Adaptive Modelling of Users' Strategies in Exploratory Learning Using Case-Based Reasoning

Abstract. In exploratory learning environments, learners can use different strategies to solve a problem. To the designer or teacher, however, not all these strategies are known in advance and, even if they were, introducing them in the knowledge base would involve considerable time and effort. In previous work, we have proposed a case-based knowledge representation, modelling the learners behaviour when constructing/exploring models through simple cases and sequences of cases, called strategies. In this paper, we enhance this approach with adaptive mechanisms for expanding the knowledge base. These mechanisms allow to identify and store inefficient cases, i.e. cases that pose additional difficulty to students in their learning process, and to gradually enrich the knowledge base by detecting and adding new strategies. Key words: user modelling, knowledge base adaptation, exploratory learning environments, case-based reasoning

• Type: Journal
• Year: 2010
• Where: KES
• Authors: Mihaela Cocea, Sergio Gutiérrez Santos, George D. Magoulas
• Keywords: Case-based Knowledge Representation, Information Technology, KES 2010, Knowledge Base, Strategies