A Multidisciplinary Research Agenda for Artificial Intelligence, Education, Learning, and Instruction

Abstract Artificial Intelligence (AI) is reshaping education, learning, and instruction, yet current research in this area is fragmented, often tool-specific, and dominated by short-term perspectives. This article develops a broader research agenda for AI and Education (AI&ED), bringing together Artificial Intelligence in Education (AIED) and AI literacy within an educational ecology framing. Using a collective writing methodology, an expert panel of eleven internationally recognised scholars from various disciplines within computer and learning sciences contributed ten standalone reflections on the challenges, opportunities, and transformations of AI&ED. Two additional leading scholars provided critical commentaries to strengthen the analysis. A thematic analysis of the contributions identifies five main challenges (learning and instructional practices and curricula, access and ethics, assessment and evaluation, research capacity, and stakeholder readiness), five areas of opportunity (enhanced pedagogies, innovation in design and research, support for learning processes, critical skills, and hybrid knowledge), and four transformational themes (AI technologies and the design of education, human-AI interplay, lifelong learning, and organisation of AI&ED research). The article proposes an educational ecology research agenda across macro (policy, research ecosystem, society), meso (curricula, institutions, leadership), and micro (instructors, learners, learning processes) levels. We argue for a future-oriented, critical, and inter- or multidisciplinary approach that recognises AI as a socio-technical assemblage and sustains educational values such as equity, democracy, and human dignity in postdigital societies.

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Institutions

Publication Details

Journal
Postdigital Science and Education
Published
2025-11-08
DOI
https://doi.org/10.1007/s42438-025-00602-8
Citations
5
Primary Topic
Digital Education and Society
Type
article
Field-Weighted Citation Impact
16.23
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article

A Multidisciplinary Research Agenda for Artificial Intelligence, Education, Learning, and Instruction

Maarten de Laat, Chrysi Rapanta, Johan Lundin, W. Holmes et al.
5 citations
Postdigital Science and Education
Digital Education and Society
16.23
article

A Multidisciplinary Research Agenda for Artificial Intelligence, Education, Learning, and Instruction

Maarten de Laat, Chrysi Rapanta, Johan Lundin, W. Holmes, Marcus Specht, Sabine Seufert, Sarah Hayes, Ylva Lindberg, Sanna Järvelä, Jimmy Jaldemark, Sandris Zeivots, Lars A. Svensson, Allison Littlejohn, Andreas Gegenfurtner, Justin Edwards, Roger Säljö
article en
5 citations

Abstract

Abstract Artificial Intelligence (AI) is reshaping education, learning, and instruction, yet current research in this area is fragmented, often tool-specific, and dominated by short-term perspectives. This article develops a broader research agenda for AI and Education (AI&ED), bringing together Artificial Intelligence in Education (AIED) and AI literacy within an educational ecology framing. Using a collective writing methodology, an expert panel of eleven internationally recognised scholars from various disciplines within computer and learning sciences contributed ten standalone reflections on the challenges, opportunities, and transformations of AI&ED. Two additional leading scholars provided critical commentaries to strengthen the analysis. A thematic analysis of the contributions identifies five main challenges (learning and instructional practices and curricula, access and ethics, assessment and evaluation, research capacity, and stakeholder readiness), five areas of opportunity (enhanced pedagogies, innovation in design and research, support for learning processes, critical skills, and hybrid knowledge), and four transformational themes (AI technologies and the design of education, human-AI interplay, lifelong learning, and organisation of AI&ED research). The article proposes an educational ecology research agenda across macro (policy, research ecosystem, society), meso (curricula, institutions, leadership), and micro (instructors, learners, learning processes) levels. We argue for a future-oriented, critical, and inter- or multidisciplinary approach that recognises AI as a socio-technical assemblage and sustains educational values such as equity, democracy, and human dignity in postdigital societies.

Postdigital Science and EducationVol. 7(4)
University West (SE), FernUniversität in Hagen (DE), The University of Sydney (AU), University of South Australia (AU), University of Augsburg (DE), University of St.Gallen (CH), Artificial Intelligence in Medicine (Canada) (CA), University College London (GB), Mid Sweden University (SE), Universidade Nova de Lisboa (PT), University of Gothenburg (SE), Bath Spa University (GB), Jönköping University (SE), Delft University of Technology (NL), University of Oulu (FI)
Openalex Percentile: Top 1%
Digital Education and Society
16.23
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