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Analysis of artificial intelligence policies for higher education in Europe

  • Stracke, Christian M. [1] ; Griffiths, Dai [2] ; Pappa, Dimitra [6] ; Bećirović, Senad [7] ; Polz, Edda [7] ; Perla, Loredana [8] ; Di Grassi, Annamaria [3] ; Massaro, Stefania [8] ; Skenduli, Marjana Prifti [9] ; Burgos, Daniel [2] Árbol académico ; Punzo, Veronica [4] ; Amram, Denise [4] ; Ziouvelou, Xenia [6] ; Katsamori, Dora [6] ; Gabriel, Sonja [10] ; Nahar, Nurun [5] ; Schleiss, Johannes [11] ; Hollins, Paul [5]
    1. [1] University of Bonn

      University of Bonn

      Kreisfreie Stadt Bonn, Alemania

    2. [2] Universidad Internacional de La Rioja

      Universidad Internacional de La Rioja

      Logroño, España

    3. [3] University of Foggia

      University of Foggia

      Foggia, Italia

    4. [4] Sant'Anna School of Advanced Studies

      Sant'Anna School of Advanced Studies

      Pisa, Italia

    5. [5] University of Bolton

      University of Bolton

      Reino Unido

    6. [6] National Centre for Scientific Research “Demokritos”
    7. [7] University College of Teacher Education Lower Austria
    8. [8] University of Bari
    9. [9] University of New York Tirana
    10. [10] University College for Teacher Education of Christian Churches Vienna/Krems
    11. [11] Otto von Guericke University Magdeburg
  • Localización: IJIMAI, ISSN-e 1989-1660, Vol. 9, Nº. 2, 2025, págs. 124-137
  • Idioma: inglés
  • DOI: 10.9781/ijimai.2025.02.011
  • Enlaces
  • Resumen
    • This paper analyses 15 AI policies for higher education from eight European countries, drawn from individual universities, from consortia of universities and from government agencies. Based on an overview of current research findings, it focuses the comparison of different aspects among the selected AI policies. The analysis distinguishes between four potential target groups, namely students, teachers, education managers and policy makers. The paper aims at contributing to the further development and improvement of AI policies for higher education through the identification of commonalities and gaps within the existing AI policies. Moreover, it calls for further and in particular evidence-based research to identify the potential and practical impact of AI in higher education and highlights the need to combine AI use in (higher) education with education about AI, often called as AI literacy.

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