Schlagwort: publication

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[publication] Digital Equipment Evolution and IT Activity of TU Graz study beginners (2011-2025): Challenges of Tablet and AI Dominance for University Digital-Sovereignty Initiatives #tugraz #welcomedays

Our most traditional research publication about the outcomes of the welcome days‘ survey is now published, titled „Digital Equipment Evolution and IT Activity of TU Graz study beginners (2011-2025): Challenges of Tablet and AI Dominance for University Digital-Sovereignty Initiatives„

Abstract:
Over the last thirteen years, more than 14 000 freshmen at the Graz University of Technology (TU Graz) have taken part in the annual „Welcome Days“ surveys. This study analyses the responses collected between 2011 and 2025 to chart the shifting digital profile of incoming students. The results highlight evolving patterns in hardware ownership, social-media activity, communication preferences, digital recreation, and the utilization of online information sources. Notably, the data reveal a steady increase in the adoption of artificial-intelligence applications and tablet devices, alongside a decline in the use of Wikipedia and open-source software. These trends pose significant challenges for TU Graz, prompting the need for initiatives that strengthen digital sovereignty and promote on-premise hosting of open-source solutions.

[publication @ conference’s homepage]
[preview @ ResearchGate]

Reference: Nagler, W., Mayr, B., Ebner, M., Schön, S. & Bruenner, B. (2026). Digital Equipment Evolution and IT Activity of TU Graz study beginners (2011-2025): Challenges of Tablet and AI Dominance for University Digital-Sovereignty Initiatives. In Proceedings of EdMedia 2026 Edinburgh (pp. 119-129). Waynesville, NC: Association for the Advancement of Computing in Education (AACE). Retrieved June 15, 2026 from https://www.learntechlib.org/primary/p/2129631/.

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[publication] Whitepaper on Evaluating GenAI Innovation in Higher Education #tugraz #research #AIinEducation

Our publication, „Whitepaper on Evaluating GenAI Innovation in Higher Education,“ is included in the proceedings of the EDMedia 2026 conference.

Abstract:
Generative artificial intelligence (genAI) is increasingly shaping higher education by enabling new forms of content creation, assessment, learner support, personalization, and synthetic media. However, its value cannot be determined solely by technical performance, novelty, or efficiency. This paper presents an evaluation framework for quality genAI applications in higher education. This paper presents a practice-derived framework developed through a cross-case synthesis of nine diverse GenAI implementations at Graz University of Technology. Analyzing projects ranging from AI-generated content to RAG-based chatbots, we identified recurring decision points and risk patterns to formulate a five-phase, non-linear evaluation model. The framework guides institutions through specifying context, assessing feasibility, selecting implementation strategies, conducting multi-layered pilots, and performing data-informed analysis. A defining feature is the integration of explicit „Sustain-or-Discontinue“ decision gates at each stage, ensuring resources are committed only to viable applications while providing a structured pathway to terminate initiatives that fail to meet pedagogical or ethical standards. We argue that the core institutional capability lies not in rapid adoption, but in the discipline to evaluate responsibly, balancing experimentation with the rigor to govern and discontinue when necessary.

[publication @ conference’s homepage]
[preview @ ResearchGate]

Reference: Schön, S., Brünner, B., Ebner, M. & Leitner, P. (2026). Whitepaper on Evaluating GenAI Innovation in Higher Education. In Proceedings of EdMedia 2026 Edinburgh (pp. 697-703). Waynesville, NC: Association for the Advancement of Computing in Education (AACE). Retrieved June 15, 2026 from https://www.learntechlib.org/primary/p/2129693/.

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

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[publication] The OER Paradox in Ukraine: Legal Comfort and Its Impact on Open Educational Practices #OER #research

Our publication about „The OER Paradox in Ukraine: Legal Comfort and Its Impact on Open Educational Practices“ is published in the conference proceedings of this year’s EDMedia conference.

Abstract:
This study analyses the impact of the new Law of Ukraine „On Copyright and Related Rights“ (2811-IX) on the use of educational materials in the context of digital transformation and military crisis. Using the benchmarking methodology „15 cases in 15 countries“ and qualitative interviews with teachers, the work compares Ukrainian norms with the practice of European countries. The results show that broad educational exceptions (in particular, Articles 22 and 24) create a situation of „legal comfort“ for the academic community, allowing the legal use of protected content in closed digital environments. However, this gives rise to the „OER paradox“: the absence of legal barriers to the use of proprietary resources reduces the motivation to create full-fledged open educational resources under open licenses. The paper highlights the need for institutional incentives to overcome dependence on closed content and integrate Ukraine into the global open education movement.

