Published April 14, 2026 | Version v2
Conference proceeding Open

Making teacher-AI complementarity visible with task-, skill- and knowledge analysis

Authors/Creators

  • 1. ROR icon Radboud University Nijmegen
  • 2. ROR icon University of Amsterdam
  • 3. ROR icon University College London
  • 4. ROR icon Ruhr University Bochum
  • 5. Radboud university

Description

The official Version of Record of this contribution is published in the Proceedings of the International Conference of Artificial Intelligence in Education 2026, and is available online at https://doi.org/10.1007/978-3-032-29791-4_35.

Please cite this paper as: Kramer, AW. et al. (2026). Making Teacher-AI Complementarity Visible with Task-, Skill- and Knowledge Analysis. In: Blanchard, E.G., Chen, G., Chi, M., Isotani, S. (eds) Artificial Intelligence in Education. Late Breaking Results, WideAIED, Practitioners, Industry and Policies, Blue Sky, Doctoral Consortium, FoL Workshops and Tutorials, FoL Invited Papers. AIED 2026. Communications in Computer and Information Science, vol 3032. Springer, Cham. https://doi.org/10.1007/978-3-032-29791-4_35 

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Funding

European Commission
TAICo - Teacher-AI Complementarity 101177268