Schlagwort: research

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[CfP] AI and Data-driven Technologies for Personalized, Inclusive, and Equitable Learning #hcii27 #conference

I will organize a parallel session in the context of the 14th International Conference on Learning and Collaboration Technologies (LCT 2027), an Affiliated Conference of HCI International 2027 (HCII 2027). This session is scheduled to take place between 28 – 30 July as a ‚hybrid‘ event.

My parallel session proposal is entitled:
„AI and Data-driven Technologies for Personalized, Inclusive, and Equitable Learning“

Session description:
The session “AI and Data-driven Technologies for Personalized, Inclusive, and Equitable Learning” explores emerging trends, technologies, and pedagogical innovations shaping education in a rapidly evolving digital landscape. It examines how artificial intelligence, self regulated learning environments, open educational resources (OER), and data-driven approaches are redefining teaching and learning. Experts should share research and case studies highlighting new models for personalized, inclusive, and sustainable digital education. Key topics include the integration of AI in education, the impact of learning analytics on student success, and strategies for fostering digital literacy and equity across diverse learning contexts. The session will also discuss the challenges of ethics, privacy, and accessibility, emphasizing the need for open, collaborative frameworks and global best practices. Participants will gain insights into future-ready skills and the critical role of innovation in shaping equitable, high-quality learning experiences for the next generation.

Important deadlines:
– 30 November 2026: Submit your abstract (800 words) for the review process.
– 10 December 2026: Notification of review outcome
– 29 January 2027: Submit the camera-ready version
– 12 February 2027: Register for the conference

If you are interested in it, just send me a short message, martin.ebner [at] tugraz.at. I will get back to you with a personal invitation.

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[publication] Prompting.School: A Design-Based Research Approach to Teaching AI Literacy Through Guided Prompt Engineering Practice #AIinEducation #tugraz #AI

Our publication (presented at least year ICL conference) about „Prompting.School: A Design-Based Research Approach to Teaching AI Literacy Through Guided Prompt Engineering Practice“ is published now.

Abstract:
We introduce prompting.school, a browser-based learning platform that teaches foundational prompt engineering skills to support AI literacy. Developed using a design-based research approach, the platform was evaluated through four iterative cycles with pre-service and in-service teachers, as well as vocational learners. Aligned with the UNESCO AI Competency Framework and DigComp 2.3 AT, it combines scaffolded lessons, interactive feedback, and real-time AI responses to promote self-regulated learning. Findings show that structured, hands-on prompting practice enhances learners’ understanding, with notable differences in engagement and performance across educational contexts.

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

Reference: Brünner, B., Jahic, I., Ebner, M. (2026). Prompting.School: A Design-Based Research Approach to Teaching AI Literacy Through Guided Prompt Engineering Practice. In: Auer, M.E., Toth, P. (eds) Innovation via Collaborative Learning in Engineering Education. ICL 2025. Lecture Notes in Networks and Systems, vol 1848. Springer, Cham. [https://doi.org/10.1007/978-3-032-20381-6_62]

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

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[publication] Code Meets Career: Employer Interpretations of Coding Bootcamp Graduates in Austria and Germany #edmedia

We are happy about another publication at this year’s edmedia conference titled „Code Meets Career: Employer Interpretations of Coding Bootcamp Graduates in Austria and Germany„

Abstract:
Coding bootcamps have expanded rapidly in response to skill shortages in the IT sector and as alternative pathways into the field. However, little is known about how these pathways are perceived and valued within organizations, especially in Austria and Germany. This study therefore examines how companies in Austria and Germany perceive, evaluate, and integrate coding bootcamp graduates. Drawing on a qualitative content analysis of five semi-structured interviews with decision-makers in software development, IT consulting, and human resources, the study focuses on socially situated employer perspectives on skills, potential, and legitimacy. The findings reveal a nuanced picture: while graduates are generally valued for their motivation, adaptability, learning orientation, teamwork, and practical engagement, concerns persist regarding theoretical depth, project experience, and formal recognition. In the case of refugee participants, language proficiency emerged as an additional challenge shaping labor market integration. The findings further suggest that workplace integration depends less on the bootcamp model itself than on organizational conditions such as onboarding structures, mentoring opportunities, and continued professional development. Overall, the study provides exploratory insights into how coding bootcamp qualifications are interpreted and evaluated by employers and contributes to alternative educational pathways into software development careers.

[article @ conference homepage]
[draft @ ResearchGate]

Reference: Wolf, D., Ebner, M. & Brünner, B. (2026). Code Meets Career: Employer Interpretations of Coding Bootcamp Graduates in Austria and Germany. In Proceedings of EdMedia 2026 Edinburgh (pp. 1170-1184). Edinburgh, Scotland: Association for the Advancement of Computing in Education (AACE). Retrieved July 1, 2026 from https://www.learntechlib.org/primary/p/2129750/.

