Vocational Teachers as AI Pioneers: A Study of Professional AI Competence in the Norwegian Vocational Field of Information Technology and Media Production.

Autor/inn/en	Berntsen, Svanhild Kristine; Granborg, Øyvind; Karstensen, Steinar; Lahn, Leif Christian; Aakernes, Nina
Titel	Vocational Teachers as AI Pioneers: A Study of Professional AI Competence in the Norwegian Vocational Field of Information Technology and Media Production.
Quelle	In: International journal for research in vocational education and training, 13 (2026) 3, S. 424-442Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
ISSN	2197-8646
DOI	10.13152/IJRVET.13.3.5
Schlagwörter	Kompetenz; Künstliche Intelligenz; Lehrerbildung; Lernumgebung; Lernmethode; Curriculum; Digitalisierung; Berufliche Fortbildung; Berufsbildung; Norwegen
Abstract	Context: Artificial intelligence (AI) integration into education is advancing rapidly, yet vocational education and training (VET) remains underexplored in AI and education research. The limited attention to VET is particularly salient given that vocational teachers are expected to prepare students for a digitalised labour market in which AI increasingly informs and transforms occupational practices. This article explores how vocational teachers in the Norwegian Information Technology and Media Production (ITMP) programme integrate AI in their teaching and how it affects their professional digital competence. Approach: Using a qualitative, exploratory case study design, we investigated two upper secondary schools in Norway that were identified as early adopters of AI in vocational teaching. Data sources included interviews with four teachers, classroom observations, documents (e.g., assignments and presentations), and field notes from teacher-industry network meetings. The data were analysed using abductive thematic analysis, supported by generative AI tools to explore emergent patterns. We employed a framework for vocational teachers' professional digital competence to guide the analysis. Findings: The study identifies three main deyvelopments. First, AI tools such as ChatGPT and image generators are widely used to support students' autonomous learning and enable real-time feedback in coding, design, and text-based tasks. Second, teachers use AI in profession-specific ways to enable students to develop digital products, business ideas, and portfolios, thus fostering creativity and entrepreneurship. Third, AI transforms teachers' professional identity and digital competence. They transition from knowledge transmitters to facilitators in a co-learning relationship with students and AI systems. Teachers also report relying on informal networks and personal initiative for upskilling, while systemic support remains limited. Conclusion: Vocational teachers in the ITMP programme emerge as AI pioneers, developing innovative didactic practices and digital strategies through bottom-up experimentation. However, the findings also highlight tensions concerning assessment, deep learning, ethical concerns, and unequal access to AI tools. These point to the need for revised frameworks of vocational digital competence, targeted teacher training, and institutional support. The study contributes to the emerging field of vocational AI didactics and provides empirical grounding for future policy and curriculum development in VET.
Erfasst von	GESIS - Leibniz-Institut für Sozialwissenschaften, Mannheim
Update	2026/3