[publication @ conference’s homepage]
[preview @ ResearchGate]

Reference: Andriichenko, Y., Ebner, M., Schön, S. & Brünner, B. (2026). The OER Paradox in Ukraine: Legal Comfort and Its Impact on Open Educational Practices. In Proceedings of EdMedia 2026 Edinburgh (pp. 1589-1599). Waynesville, NC: Association for the Advancement of Computing in Education (AACE). Retrieved June 15, 2026 from https://www.learntechlib.org/primary/p/2129797/.

This is an impactful contributions, methodological rigor, and exceptional novelty in the research field of Open Educational Resources (OER).

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[publication] Implementing a Technical Commission in a European University Alliance: Role and Processes in Unite! #zfhe

Our article about „Implementing a Technical Commission in a European University Alliance: Role and Processes in Unite!“ has been published within the issue „European University Alliances in Action“ of the Journal of Higher Education Development (ZFHE)

Abstract:
European University Alliances seek to integrate teaching, research, and administration across borders by aligning digital and internationalisation strategies. This paper first outlines the alliances’ common objectives and governance models. It then highlights the pivotal role of a federated IT infrastructure—providing identity management or interoperable learning systems—and explains why ongoing technical decisions are necessary to meet evolving regulations and the need for scaling and interoperability, as described, for example, in the Higher Education Interoperability Framework (HEIF). Using the Technical Commission (TC) of Unite! as a case study, the article maps its mandate, composition, and end‑to‑end workflow. The final sections reflect on lessons learned, noting success factors and future directions (e.g. the implementation of the TC within the core organisation of the alliance) to sustain transnational collaboration.

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

Cite as: Ebner, M., Gasplmayr, K., Koschutnig-Ebner, M., Schön, S., Alcober, J., Bertonasco, R., Diar, J., Francisco, A., Hoppe, C., Martikainen, J., Krysiak, J., Petersson, J. & Szymanka-Kwiencien, A. (2026). Implementing a Technical Commission in a European University Alliance: Role and Processes in Unite!. Zeitschrift für Hochschulentwicklung (Journal for Higher Education Development), 21(2), 111–130. [https://doi.org/10.21240/zfhe/21-2/06]

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[publication] Generative AI Chatbots in Secondary Mathematics Education: Development and Implementation of a Dynamic Large Language Model-Based Learning Assistant for Quadrilaterals #tugraz

Our contribution titled „Generative AI Chatbots in Secondary Mathematics Education: Development and Implementation of a Dynamic Large Language Model-Based Learning Assistant for Quadrilaterals“ is now published.

Abstract:
As artificial intelligence becomes more and more a part of education, the challenge is not about having access to generative tools, but about connecting them with the goals of the curriculum and the needs of the classroom. This chapter presents the design and evaluation of a large language model–based chatbot developed specifically for teaching quadrilaterals in lower secondary mathematics. The chatbot integrates fine-tuning with retrieval-augmented generation (RAG), combining accurate, curriculum-aligned content with flexible, conversational support. The chatbot allows learners to ask conceptual questions, solve problems step by step, receive guided hints, and generate flashcards or exercises of varying difficulty. A hybrid routing mechanism selects the most appropriate response strategy based on user intent. Evaluations using both isolated prompts and multi-turn dialogues demonstrate that the hybrid system significantly outperforms standard LLM baselines in terms of accuracy, consistency, and pedagogical suitability. A classroom trial with 20 students confirmed the tool’s usability and effectiveness; students reported high satisfaction and meaningful engagement. This study demonstrates that, with careful content and architectural structuring, generative AI can enhance student learning while supporting differentiated instruction. Future directions include scaling the approach to other topics and incorporating multimodal capabilities.

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

Reference: Mallweger, M., Brünner, B., Ebner, M. (2026). Generative AI Chatbots in Secondary Mathematics Education: Development and Implementation of a Dynamic Large Language Model-Based Learning Assistant for Quadrilaterals. In: Auer, M.E., Nikou, S.A. (eds) GenAI in Novel Educational Applications. Studies in Computational Intelligence, vol 1260. Springer, Cham. https://doi.org/10.1007/978-3-032-16153-6_7

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

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[publication] Generative AI literacy across education and business: competencies, obstacles, and benefits—a systematic literature review #research

Our article, which we really worked on for a long time, is published right now with the title „Generative AI literacy across education and business: competencies, obstacles, and benefits—a systematic literature review„.

