Empirically Grounding and Refining a Model for Teachers’ AI-Related Competences: Insights from Expert Interviews
The European Educational Researcher, Volume 9, Issue 3, October 2026, pp. 1-21
OPEN ACCESS VIEWS: 11 DOWNLOADS: 3 Publication date: 15 Oct 2026
OPEN ACCESS VIEWS: 11 DOWNLOADS: 3 Publication date: 15 Oct 2026
ABSTRACT
The growing adoption of artificial intelligence (AI) in education is reshaping teaching and learning in schools, while also increasing the professional demands on teachers. To support effective and responsible AI use in schools, a clear and empirically grounded understanding of teachers’ AI-related competences is required. This study examines and refines an existing competence model by incorporating perspectives from diverse stakeholder groups. Seven semi-structured expert interviews were conducted with representatives from computer science, educational science, subject-specific didactics, schools, industry, and education policy. The data were analysed using structured qualitative content analysis to identify relevant competence dimensions and their interrelations. The findings largely support the overall structure of the model but place particular emphasis on the central role of AI didactics. AI-related competences are not limited to technical understanding or tool use but crucially involve the ability to design, implement, and reflect on learning processes with and about AI. This includes selecting meaningful use cases, adapting instructional formats, addressing ethical and societal implications, and developing new approaches to assessment and classroom practice in response to AI. In addition, personal and social dispositions for effective AI use and teaching about AI in everyday school practice function as enabling conditions for the enactment of these competences. Based on these results, the model was elaborated to provide an empirically grounded, didactically actionable framework for teacher education and future research.
KEYWORDS
AI competences, competence model, teacher education, qualitative content analysis.
CITATION (APA)
Mikula, L. (2026). Empirically Grounding and Refining a Model for Teachers’ AI-Related Competences: Insights from Expert Interviews. The European Educational Researcher, 9(3), 1-21. https://doi.org/10.31757/euer.19108
REFERENCES
- ALLEA. (2023). The European code of conduct for research integrity – Revised edition 2023. https://doi.org/10.26356/ECOC
- Bitkom. (2024). Wie digital sind Deutschlands Schulen? [How digital are German schools?] https://bitkom-research.de/node/1062
- Bitkom. (2025). Digitale Schule [Digital school]. https://doi.org/10.64022/2025-digitale-schule
- Bloom, B. S. (Ed.). (1956). Taxonomy of educational objectives: The classification of educational goals. Handbook I: Cognitive domain. David McKay.
- Bogner, A., Littig, B., & Menz, W. (2014). Interviews mit Experten: Eine praxisorientierte Einführung [Interviews with experts: A praxisoriented introduction]. Springer VS. https://doi.org/10.1007/978-3-531-19416-5
- Brinda, T., Brüggen, N., Diethelm, I., Knaus, T., Kommer, S., Kopf, C., Leschke, R., Missomelius, P., Tilemann, F., & Weich, A. (2025). Frankfurt triangle for education in the digital world. MedienPädagogik: Zeitschrift Für Theorie Und Praxis Der Medienbildung, 186–198. https://doi.org/10.21240/mpaed/00/2025.08.06.X
- Calzada-Prado, J., & Marzal, M. Á. (2013). Incorporating Data Literacy into Information Literacy Programs: Core Competencies and Contents. Libri, 63(2), 123-134.. https://doi.org/10.1515/libri-2013-0010
- Celik, I. (2023). Towards Intelligent-TPACK: An empirical study on teachers’ professional knowledge to ethically integrate artificial intelligence (AI)-based tools into education. Computers in Human Behavior, 138. https://doi.org/10.1016/j.chb.2022.107468
