Conference Agenda
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Please note that all times are shown in the time zone of the conference. The current conference time is: 19th Aug 2026, 21:28:40 EET
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02 SES 07 B: Emerging Researchers as AI Pioneers: Ethical Challenges of AI Use in Vocational Education and Training – A Shift in Perspective
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02. Vocational Education and Training (VETNET)
Research Workshop Emerging Researchers as AI Pioneers: Ethical Challenges of AI Use in Vocational Education and Training – A Shift in Perspective University of Bremen, Institute Technology and Education (ITB), Germany Presenting Author:Debates on artificial intelligence (AI) in education have been very active in recent years due to various developments and innovations in this area. Furthermore, there have been various national and international strategy papers as well as funding programmes to provide support for the implementation of AI in educational contexts (Meyne et al., 2025). In parallel to various risks, there are numerous advantages and potentials associated with the use of AI in vocational training (De Witt, 2024; Roppertz, 2021). Furthermore, UNESCO emphasises that "emerging practices in the use of AI in education clearly demonstrate the potential of AI to enable new forms of teaching, learning and education management and enhance learning experiences and support teacher tasks" (UNESCO, 2024, p. 13). Seufert (2023) states that the use of AI goes hand in hand with new and innovative learning objectives, methods and environments. AI competences will be needed in the context of all of these aspects and new forms of collaboration will become necessary. In order to be able to use new AI technologies precisely, basic knowledge and application expertise is required (Rampelt et al., 2025).
Furthermore, it is essential promising to focus on learning from each other in groups and networks when it comes to developing skills, especially from an international point of view with many potentials to share lessons learned and practical use cases of AI in VET for what workshop settings are well suited. The main question addressed by the workshopdescribed below is: How can practical learning scenarios in vocational training enable emerging researcher to use AI tools in a reflective and ethically responsible manner, particularly with regard to data protection, bias, transparency and accountability?
The interactive workshop on the integration and ethical reflection of artificial intelligence (AI) in vocational education and training guides participants (especially emerging researchers) step by step through a practical and critically reflective examination of current developments. The main objective of the workshop is to foster participants’ ethical and practical literacy in dealing with AI by combining theoretical orientation with hands-on experience. Participants explore cases that mirror authentic training contexts and professional sectors, allowing them to identify and assess opportunities, risks, and tensions arising from the use of AI. By experimenting with realistic application scenarios, from nursing education to technical and commercial training fields, they develop a multidimensional understanding of AI’s pedagogical, social, and regulatory implications. Through structured group interaction, the workshop aims to stimulate collective reflection on what responsible use entails and what competences are required to sustain it.
The workshop draws on an interdisciplinary framework focussing on ethical reflection embedded in authentic work scenarios with different professional perspectives—teachers, learners, data officers, or customers. This perspective enriches the discourse on accountability and trust. The workshop explicitly situates its inquiry within the European and international policy landscape on digital and ethical competence. References to frameworks such as the EU’s “Digital Education Action Plan” and UNESCO’s “AI Competency Framework for Educators” underline the transnational relevance of its approach. Ethical literacy in AI thus becomes not only a local institutional concern but a shared international objective shaping global vocational training. By connecting reflections from diverse national and professional contexts, the workshop contributes to strengthening a common European understanding of how responsible AI use can support inclusive, transparent, and future-oriented vocational education. Methodology, Methods, Research Instruments or Sources Used After a brief welcome, a presentation entitled ‘Where AI already shapes VET’ will set the context: concrete examples from vocational schools, training situations, learning platforms and everyday application scenarios will be used to show where AI already plays a role nowadays. The introduction is rounded off with input on the ‘Ethics Check’, which highlights the evaluation of AI using a selected scheme: topics such as data protection, bias, transparency, educational responsibility and