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[publication] How Embodiment Changes AI Tutoring: Comparing Student Perceptions of Text and AI Human Avatar-Based Chatbot Systems #AIinEducation #chatbot #tugraz

Our publication titled „How Embodiment Changes AI Tutoring: Comparing Student Perceptions of Text and AI Human Avatar-Based Chatbot Systems“ is now published.

Abstract:
Embodied conversational interfaces are able to deliver generative AI tutoring via synthesised speech and human-like video avatars. However, there is limited empirical evidence on how embodiment shapes the learner experience and self-regulated learning (SRL). This study compares the perceptions of students interacting with a text-based Retrieval-Augmented Generation (RAG) tutor and an avatar-based RAG tutor in two authentic higher education contexts (introductory computer science and Python programming) across two European universities. Adopting a Design-Based Research approach, we collected (1) questionnaire data from users and non-users, and (2) anonymised interaction logs comprising 341 user messages, which were coded using an SRL process–action framework. The results show that the perceived level of learning support is largely consistent with previous text-only deployments: the tutor is primarily valued for providing explanations and support related to practice, while motivational support is still comparatively weak. However, embodiment notably improves perceptions of the system as a communication partner, with active users rating this dimension more positively than non-users. Modality ratings suggest that audio output is perceived as more helpful than the visual avatar. Log analyses show that interactions are still dominated by information-seeking (Seeking–Search) and that metacognitive SRL actions (e.g. goal setting and self-evaluation) are rare. Embodiment also introduces additional peripheral interactions (e.g. character-focused prompts and human-likeness checks), thereby increasing the proportion of non-learning dialogue. Overall, the findings suggest that, while embodiment enhances social presence, it does not automatically foster deeper SRL. Explicit pedagogical scaffolding is needed to encourage learners to engage in metacognitive regulation.

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

Reference: Brünner, B., Nestler, M., Pucher, L., Ebner, M. (2026). How Embodiment Changes AI Tutoring: Comparing Student Perceptions of Text and AI Human Avatar-Based Chatbot Systems. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2026. Lecture Notes in Computer Science, vol 16731. Springer, Cham. https://doi.org/10.1007/978-3-032-30542-8_25

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

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[blogpost] Generative KI in der Hochschullehre – Wie wir Innovation verantwortungsvoll gestalten #hfd #tugraz #AI

Wir haben einen kurzen Blogpost über „Generative KI in der Hochschullehre – Wie wir Innovation verantwortungsvoll gestalten,“ beim Hochschulforum Digitalisierung verfasst um auch auf unsere Whitepaper hinzuweisen:

Dieser Blogbeitrag von Philipp Leitner, Benedikt Brünner, Martin Ebner und Sandra Schön bietet Hochschulen eine kompakte Anleitung, wie sie generative KI überlegt in der Lehre einsetzen können. Die Tipps wurden aus der Praxis an der TU Graz entwickelt und getestet und werden ergänzt mit Beispielen sowie Hinweisen auf nützliche Tools.

[Link zum Blogpost]

Whitepaper: Schön, S., Brünner, B., Ebner, M., & Leitner, P. (2026). Evaluating GenAI Innovation in Higher Education. A Whitepaper (Version 1.0 – May 22, 2026). Graz University of Technology. https://doi.org/10.3217/1tfkj-ntj85

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[publication] Empowering Preservice Biology Teachers as Designers of Pedagogical AI Agents: Moving Beyond Data Feeding toward Pedagogical Design #research

Our article about „Empowering Preservice Biology Teachers as Designers of Pedagogical AI Agents: Moving Beyond Data Feeding toward Pedagogical Design“ is published and available online.

Abstract:
Artificial intelligence (AI) influences learning processes, student activities, and the organization of teaching, both in general and specifically in science education. Research indicates that the way AI will affect science learning primarily depends on how it is implemented in teaching. This study examines the ability of preservice biology teachers (PSBTs) to independently develop pedagogical AI agents (TDP-AI agents), most often in the form of chatbots, tailored to teaching goals, content, and students‘ needs. This empirical study, based on a mixed-methods research approach and applying the ICAP theoretical framework, analyzed 54 lesson plans. In addition, the study explored PSBTs‘ perceptions regarding the development and contribution of TDP-AI to biology teaching. The results reveal three patterns of AI agent application in lesson plans: (a) intensive use of TDP-AI agents across all lesson phases, promoting students‘ cognitive engagement, (b) moderate and selective use focused on core activities, and (c) limited use mainly in introductory segments. Five thematic areas reflect PSBTs‘ perspectives: (1) personalization and flexibility of learning, (2) enhancement of student motivation and engagement, (3) development of teachers‘ digital and pedagogical competencies, (4) technical and resource-related challenges in agent development, and (5) pedagogical-methodological barriers in designing student-AI interactions. The findings emphasize the need for systematic support for pre-service teachers in developing digital tools and building pedagogical approaches to ensure AI is used ethically and effectively in science education.

