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Research field

Artificial Intelligence

Artificial intelligence in work and education; generative and adaptive AI systems; human–AI collaboration; AI competences and AI literacy; AI-supported teaching-learning processes and feedback; AI-supported competence diagnostics; qualification needs arising from AI; AI ethics and data protection; algorithmic discrimination; responsible and participatory AI design; AI governance in educational organisations.

Artificial intelligence is changing occupational work processes, competence requirements and teaching-learning processes at the same time. This research field bundles the ITB's AI-related research and examines AI as an object, a tool and a design task of vocational education and training. At the level of work, the focus is on the use of AI systems in occupational work processes, forms of human–AI collaboration, changes in occupational requirement profiles and the early identification of the resulting qualification needs. At the level of learning, generative and adaptive AI systems, intelligent tutoring systems and AI-supported learning analytics are examined with regard to how they support feedback, individualisation, reflection and cooperation, and how they can be embedded in initial training, classroom teaching and continuing training in pedagogically and didactically sound ways. This is complemented by the development of AI-supported procedures for competence diagnostics, validation and curriculum development. As a cross-cutting theme, the field researches the development of AI competences (AI literacy) among learners, skilled workers and training staff. At the normative and organisational level, it addresses AI ethics, data protection, transparency, algorithmic discrimination and digital inequality, as well as questions of governance and the responsible implementation of AI in companies, vocational schools and educational organisations. The aim is design-oriented research that develops, tests and evaluates AI applications together with practice partners and thus contributes to a self-determined, critically reflective use of AI in work and vocational education and training.

Research questions

  1. How does the use of AI systems change occupational work processes, the division of tasks and the requirement profiles of skilled workers in different occupational fields?

  2. How can forms of human–AI collaboration be designed that preserve and extend the experiential knowledge, scope of action and learning opportunities of skilled workers?

  3. Which AI competences (AI literacy) do learners, skilled workers and training staff need, and how can they be anchored in curricula and continuing training?

  4. Under which didactic conditions do generative and adaptive AI systems support feedback, individualisation and reflection in vocational teaching-learning processes?

  5. How can AI-supported procedures assist competence diagnostics, validation and curriculum development, and how valid and fair are their results?

  6. Which ethical, data-protection and anti-discrimination requirements must AI applications in companies and educational organisations meet?

  7. How can AI be introduced responsibly and participatively in vocational schools, companies and educational organisations, and which governance structures does this require?

Projects

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