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Erasmus+ KA3 - European Policy Experimentation
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References

Academic and institutional sources underpinning the PLAIP framework

  • Banks, I. (2026). Judges-in-the-loop? Judicial involvement in human oversight of high-risk decision support systems under the EU AI Act. International Journal of Law and Information Technology, 34, eaag001. https://doi.org/10.1093/ijlit/eaag001
  • Black, P., & Wiliam, D. (2018). Classroom assessment and pedagogy. Assessment in Education: Principles, Policy & Practice, 25(6), 551–575. https://doi.org/10.1080/0969594X.2018.1441807
  • Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. Internet and Higher Education, 27, 1–13. https://doi.org/10.1016/j.iheduc.2015.04.007
  • Cosgrove, J., & Cachia, R. (2025). DigComp 3.0: European digital competence framework (5th ed.). Publications Office of the European Union. https://data.europa.eu/doi/10.2760/0001149
  • Council of Europe (2018). Reference Framework of Competences for Democratic Culture (RFCDC). https://www.coe.int/en/web/reference-framework-of-competences-for-democratic-culture
  • Council Recommendation on Pathways to School Success (2022); Council Recommendation on Key Competences for Lifelong Learning (2018); Digital Education Action Plan 2021-2027; European Pillar of Social Rights Action Plan (2021).
  • Education Endowment Foundation (2024). Teaching and Learning Toolkit. EEF.
  • European Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). Official Journal of the European Union.
  • Garzón, J., Patiño, E., & Marulanda, C. (2025). Systematic Review of Artificial Intelligence in Education: Trends, Benefits, and Challenges. Multimodal Technologies and Interaction, 9(8), 84. https://doi.org/10.3390/mti9080084
  • Haddad, C. R., & Bergek, A. (2023). Towards an integrated framework for evaluating transformative innovation policy. Research Policy, 52(2), 104676. https://doi.org/10.1016/j.respol.2022.104676
  • Hattie, J. (2023). Visible learning: The sequel. Routledge. https://doi.org/10.4324/9781003381627
  • Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
  • Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068
  • Kang, S. H. K. (2016). Spaced repetition promotes efficient and effective learning: Policy implications for instruction. Policy Insights from the Behavioral and Brain Sciences, 3(1), 12–19. https://doi.org/10.1177/2372732215624708
  • Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727
  • Merino-Campos, C. (2025). The Impact of Artificial Intelligence on Personalized Learning in Higher Education: A Systematic Review. Trends in Higher Education, 4(2), 17. https://doi.org/10.3390/higheredu4020017
  • Molenaar, I. (2022). The concept of hybrid human-AI regulation: Exemplifying how to support young learners' self-regulated learning. Computers and Education: Artificial Intelligence, 3, 100070. https://doi.org/10.1016/j.caeai.2022.100070
  • Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041. https://doi.org/10.1016/j.caeai.2021.100041
  • OECD (2023). AI and the Future of Skills. OECD Publishing. https://doi.org/10.1787/1234abcd
  • Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-regulated learning strategies on students' academic performance: A meta-analysis. Educational Research Review, 22, 77–98. https://doi.org/10.1016/j.edurev.2017.08.004
  • Sant, E. (2021). Political education in times of populism: Towards a radical democratic approach. Springer.
  • Smuha, N. A. (2021). From a 'race to AI' to a 'race to AI regulation': Regulatory competition for artificial intelligence. Law, Innovation and Technology, 13(1), 57–84. https://doi.org/10.1080/17579961.2021.1898300
  • UNESCO (2024). Guidance for Generative AI in Education and Research. UNESCO.
  • Vuorikari, R., Kluzer, S., & Punie, Y. (2022). DigComp 2.2: The digital competence framework for citizens. Publications Office of the European Union. https://doi.org/10.2760/115376
  • Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223–235. https://doi.org/10.1080/17439884.2020.1798995
  • Wisniewski, B., Zierer, K., & Hattie, J. (2020). The Power of Feedback Revisited: A Meta-Analysis of Educational Feedback Research. Frontiers in Psychology, 10, 3087. https://doi.org/10.3389/fpsyg.2019.03087
  • Yeager, D. S., Hanselman, P., Walton, G. M., et al. (2019). A national experiment reveals where a growth mindset improves achievement. Nature, 573, 364–369. https://doi.org/10.1038/s41586-019-1466-y
  • Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education: Where are the educators? International Journal of Educational Technology in Higher Education, 16, 39. https://doi.org/10.1186/s41239-019-0171-0