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

Reference: Anđić, B., Helm, C., Weinhandl, R. et al. Empowering Preservice Biology Teachers as Designers of Pedagogical AI Agents: Moving Beyond Data Feeding toward Pedagogical Design. Res Sci Educ (2026). https://doi.org/10.1007/s11165-026-10359-0

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

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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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[issue] Applications of Digital Technology and AI in Educational Settings #tugraz #research

I am happy to announce that my successful journal issue on „Applications of Digital Technology and AI in Educational Settings“ is now closed. In summary, 16 very interesting articles are part of it:

  • Generative AI as a More Knowledgeable Other: An Autoethnographic Study of Game Design Education
  • An Exploratory Study of a Generative AI-Based Intelligent Tutoring System Using a Multi-Agent Architecture in Higher Education
  • Design Principles and Impact of a Learning Analytics Dashboard: Evidence from a Randomized MOOC Experiment
  • Retrieval-Augmented Vision–Language Agents for Child-Centered Encyclopedia Learning
  • A Multi-Agent Chatbot Architecture for AI-Driven Language Learning
  • Memory-Augmented Large Language Model for Enhanced Chatbot Services in University Learning Management Systems
  • PCcGE: Personalized Chinese Couplet Generation and Evaluation Framework Based on Large Language Models
  • Gen-SynDi: Leveraging Knowledge-Guided Generative AI for Dual Education of Syndrome Differentiation and Disease Diagnosis
  • Students’ Perceptions of AI Digital Assistants (AIDAs): Should Institutions Invest in Their Own AIDAs?
  • Digital Human Technology in E-Learning: Custom Content Solutions
  • Automatic Correction System for Learning Activities in Remote-Access Laboratories in the Mechatronics Area
  • Toward Questionnaire Complexity Reduction by Decreasing the Questions
  • Gamification and Immersive Experiences: A Gamified Approach for Promoting Active Aging
  • AI-Driven Smart Transformation in Physical Education: Current Trends and Future Research Directions
  • Regional Perspectives on Service Learning and Implementation Barriers: A Systematic Review
  • An Overview of Commercial Virtual Reality Providers in Education: Mapping the Current Market Landscape

You can find the whole issue here [Link to the Open-Access-Issue]

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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] Sieben Mythen der KI-Nutzung #tugraz

Unser Beitrag zu „Sieben Mythen der KI-Nutzung“ hat viele Reaktionen hervorgerufen und nun wurde er auch in die Zeitschrift „Die Österreichische Volkshochschule“ aufgenommen.

Abstract:
Wer das Internet nutzt, kommt im Frühjahr 2026 nicht um Anwendungen generativer Künstlicher Intelligenz (kurz KI) herum. Suchmaschinen bieten neben Links standardmäßig KI-generierte Antworten an, Chatbots unterstützen bei der Buchung von Websites, Schüler:innen lassen sich Tests passend zu den Arbeitsblättern der Lehrer:innen generieren usw. – Doch nicht alles, was uns die KI-Anwendungen liefern, wie wir sie nutzen und ihre Ergebnisse verstehen, ist zutreffend und unproblematisch. Das liegt auch an Missverständnissen darüber, wie KI-Anwendungen funktionieren. Aus unserer Sicht – es gibt dazu noch keine empirische Evidenz – verdienen folgende sieben Aussagen besondere Aufmerksamkeit, insbesondere auch im Kontext von Bildung, Schule und Hochschule:

  1.  KI-Anwendungen sind neutral, objektiv und vorurteilsfrei
  2.  KI-Anwendungen arbeiten logisch
  3. KI-Anwendungen denken und lernen wie Menschen
  4. KI-Anwendungen sind empathisch
  5. KI-Anwendungen sind ökologisch und sozial problemlos
  6. KI-Nutzung ist rechtlich einwandfrei
  7. KI-Anwendungen machen Wissen und Kompetenzentwicklung überflüssig

In diesem Beitrag möchten wir diese als „Mythen“ bezeichneten Aussagen beschreiben und aufzeigen, dass und warum sie nicht zutreffend sind. Damit möchten wir einen zukünftig fundierten Umgang und durch die Beschreibung von KI-Mythen Forschung dazu initiieren und unterstützen. 

Referenz: Schön, S., Brünner, B., Ebner, M., Diesenreither, S., Hanfstingl, B., Krammer, G (2026) Sieben Mythen der KI-Nutzung. Die Österreichische Volkshochschule. Jg. 2026 / 286. [Link]

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