Using Interval-Valued Fuzzy Sets for Recommending Groups in E-Learning Systems
| Autor: | Krzysztof Myszkorowski, Danuta Zakrzewska |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Group (mathematics) Fuzzy set Joins 02 engineering and technology Recommender system computer.software_genre Fuzzy logic 020901 industrial engineering & automation Cardinality Similarity (psychology) ComputingMilieux_COMPUTERSANDEDUCATION 0202 electrical engineering electronic engineering information engineering Fuzzy number 020201 artificial intelligence & image processing Artificial intelligence business computer Natural language processing |
| Zdroj: | Computational Collective Intelligence ISBN: 9783030630065 ICCCI |
| DOI: | 10.1007/978-3-030-63007-2_7 |
| Popis: | To obtain required effects of Web-based learning process, teaching environment should be adjusted to student needs. Differentiation of the environment features can be received by grouping learners of similar preferences. Then each new student, who joins the community, should obtain the recommendation of the group of colleagues with similar characteristics. In the paper, we consider using fuzzy logic for modeling student groups. As the representation of each group, we assume fuzzy numbers connected with learner attributes ranked according to their cardinality. Recommendations for new students are determined taking into account similarity of their dominant features and the highest ranked attributes of groups. The presented approach is examined, for students described by learning style dimensions. The method is evaluated on the basis of experimental results obtained for data of different groups of real students. |
| Databáze: | OpenAIRE |
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