- Delcker, J., Heil, J., & Ifenthaler, D. (2025). Evidence-based development of an instrument for the assessment of teachers’ self-perceptions of their artificial intelligence competence. Educational Technology Research and Development, 73(1), 115–133. https://doi.org/10.1007/s11423-024-10418-1
- Döbeli Honegger, B. (2021). Covid-19 und die digitale Transformation in der Schweizer Lehrerinnen- und Lehrerbildung [Covid-19 and the digital transformation in Swiss teacher education]. BzL - Beiträge Zur Lehrerinnen- Und Lehrerbildung, 39(3), 411–422. https://doi.org/10.36950/bzl.39.3.2021.9217
- Elstad, E., & Eriksen, H. (2026). Integration of Artificial Intelligence as an institutionalised wicked problem in Norwegian upper-secondary education. European Journal of Educational Management, 9(2), 125–140. https://doi.org/10.12973/eujem.9.2.125
- Falloon, G. (2020). From digital literacy to digital competence: The teacher digital competency (TDC) framework. Educational Technology Research and Development, 68(5), 2449–2472. https://doi.org/10.1007/s11423-020-09767-4
- Holmes, W., Bialik, M., & Fadel, C. (2023). Artificial intelligence in education. In C. Stückelberger & P. Duggal (Eds.), Data ethics: building trust: How digital technologies can serve humanity (pp. 621–653). Globethics Publications. https://doi.org/10.58863/20.500.12424/4276068
- Jaschke, S., Klusch, M., Krupka, D., Losch, D., Michaeli, T., Opel, S., Schmid, U., Schwarz, R., Seegerer, S., & Stechert, P. (2023). Positionspapier der Gesellschaft für Informatik e.V. (GI): Künstliche Intelligenz in der Bildung [Position-Paper by the German Informatics Society (GI): Artificial Intelligence in education]. Gesellschaft für Informatik. https://dl.gi.de/server/api/core/bitstreams/7c533204-8a9e-4436-91a8-069b7d74fc8d/content
- Krell, C., & Lamnek, S. (2024). Qualitative Sozialforschung: Mit Online-Material [Qualitative social Research: With online materials]. Julius Beltz GmbH & Co. KG.
- Kuckartz, U., & Rädiker, S. (2023). Qualitative content analysis: Methods, practice and software (2nd ed.). Sage Text UK. https://doi.org/10.4135/9781036212940
- Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159. https://doi.org/10.2307/2529310
- Laupichler, M. C., Aster, A., Haverkamp, N., & Raupach, T. (2023). Development of the “Scale for the assessment of non-experts’ AI literacy” – An exploratory factor analysis. Computers in Human Behavior Reports, 12. https://doi.org/10.1016/j.chbr.2023.100338
- Le Deist, F. D., & Winterton, J. (2005). What Is Competence? Human Resource Development International, 8(1), 27–46. https://doi.org/10.1080/1367886042000338227
- Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. In Proceedings of the CHI 2020. https://doi.org/10.1145/3313831.3376727
- Meuser, M., & Nagel, U. (2009). Das Experteninterview – konzeptionelle Grundlagen und methodische Anlage [The expert interview – Conceptual foundations and methodological framework]. In S. Pickel, G. Pickel, H.-J. Lauth, & D. Jahn (Eds.), Methoden der vergleichenden Politik- und Sozialwissenschaft: Neue Entwicklungen und Anwendungen [Methods in comparative political and social science: New developments and applications] (1. ed., pp. 465–479). VS Verlag für Sozialwissenschaften. https://doi.org/10.1007/978-3-531-91826-6_23
- Mikeladze, T., Meijer, P. C., & Verhoeff, R. P. (2024). A comprehensive exploration of artificial intelligence competence frameworks for educators: A critical review. European Journal of Education, 59(3), Article e12663, e12663. https://doi.org/10.1111/ejed.12663
- Mikula, L. (2026a). Interviewleitfaden zu KI-bezogenen Kompetenzen von Lehrkräften [Interviewguide on teachers‘ AI-related competences]. https://doi.org/10.57880/rdspace-ubt-51
- Mikula, L. (2026b). Kodierhandbuch zu Experteninterviews über KI-bezogene Kompetenzen von Lehrkräften [Coding manual for expert interviews on teachers‘ AI-related competences]. https://doi.org/10.57880/rdspace-ubt-747
- Mikula, L. (2026c). Towards a comprehensive model of AI-related competences for teachers: Insights from a scoping literature review. Education Journal, 15(3), 113–132. https://doi.org/10.11648/j.edu.20261503.12