monitoring are made tangible here using the AI Pioneers Ethical Evaluation Scheme (Roman Etxebarrieta et al., 2025). Participants then deepen their discussion in small groups using case studies from various areas of vocational training. Three thematic scenarios illustrate the diversity and complexity of AI use in practice: In nursing training, learners test chatbots for creating nursing reports and preparing for exams – raising questions about data sensitivity, hallucinations and professional responsibility. In the commercial-technical field, for example among industrial mechanics, the focus is on AI-supported assistance systems that guide maintenance work, raising questions about automation, safety and skills development. Finally, in the commercial sector, AI tools are used to create application documents, sales texts or feedback on customer dialogues – here, aspects such as fairness, equal treatment and academic integrity come into focus. Each group uses digital tools of their choice, such as visualisation or documentation tools, to address key questions: What added value does the use of AI offer? Where are the ethical risks? What data is used and what skills are required? The participants take different perspectives – those of teachers, learners, trainers, IT or data protection officers, or customers and patients. The results of this work are then presented in short pitch presentations to the plenary. This is followed by a concise input on the ‘Process of Implementing AI in VET institutions’, which highlights important steps and stumbling blocks in the institutional use of AI tools. Finally, all groups compile the most important findings in the form of a practical ‘dos and don'ts’ list for AI in vocational training. In a final reflection round – in the form of a short flashlight – each participant formulates which suggestion or idea he or she will take back to their own institution the next day. The workshop thus ends with a sense of shared orientation, concrete impulses for action and a heightened sensitivity to the responsible use of artificial intelligence in vocational education and training. Conclusions, Expected Outcomes or Findings The workshop described above, entitled ‘Emerging Researchers as AI Pioneers: Ethical Challenges of AI Use in Vocational Education and Training – A Shift in Perspective’, aims to directly address emerging researchers in vocational education and training with regard to the use of AI. For this purpose, the focus will be on practical case studies from vocational education and training in order to learn from each other from an international perspective and enable the transfer to one's own everyday work. The workshop will be structured around cooperative small group work with roles and case studies from various professional fields in order to ensure international perspectives and practical relevance, to treat AI as both a subject of learning and a learning tool, and to promote critical reflection and action-oriented learning as central goals of the workshop format. As a further outcome of the workshop, emerging researchers should be able to take away the most important findings of the cooperative exchange in the form of a practical “dos and don'ts” guide for AI in vocational training, which will be created jointly and made available afterwards. Finally, the workshop should contribute to networking among emerging researchers so that exchange is encouraged even after the conference. References De Witt, C. (2024). Künstliche Intelligenz in der Berufsbildung. Technologische Entwicklungen, didaktische Potenziale und notwendige ethische Standards. BWP, 53(1), 8-12. https://www.bwp-zeitschrift.de/dienst/publikationen/de/19416 Meyne, L., Klaus, F., Siemer, C., Deitmer, L., & Gessler, M. (2025). Artificial Intelligence in Vocational Education and Training: A Micro, Meso and Macro Perspective From the AI Pioneers Project. Ubiquity Proceedings, 6(1), 4.https://doi.org/10.5334/uproc.172 Rampelt, F., Klier, J., Kirchherr, J., & Ruppert, R. (2025). KI-Kompetenzen in deutschen Unternehmen. Schlüssel zu einer Jahrhundertchance für Deutschland. Stifterverband. https://doi.org/10.5281/zenodo.14637137 Roman Etxebarrieta, G., Orcasitas-Vicandi, M., & Antzaka, A. ( 2025). Evaluation schema for AI in education on data, privacy, ethics, and EU values. AI Pioneers. https://aipioneers.org/evaluation-schema-for-ai-in-education-on-data-privacy-ethics-and-eu-values-wp5/ Roppertz, S. (2021). Die Rolle und Bedeutung von Künstlicher Intelligenz in der Berufsausbildung – Implikationen für angehende Berufs- und Wirtschaftspädagog*innen. bwp@ Berufs- und Wirtschaftspädagogik – online, 40, 1-23. https://www.bwpat.de/ausgabe40/roppertz_bwpat40.pdf Seufert, S. (2023). KI-basierte Anwendungsfälle für die Lernortkooperation. Gestaltung eines digitalen Ökosystems in der Berufsbildung. Zeitschrift für Berufs- und Wirtschaftspädagogik, 119(2), 208–235. https://doi.org/10.25162/zbw-2023-0009 Unesco (2024). AI competency framework for teachers. United Nations Educational, Scientific and Cultural Organization. https://doi.org/10.54675/ZJTE2084 | ||