An Application of Fuzzy Adaptive Resonance Theory to Engineering Education

In this paper, the use of Fuzzy Adaptive Resonance Theory (ART) in education data mining is demonstrated. Criterion-referenced assessment (CRA) attempts to determine students' score by comparing their achievements with a clearly stated criterion for learning outcomes. Scoring rubrics are usually used in CRA. The aim of this paper is on the use of Fuzzy ART to group students with scores from CRA, via scoring rubrics. Such approach is useful to assist instructors to establish a personalized learning system, to promote effective group learning, and to provide adaptive contents, for engineering education. In this paper, the applicability of Fuzzy ART-based approach is demonstrated with a real case study relating laboratory project assessment in Universiti Malaysia Sarawak, with positive results obtained. This paper contributes to a new application of an incremental learning neural network with no prefixed number of clusters required, i.e., Fuzzy ART, to engineering education.