Cited by 136Intelligent Tutoring Systems and Adaptive LearningOnline Learning and AnalyticsArtificial Intelligence in Education

The Evolution of Research on Digital Education

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Dillenbourg, Pierre·2016·International Journal of Artificial Intelligence in Education

Abstract

How does AI&EdAIED today compare to 25 years ago? This paper addresses this evolution by identifying six trends. The trends are ongoing and will influence learning technologies going forward. First, the physicality of interactions and the physical space of the learner became genuine components of digital education. The frontier between the digital and the physical has faded out. Similarly, the opposition between individual and social views on cognition has been subsumed by integrated learning scenarios, which means that AIED pays more attention today to social interactions than it did at its outset. Another trend is the processing of learners’ behavioural particles, which do not carry very many semantics when considered individually, but are predictive of knowledge states when large data sets are processed with machine learning methods. The development of probabilistic models and the integration of crowdsourcing methods has produced another trend: the design of learning environments has become less deterministic than before. The notion of learning environment evolved from a rather closed box to an open ecosystem in which multiple components are distributed over multiple platforms and where multiple stakeholders interact. Among these stakeholders, it is important to notice that teachers play a more important role than before: they interact not only at the design phase (authoring) but also in the runtime phase (orchestration). These trends are not specific to AIED; they depict the evolution of learning technologies as a whole.

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  • These concerns echo critiques within constructivist and socio-emotional learning literature that caution against excessive automation.

    “These concerns echo critiques within constructivist and socio-emotional learning literature that caution against excessive automation (Dillenbourg, 2016).”

    From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Dillenbourg, 2016

  • Concerns related to creativity, emotional engagement, and socio-emotional development echo critiques within constructivist and socio-emotional learning frameworks, which warn that excessive reliance on technology may undermine relational depth and learner agency.

    “Concerns related to creativity, emotional engagement, and socio-emotional development echo critiques within constructivist and socio-emotional learning frameworks, which warn that excessive reliance on technology may undermine relational depth and learner agency (Dillenbourg, 2016).”

    From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Dillenbourg, 2016

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References 72 · Cited by 136

Authors
Dillenbourg, P.
Affiliations
École Polytechnique Fédérale de Lausanne (CH)
Corresponding author
Dillenbourg, Pierre
Venue
International Journal of Artificial Intelligence in Education
Publisher
Elsevier BV
Published
2016-06
Volume
26
Issue
2
Pages
544-560
ISSN
1560-4292 (ISSN-L)
OpenAlex
W2287976161
Cited by
136
References
72
Citations by year
2026: 14 · 2025: 13 · 2024: 25 · 2023: 16 · 2022: 21 · 2021: 11 · 2020: 16 · 2019: 10 · 2018: 5 · 2017: 3 · 2016: 2
FWCI
5.49
Type
journal article
Language
en
Open access
Locations
  • International Journal of Artificial Intelligence in Education (publishedVersion, cc-by-nc-nd)
  • Infoscience (Ecole Polytechnique Fédérale de Lausanne) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Keywords
artificial intelligence in education, adaptive intelligent tutoring systems, social interaction in learning, probabilistic models, crowdsourcing, learning environment design, teacher role in learning, educational technology

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