Fuzzy rules in assessing student learning outcomes

Source of Publication

ASEE Annual Conference and Exposition, Conference Proceedings


In this paper, it is shown how fuzzy rules can be used as a modeling and evaluation tool for the achievement of the learning outcomes in information systems (IS) courses. In an outcome-based educational model (OBE), all courses in an IS college are required to clearly demonstrate the experiences that students can gain upon achieving a learning outcome. Consequently, master course syllabi describing the integration of the desired learning outcomes into IS courses are developed. The IS college provides a map between passing a given course and achieving a particular learning outcome at a certain level. Four different levels of achievements are identified: Beginning, Developmental, Achieved and Exemplary. Though, the map shows a clear relationship between courses and learning outcomes, it is not easy to define the boundaries between these four achievement levels or to combine all of the achievement results into one final assessment. In this case, the use of fuzzy logic is suitable to represent the complexities and vagueness in modeling the students learning outcomes achievements. Fuzzy membership functions are developed to model the achievement levels and define their overlaps and Fuzzy rules are generated to model the relationship between course grade (input) and the expected achievement level of learning outcomes (output). The aggregation of all learning outcome achievement levels for a sequence of courses that a student has to take provides an approximate indication of the experiences learned. Moreover, an overall analysis of all students' performances can identify the inherent strengths and weaknesses in the outcome-based educational model. Furthermore, theses results can be used by faculty members to assess the effectiveness of the integration of the learning outcomes into their courses. © American Society for Engineering Education, 2006.

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Conference Proceeding

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