Abstract:
This systematic literature review analyses AI literacy, focusing on the required competencies for, the obstacles arising from, and the benefits of, Generative AI (GenAI) in the fields of education and business. The analysis uses the PRISMA 2020 methodology with data from the SCOPUS and ERIC databases. A total of 538 articles were identified; of these, 206 were included after the full-text screening phase. Of those 206, only 33% (education) and 29% (business) were based on empirical research, highlighting the predominantly conceptual state of research. Using a combination of inductive coding and GenAI (ChatGPT-4o) validation, we identified AI literacy as a multidimensional concept comprising technical competencies (e.g. algorithmic literacy and prompt engineering), personal and interpersonal competencies (e.g. adaptability and collaboration), and ethical and critical thinking competencies (e.g. awareness of bias and ethical reflection). While educational literature emphasised pedagogical applications such as adaptive feedback and inclusive curriculum design, business research focused on process automation and data-driven decision-making. Top three identified obstacles included hallucinations, ethics and plagiarism, which manifested differently in contexts such as student assessment and personnel selection. Addressing these challenges will require targeted training modules, ethical governance structures, and institutional support in the form of faculty development programmes or workplace reskilling initiatives. Top three identified benefits of GenAI literacy training are described as critical thinking, personalized teaching and learning and personalized feedback across sectors.

[full article @ publisher’s homepage (open access)]
[full article @ resarchgate]

Reference: Reicho, M., Otrel-Cass, K., Ebner, M. et al. “Generative AI literacy across education and business: competencies, obstacles, and benefits—a systematic literature review”. Int J Educ Technol High Educ 23, 23 (2026). https://doi.org/10.1186/s41239-026-00596-8

This is an impactful contributions, methodological rigor, and exceptional novelty in the research field of AI in education. This is a comprehensive literature review on the topic of AI in education

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[publication] Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach #ARS #AI #tugraz

Our publication about „Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach“ is now online available.

Abstract:
This paper introduces echoQuiz, an open-source, AI-supported Audience Response System (ARS) designed for synchronous university (online) teaching with open-ended questions. The system follows a two-phase interaction model: In the quiz phase, students/learners submit their responses and then rate their peers’ responses. In the echo phase, the instructor highlights one response for group reflection, with all responses remaining anonymous. To ease the interpretation of open responses, the lecturer can be assisted by an AI system during live sessions. Developed with an Educational Design Research (EDR) approach, echoQuiz was piloted in synchronous university courses with a total of 62 participants. Survey results show high motivation and moderate perceived learning gains. The findings suggest that free-text interaction, supported by AI, can enhance engagement and adaptability in digital classrooms.

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

Reference: Brünner, B., Ebner, M. (2026). Enhancing Synchronous Collaborative Learning with AI-Supported Audience Response Systems: The EchoQuiz Approach. In: Auer, M.E., Toth, P. (eds) Innovation via Collaborative Learning in Engineering Education. ICL 2025. Lecture Notes in Networks and Systems, vol 1847. Springer, Cham. https://doi.org/10.1007/978-3-032-18885-4_2

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

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

Our publication about „Developing and Testing a Peer-Review Process for Content Quality Assurance in MOOCs: A Case Study on an E-Assessment Course“ got published now.

Abstract:
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 design 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 assurance approach that supports both collaboration and content improvement.

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

Reference: Loitzenbauer, J., Ebner, M., Schön, S., Brünner, B. (2026). Developing and Testing a Peer-Review Process for Content Quality Assurance in MOOCs: A Case Study on an E-Assessment Course. In: Auer, M.E., Toth, P. (eds) Innovation via Collaborative Learning in Engineering Education. ICL 2025. Lecture Notes in Networks and Systems, vol 1847. Springer, Cham. https://doi.org/10.1007/978-3-032-18885-4_26

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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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[publiation] AI-Powered Chatbots for Education Using RAGs #tugraz

Our publication about „AI-Powered Chatbots for Education Using RAGs“ got published right now.

Abstract:
This study examines the use of Retrieval-Augmented Generation (RAG) in AI-powered educational chatbots, focusing on embedding efficiency, large language model (LLM) performance, and context integrity. Implemented within the MOOC Informatik-Fit at TU Graz, the system supports scalable, curriculum-aligned self-paced learning. Three embedding models were evaluated, with text-embedding-ada-002 offering the best balance between semantic quality and cost-efficiency. Subsequently, three LLMs—GPT-3.5 Turbo, GPT-4o, and GPT-4o mini—were compared, revealing GPT-4o mini as the most cost-effective option while maintaining high accuracy and contextual coherence. Ethical robustness was assessed using 30 adversarial prompts, demonstrating strong resistance to jailbreaking in both GPT-4o and GPT-4o mini, supporting their suitability for secure and pedagogically reliable MOOC applications.
The paper also presents a replicable framework for the implementation of RAG-based systems, with the objective of promoting personalized, ethical, and accessible digital education on a large scale.

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

Reference: Brünner, B., Deutschmann, F., Etzelstorfer, S., Lechner, A., Schön, S. & Ebner, M. (2029) “AI-Powered Chatbots for Education using RAGs: A Study on Embedding Efficiency, LLM Performance, and Context Integrity”. In: Transforming Education with Singularity Technologies: Lifelong Learning from Childhood to Adulthood (1st ed.). Uğur, S. (Ed.) Chapman and Hall/CRC. Chapter 9. 21 pages https://doi.org/10.1201/9781003584339