Reinforcement learning of pedagogical policies in adaptive and intelligent educational systems
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This presents a great opportunity for AI's applications in education for further enhancing students' learning outcomes, reducing teachers' workloads and making learning personalized, interactive and fun for teachers and students.
“This presents a great opportunity for AI’s applications in education for further enhancing students’ learning outcomes, reducing teachers’ workloads [30] and making learning personalized [64], interactive and fun [50, 53] for teachers and students.”
From Artificial Intelligence in Education (AIEd): a high-level academic and industry note 2021 (2022) · cites this paper as [30]
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References 9 · Cited by 56
Research works printed but not linked: 2
- B. Carr, I. Goldstein, Overlays: A teory of modeling for computer aided instruction, Technical report ai memo 406, AI Laboratory, Massachusetts Institute of Technology, Cambridge, MA, 1977.
- A. Iglesias, P. Martínez, R. Aler, F. Fernández, Learning pedagogical policies from few training data, in: Proceedings of the 17th European Conference on Artificial Intelligence, Workshop on Planning, Learning and Monitoring with Uncertainty and Dynamic Worlds, Riva del Garda (Italy), 2006, pp. 13-18.
- Authors
- Iglesias, A., Martínez, P., Aler, R., & Fernández, F.
- Affiliations
- Universidad Carlos III de Madrid (ES)
- Corresponding author
- Iglesias, Ana
- Venue
- Knowledge-Based Systems
- Publisher
- Elsevier BV
- Published
- 2009-05
- Volume
- 22
- Issue
- 4
- Pages
- 266-270
- ISSN
- 0950-7051 (ISSN-L)
- OpenAlex
- W2000976551
- Cited by
- 56
- References
- 9
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 3 · 2023: 6 · 2022: 6 · 2021: 7 · 2020: 11 · 2019: 3 · 2018: 1 · 2017: 1 · 2016: 1 · 2013: 1 · 2012: 3
- FWCI
- 3.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Knowledge-Based Systems (publishedVersion)
- e-Archivo (Carlos III University of Madrid) (acceptedVersion)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, other-oa)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Keywords
- reinforcement learning, simulated students, personalized learning paths, computer science education, undergraduate students
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