F. Castro, À. Nebot (Spain), and F. Mugica (Mexico)
Virtual campus; e-learning; Fuzzy inductive reasoning; Rules extraction.
. E-learning offers a new context for education where large amounts of information describing the continuum of the teaching-learning interactions are endlessly generated and ubiquitously available. But raw information by itself may be of no help to any of the e learning actors. The use of Data Mining methods to extract knowledge from this information can, therefore, be an adequate approach to follow in order to use the obtained knowledge to fit the educational proposal to the students’ needs and requirements. In this brief study we use an extension of Fuzzy Inductive Reasoning methodology to extract comprehensible, actionable and reasonable set of rules describing the students’ learning behavior. The obtained rules can be used to improve the system understanding and to provide valuable information to tutors about the course performance. The extraction rules model presented in this research is applied to a real virtual campus graduate course of the Center of Studies in Communication and Educational Technologies (CECTE, as Spanish acronym).
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