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

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Title: Vocational Teachers as AI Pioneers: A Study of Professional AI Competence in the Norwegian Vocational Field of Information Technology and Media Production
Language: English
Authors: Svanhild Kristine Berntsen, Øyvind Granborg, Steinar Karstensen, Leif Christian Lahn, Nina Aakernes
Source: International Journal for Research in Vocational Education and Training. 2026 13(3):424-442.
Availability: European Educational Research Association / European Research Network Vocational Education and Training.Am Fallturm 1, Bremen, 28359, Germany. Tel: +49-421-218-66336; Fax: +49-421-218-98-66336; e-mail: ijrvet@uni-bremen.de; Web site: http://www.ijrvet.net
Peer Reviewed: Y
Page Count: 19
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Secondary Education
Descriptors: Foreign Countries, Career and Technical Education Teachers, Artificial Intelligence, Digital Literacy, Information Technology, Technology Uses in Education, Technology Integration, Teacher Attitudes, Secondary School Teachers, Education Work Relationship, Production Techniques
Geographic Terms: Norway
ISSN: 2197-8638
2197-8646
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 realtime 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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1506218
Database: ERIC
FullText Text:
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  Data: Vocational Teachers as AI Pioneers: A Study of Professional AI Competence in the Norwegian Vocational Field of Information Technology and Media Production
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  Data: <searchLink fieldCode="AR" term="%22Svanhild+Kristine+Berntsen%22">Svanhild Kristine Berntsen</searchLink><br /><searchLink fieldCode="AR" term="%22Øyvind+Granborg%22">Øyvind Granborg</searchLink><br /><searchLink fieldCode="AR" term="%22Steinar+Karstensen%22">Steinar Karstensen</searchLink><br /><searchLink fieldCode="AR" term="%22Leif+Christian+Lahn%22">Leif Christian Lahn</searchLink><br /><searchLink fieldCode="AR" term="%22Nina+Aakernes%22">Nina Aakernes</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22International+Journal+for+Research+in+Vocational+Education+and+Training%22"><i>International Journal for Research in Vocational Education and Training</i></searchLink>. 2026 13(3):424-442.
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  Data: European Educational Research Association / European Research Network Vocational Education and Training.Am Fallturm 1, Bremen, 28359, Germany. Tel: +49-421-218-66336; Fax: +49-421-218-98-66336; e-mail: ijrvet@uni-bremen.de; Web site: http://www.ijrvet.net
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  Data: <searchLink fieldCode="DE" term="%22Norway%22">Norway</searchLink>
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  Data: 2197-8638<br />2197-8646
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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 realtime 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.
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      – Text: English
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        PageCount: 19
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      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Career and Technical Education Teachers
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      – SubjectFull: Artificial Intelligence
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      – SubjectFull: Digital Literacy
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      – SubjectFull: Production Techniques
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      – SubjectFull: Norway
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