transparency. Following an iterative research process, AI-generated questions were assessed and refined using QUEST, revealing that the framework effectively improves question clarity, relevance, and educational value. The findings suggest that QUEST is a viable tool for educators to maintain high-quality standards in AI-generated assessments, ensuring these resources meet the pedagogical needs of diverse learners in higher education.

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

Reference: Ebner, M., Brünner, B., Forjan, N., Schön, S. (2025). Ensuring Quality in AI-Generated Multiple-Choice Questions for Higher Education with the QUEST Framework. In: Tomczyk, Ł. (eds) New Media Pedagogy: Research Trends, Methodological Challenges, and Successful Implementations. NMP 2024. Communications in Computer and Information Science, vol 2537. Springer, Cham. https://doi.org/10.1007/978-3-031-95627-0_20

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[publication] A multilingual OER MOOC: A case study on production and usage in a university cooperation #KI #tugraz #research

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

Our publication about our OER-MOOC titled „A multilingual OER MOOC: A case study on production and usage in a university cooperation“ is now published.

Abstract:
This paper investigates the processes, outcomes, and impact of the Unite! OER Courses Project, a cross-university initiative aimed at promoting Open Educational Resources (OER) across nine European higher education institutions. Aligned with UNESCO’s OER recommendations and the Open Science movement, the project sought to enhance accessibility to high-quality educational materials and foster digital competencies among both educators and students. The research adopts a qualitative case study approach, leveraging project reports and feedback from partners. Through the development of a multilingual massive open online course (MOOC) and an international OER course, the project addressed several core goals, including support for Open Science competencies and the advancement of digital literacy across Europe. The MOOC, launched in May 2024, attracted over 1,400 participants, exceeding initial targets and demonstrating the growing demand for accessible OER content. Furthermore, capacity-building workshops aimed at educators provided training on how to incorporate OER. Initial findings indicate that the project successfully developed and disseminated several OER materials, including a multilingual MOOC and additional resources translated into Turkish, Indonesian, and Arabic. The project also fostered capacity-building among partner institutions, enabling broader engagement with OER practices. Participants in the MOOC and related activities have also reported a significant increase in their competencies regarding OER and Open Science. This study underscores the value of cross-institutional collaboration and the potential of OER to enhance radical creativity, educational accessibility, and innovation in higher education.

[article @ ResearchGate]
[article @ Journal’s Homepage]

Reference: Schön, S., Ebner, M., Hohla-Sejkora, K., Keller, E., Rapp, A., Ribeiro, M. H., Segradin, R., & Vicente-Saez, R. (2025). A multilingual OER MOOC: A case study on production and usage in a university cooperation. Journal of Open, Distance, and Digital Education, 2(1), 1-16. https://doi.org/10.25619/y956n017

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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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[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] Early Findings from Pilots in AI-Driven Education: Effects of AI-Generated Courses and Videos on Learning and Teaching #research #tugraz #AI

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

Our chapter in the new book on Emerging Technologies, „Early Findings from Pilots in AI-Driven Education: Effects of AI-Generated Courses and Videos on Learning and Teaching,“ has been published.

Abstract:
This paper presents the (preliminary) findings from three pilot activities conducted at TU Graz over the past 18 months, exploring the use of AI in generating (open) educational resources. The first pilot involved developing a MOOC titled “Societech: Society in the Context of Information Technologies”, which utilized various AI tools to create videos and learning materials, engaging over 500 participants. The second pilot focused on creating multilingual videos for the MOOC “Open Educational Resources in Higher Education”, using AI-generated avatars of course instructors, involving more than 800 participants. The third pilot was a field study conducted in an Austrian secondary school, where 20 students aged 12–15 could choose between videos featuring their teacher, an AI-generated human avatar, or a cartoon character. Preliminary results indicate a clear preference for teacher-led videos, highlighting the significant role of the teacher in the learning process. While AI tools facilitated quicker and more cost-effective production of educational resources, challenges such as the need for quality assurance and handling of (now possible) automatic translations were noted.

[draft @ ResearchGate]
[full version @ publisher’s website]

Reference: Schön, S., Brünner, B., Ebner, M., Edelsbrunner, S., Hohla-Sejkora, K., Uhl, B. (2025). Early Findings from Pilots in AI-Driven Education: Effects of AI-Generated Courses and Videos on Learning and Teaching. In: Auer, M.E., May, D. (eds) 2024 Yearbook Emerging Technologies in Learning. Learning and Analytics in Intelligent Systems, vol 44. Springer, Cham. https://doi.org/10.1007/978-3-031-80388-8_2

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[publication] Empowering Students through Visual Analytics: A Dashboard Redesign for Modern #learninganalytics #tugraz

Our paper, „Empowering Students through Visual Analytics: A Dashboard Redesign for Modern,“ which was awarded at this year’s EDMedia conference, is now available online.

Abstract:
Graz University of Technology originally launched a study progress dashboard in 2020 to help students monitor their academic progress and better understand their degree structures. In response to systematic changes in the university’s academic data modeling and the phasing out of legacy curricula between 2022 and 2024, the dashboard underwent a complete technical and conceptual overhaul. This paper presents the redesigned tool, which now features a modular, service-oriented architecture, real-time integration of current curricula, and enriched analytics combining student records with historical performance data. Supporting all Bachelor’s and Master’s programs, the updated dashboard continues to prioritize usability, transparency, and student autonomy. Drawing on student feedback and us-age data collected since the dashboard’s introduction, we analyze patterns of adoption and engagement, highlight lessons learned, and offer practical guidance for institutions aiming to implement adaptable, student-centered learning analytics systems.

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

Reference: Leitner, P., Pranter, P.P., Brünner, B. & Ebner, M. (2025). Empowering Students through Visual Analytics: A Dashboard Redesign for Modern Curricula. In T. Bastiaens (Ed.), Proceedings of EdMedia + Innovate Learning (pp. 599-608). Barcelona, Spain: Association for the Advancement of Computing in Education (AACE). Retrieved May 28, 2025 from https://www.learntechlib.org/primary/p/226201/.

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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/.