Recommender Systems for Technology Enhanced Learning Research Trends and Applications /
As an area, Technology Enhanced Learning (TEL) aims to design, develop and test socio-technical innovations that will support and enhance learning practices of individuals and organizations. Information retrieval is a pivotal activity in TEL and the deployment of recommender systems has attracted in...
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| Other Authors: | , , , |
| Format: | Electronic eBook |
| Language: | English |
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New York, NY :
Springer New York : Imprint: Springer,
2014.
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| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- Collaborative Filtering Recommendation of Educational Content in Social Environments utilizing Sentiment Analysis Techniques
- Towards automated evaluation of learning resources inside repositories
- Linked Data and the Social Web as facilitators for TEL recommender systems in research and practice
- The Learning Registry: Applying Social Metadata for Learning Resource Recommendations
- A Framework for Personalised Learning-Plan Recommendations in Game-Based Learning
- An approach for an Affective Educational Recommendation Model
- The Case for Preference-Inconsistent Recommendations
- Further Thoughts on Context-Aware Paper Recommendations for Education
- Towards a Social Trust-aware Recommender for Teachers
- ALEF: from Application to Platform for Adaptive Collaborative Learning
- Two Recommending Strategies to enhance Online Presence in Personal Learning Environments
- Recommendations from Heterogeneous Sources in a Technology Enhanced Learning Ecosystem
- COCOON CORE: CO-Author Recommendations based on Betweenness Centrality and Interest Similarity
- Scientific Recommendations to Enhance Scholarly Awareness and Foster Collaboration.
