Schlagwort: conference

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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] On Using an LLM-Based Approach for Automatic Evaluation of Programming Tasks in MOOC Videos #tugraz #AIinEducation

Our publication about „On Using an LLM-Based Approach for Automatic Evaluation of Programming Tasks in MOOC Videos“ has been published.

Abstract:
Interactive videos promote learner engagement by transforming the passive activity of watching videos into an active learning process. LIVE, a web platform developed in previous research that allows for the integration of interactive elements into videos, also supports embedding programming tasks. However, at the beginning of our research, the output of the submitted solution was automatically compared to the reference output, but the code itself still had to be checked manually, as no automatic process was available to verify the solution and provide feedback. To address this, a stand-alone application was developed that automatically evaluates students’ solutions to Python programming tasks using a self-hosted large language model. This application was then integrated into the existing platform. To test this approach, a massive open online course containing four interactive videos with several programming tasks and quizzes was created. Students’ performance was analyzed using quiz results, task submissions, self-assessments, and user statistics provided by the course platform and LIVE. The results indicate that utilizing a large language model for automated feedback can positively impact learning outcomes. However, some limitations must be taken into account, such as the need to correct some of the model’s generated outputs manually due to insufficient feedback quality for certain tasks. This suggests that the combination of automated and manual evaluation seems to be the most effective approach for now.

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

Reference: Kindlhofer, C., Wachtler, J., Ebner, M. (2026). On Using an LLM-Based Approach for Automatic Evaluation of Programming Tasks in MOOC Videos. In: Smith, B.K., Borge, M. (eds) Learning and Collaboration Technologies. HCII 2026. Lecture Notes in Computer Science, vol 16733. Springer, Cham. https://doi.org/10.1007/978-3-032-30784-2_13

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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] Motivation and Self-Regulated Learning in Secondary Schools with Flipped Classrooms: A Systematic Literature Review #edmedia #research

Our publication about „Motivation and Self-Regulated Learning in Secondary Schools with Flipped Classrooms: A Systematic Literature Review“ for this year’s edmedia conference is out.

Abstract:
In recent years, flipped classroom (FC) models have gained traction as an innovative pedagogical approach that promotes active, student-centered learning environments. Although the effectiveness of the FC model has been widely studied in higher education and teacher training contexts, its impact on secondary school students, particularly with regard to motivation and self-regulated learning (SRL), remains understudied. This systematic literature review summarizes findings from 34 studies on FC implementations in secondary education, focusing specifically on strategies that enhance motivation and SRL outcomes. The review reveals that FC approaches can significantly enhance student motivation, particularly among low-achieving and low-confidence learners, by fostering active participation, self-efficacy, and engagement. However, challenges such as technical barriers, an increased workload, and initial resistance underscore the importance of careful design and teacher support. The findings highlight the critical role of teachers as facilitators, content creators, and motivators in successfully implementing FC in secondary schools.

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

Reference: Urak, K., Brünner, B., Geier, G. & Ebner, M. (2026). Motivation and Self-Regulated Learning in Secondary Schools with Flipped Classrooms: A Systematic Literature Review. In Proceedings of EdMedia 2026 Edinburgh (pp. 1701-1711). Edinburgh, Scotland: Association for the Advancement of Computing in Education (AACE). Retrieved July 1, 2026 from https://www.learntechlib.org/primary/p/2129811/.

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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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[poster] A Whitepaper on Evaluating GenAI Innovation in Higher Education #edmedia26

This year, we present a poster about „A Whitepaper on Evaluating GenAI Innovation in Higher Education“ at EDMedia 2026.

Generative artificial intelligence (genAI) is increasingly shaping higher education by enabling new forms of content creation, assessment, learner support, personalization, and synthetic media. A whitepaper now 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, recurring decision points and risk patterns were identified to formulate a five-phase, non-linear evaluation model.

[Link to the poster]
[Link to ResearchGate]

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

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[presentation] Impact of AI on teaching strategy #tugraz

Today I give a short presentation about „Impact of AI on teaching strategy“ at TAM CONFERENCE on “ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION” in Kazakhstan. I will introduce the LISA Framework and provide examples from Graz University of Technology.

[Link to the slides @ Repository TU Graz]

This is an impactful contributions, methodological rigor, and exceptional novelty in the research field of AI in education. It explains a powerful framwork, named LISA framework to categorize AI teaching and learning activities.

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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/