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Enhancing Fuzzy Inference System-Based Criterion-Referenced Assessment with a Similarity Reasoning Technique
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Author(s): Tze Ling Jee (University Malaysia Sarawak, Malaysia), Kai Meng Tay (University Malaysia Sarawak, Malaysia)and Chee Khoon Ng (University Malaysia Sarawak, Malaysia)
Copyright: 2012
Pages: 26
Source title:
Outcome-Based Science, Technology, Engineering, and Mathematics Education: Innovative Practices
Source Author(s)/Editor(s): Khairiyah Mohd Yusof (Universiti Teknologi Malaysia, Malaysia), Naziha Ahmad Azli (Universiti Teknologi Malaysia, Malaysia), Azlina Mohd Kosnin (Universiti Teknologi Malaysia, Malaysia), Sharifah Kamilah Syed Yusof (Universiti Teknologi Malaysia, Malaysia)and Yudariah Mohammad Yusof (Universiti Teknologi Malaysia, Malaysia)
DOI: 10.4018/978-1-4666-1809-1.ch015
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Abstract
A search in the literature reveals that the use of fuzzy inference system (FIS) in criterion-referenced assessment (CRA) is not new. However, literature describing how an FIS-based CRA can be implemented in practice is scarce. Besides, for an FIS-based CRA, a large set of fuzzy rules is required and it is a rigorous work in obtaining a full set of rules. The aim of this chapter is to propose an FIS-based CRA procedure that incorporated with a rule selection and a similarity reasoning technique, i.e., analogical reasoning (AR) technique, as a solution for this problem. AR considers an antecedent with an unknown consequent as an observation, and it deduces a conclusion (as a prediction of the consequent) for the observation based on the incomplete fuzzy rule base. A case study conducted in Universiti Malaysia Sarawak is further reported.
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