Cocea, Mihaela and Magoulas, George D. (2012) Learning task-related strategies from user data through clustering. In: UNSPECIFIED (ed.) International Conference on Advanced Learning Technologies. New York, USA: Institute of Electrical and Electronics Engineers, pp. 400-404. ISBN 9781467316422.
Abstract
In exploratory learning environments, learners can use different strategies to solve the same problem. Not all these strategies, however, are known to the teacher and, even if they were, they need considerable time and effort to introduce them in the knowledge base. In this paper we propose a learning mechanism that extracts strategies from user data and presents them to the teacher for further authoring. To this end, a clustering approach is used in which the strategies of learners are grouped into clusters and the teacher is presented with a representative strategy for each cluster. The teacher can then decide whether to store the proposed strategies or to author them further. This approach allows populating the knowledge base using user data, thus saving authoring time for the teacher.
Metadata
| Item Type: | Book Section |
|---|---|
| Keyword(s) / Subject(s): | vectors, tiles, resource management, image color analysis, knowledge based systems, clustering algorithms, educational institutions, exploratory learning environments, clustering, learning from user data |
| School: | Birkbeck Faculties and Schools > Faculty of Science > School of Computing and Mathematical Sciences |
| Research Centres and Institutes: | Birkbeck Knowledge Lab |
| Depositing User: | Sarah Hall |
| Date Deposited: | 18 Jul 2013 11:05 |
| Last Modified: | 09 Aug 2023 12:33 |
| URI: | https://eprints.bbk.ac.uk/id/eprint/7717 |
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