Fuzzy Inference System Based on a Model of Affective Cognitive Criteria for English Learning Achievement
Criterion-referenced assessment (CRA) employs a specifically-defined set of criteria or standards that can guide teachers to assess students grade by comparing students’ learning score with the pre-specified standards. However, the use of CRA is considered incomplete as most of the criteria are merely based on knowledge domains. Meanwhile, affective factors also need to be considered in the assessment to describe students’ complete attributes. Nonetheless, measuring affective factors is not as straightforward task as measuring cognitive factors because affective descriptions is often represented in descriptive verbal terms. In this study, affective factors and cognitive factors based on CRA are combined as a model for assessment of students’ learning. A questionnaire is developed to collect student affective attributes. A novel fuzzy inference system (FIS) is proposed to infer student achievement in English learning based on CRA. The FIS method was applied to analyze the data collected from students studying English as a second language. The result indicates the usefulness of the FIS based on CRA as a basis to assess student English learning by considering both affective and cognitive factors.
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