Predicting Students’ Course Performance Based on Learners’ Characteristics via Fuzzy Modelling Approach
Frequent assessment allows instructors to ensure students have met the course learning objectives. Due to lack of instructor-student interaction, most of the assessment feedbacks and early interventions are not carried out in the large class size. This study is to proposes a new way of assessing s...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
INSIGHT - Indonesian Society for Knowledge and Human Development
2019
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/28697/1/Predicting%20Students%E2%80%99%20Course%20Performance%20Based%20on%20Learners%E2%80%99%20-%20Copy.pdf http://ir.unimas.my/id/eprint/28697/ http://ijaseit.insightsociety.org/ |
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| Summary: | Frequent assessment allows instructors to ensure students have met the course learning objectives. Due to lack of
instructor-student interaction, most of the assessment feedbacks and early interventions are not carried out in the large class size.
This study is to proposes a new way of assessing student course performance using a fuzzy modeling approach. The typical steps in
designing a fuzzy expert system include specifying the problem, determining linguistic variables, defining fuzzy sets as well as
obtaining and constructing fuzzy rules is deployed. An educational expert is interviewed to define the relationship between the factors
and student course performance. These steps help to determine the range of fuzzy sets and fuzzy rules in fuzzy reasoning. After the
fuzzy assessing system has been built, it is used to compute the course performances of the students. The subject expert is asked to
validate and verify system performance. Findings show that the developed system provides a faster and more effective way for
instructors to assess the course performances of students in large class sizes. However, in this study, the system is developed based on
150 historical student data and only a total of six factors related to course performance are considered. It is expected that considering
more historical student data and adding more factors as the variables help to increase the accuracy of the system. |
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