Semantic Technologies in e-Learning
Author:
Affiliation:
1. Department of Information Technologies, Vilnius Gediminas Technical University, Vilnius, Lithuania
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3227609.3227669
Reference26 articles.
1. Design a personalized e-learning system based on item response theory and artificial neural network approach
2. Learning style Identifier: Improving the precision of learning style identification through computational intelligence algorithms
3. Semantic Web Technologies for supporting learning assessment
4. Static neural network process models: Considerations and case studies
5. Learning and Teaching Styles in Engineering;Felder Richard M.;Education. Eng. Educ. 78,2002
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