Learning Cognitive Models Using Neural Networks
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Intelligent Tutoring Systems can adapt their behavior in real time according to the needs of individuals or to support collaborative learning.
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From Tackling climate change with machine learning (2023) · cites this paper as [124]
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Flagged first, then by citations
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Tackling climate change with machine learning
Rolnick, D., Donti, P. L., Kaack, L. H., Kochanski, K., Lacoste, A., Sankaran, K., Ross, A. S., Milojevic-Dupont, N., Jaques, N., Waldman-Brown, A., et al. (2023) · ACM Computing Surveys · doi:10.1145/3485128 · Cited by 336 · see citing works
- Authors
- Chaplot, D. S., MacLellan, C., Salakhutdinov, R., & Koedinger, K.
- Affiliations
- Carnegie Mellon University (US)
- Corresponding author
- Chaplot, Devendra Singh
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 43-56
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2809473367
- Cited by
- 11
- References
- 25
- Citations by year
- 2023: 3 · 2022: 3 · 2021: 1 · 2020: 1 · 2019: 3
- FWCI
- 0.51
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Lecture notes in computer science (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- ill-structured domains, adaptive tutoring systems, human learning, Chinese character learning, article selection
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