- Missomelius, P. (2016). Die Dagstuhl-Erklärung [The Dagstuhl-Declaration]. Medienimpulse, 54(1). https://doi.org/10.21243/MI-01-16-15
- Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2. https://doi.org/10.1016/j.caeai.2021.100041
- Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers' AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6
- OECD. (2025). Results from TALIS 2024: The State of Teaching. TALIS. OECD Publishing. https://doi.org/10.1787/90df6235-en
- Raffaghelli, J. E. (2019). Developing a Framework for Educators’ Data Literacy in the European context: Proposal, Implications and Debate. In L. Gómez Chova, A. López Martínez, & I. Candel Torres (Eds.), EDULEARN Proceedings, EDULEARN19 Proceedings (pp. 10520–10530). IATED. https://doi.org/10.21125/edulearn.2019.2655
- Redecker, C. (2017). European framework for the digital competence of educators: DigCompEdu. Publications Office of the European Union. https://doi.org/10.2760/159770
- Reinhold, A. (2015). Das Experteninterview als zentrale Methode der Wissensmodellierung in den Digital Humanities [The expert interview as a key method for knowledge modeling in the digital humanities]. Information - Wissenschaft & Praxis, 66(5-6), 327–333. https://doi.org/10.1515/iwp-2015-0057
- Rieck, D. A., & Hellmig, L. (2025). KI in deutschsprachigen Rahmenplänen. In Gesellschaft für Informatik e.V. (Chair), Posterbeiträge, Stoos, Schweiz. https://doi.org/10.18420/infos2025_po_16
- Robert Bosch Stiftung. (2025). Deutsches Schulbarometer: Befragung Lehrkräfte. Ergebnisse zur aktuellen Lage an allgemein- und berufsbildenden Schulen [German school barometer: Survey of teachers. Findings on the current situation in general and vocational schools]. Robert Bosch Stiftung. https://www.bosch-stiftung.de/de/publikation/deutsches-schulbarometer-lehrkraefte-2025
- Seyferth-Zapf, C., Mikula, L., & Ehmann, M. (2025). Förderung KI-bezogener Kompetenzen bei Lehramtsstudierenden: Praxis- und theorieorientierte Entwicklung und Evaluation eines hochschuldidaktischen Konzepts [Promoting AI-related skills among pre-service teachers: Practice- and theory-oriented development and evaluation of a university teaching concept]. Journal Für Allgemeine Didaktik, 13, 108–134. https://doi.org/10.35468/jfad-13-2025-05
- Shiri, A. (2024). Artificial intelligence literacy: a proposed faceted taxonomy. Digital Library Perspectives, 40(4), 681–699. https://doi.org/10.1108/DLP-04-2024-0067
- Thyssen, C., Huwer, J., Irion, T., & Schaal, S. (2023). From TPACK to DPACK: The “Digitality-Related Pedagogical and Content Knowledge”-Model in STEM-Education. Education Sciences, 13(8), 769. https://doi.org/10.3390/educsci13080769
- Tong, A., Sainsbury, P., & Craig, J. (2007). Consolidated criteria for reporting qualitative research (COREQ): A 32-item checklist for interviews and focus groups. International Journal for Quality in Health Care, 19(6), 349–357. https://doi.org/10.1093/intqhc/mzm042
- UNESCO. (2024). AI competency framework for teachers. United Nations Educational, Scientific and Cultural Organization. https://doi.org/10.54675/ZJTE2084
- Wang, B., Rau, P.-L. P., & Yuan, T. (2023). Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & Information Technology, 42(9), 1324–1337. https://doi.org/10.1080/0144929X.2022.2072768
- Weich, A. (2019). Das „Frankfurt-Dreieck“ [The „Frankfurt-Triangle“]. Medienimpulse, 57(2). https://doi.org/10.21243/mi-02-19-05
- Weinert, F. E. (2001). Concept of competence: A conceptual clarification. In D. S. Rychen & L. H. Salganik (Eds.), Defining and selecting key competencies (pp. 45–65). Hogrefe & Huber Publishers.
- Wimmer, R. D., & Dominick, J. R. (2014). Mass media research: An introduction (10th ed.). Wadsworth series in mass communication and journalism. Cengage.
LICENSE
This work is licensed under a Creative Commons Attribution 4.0 International License.