A simple and effective remedial learning system with a fuzzy expert system
Journal of Computer Assisted Learning Volume 32, Number 6, ISSN 1365-2729 Publisher: Wiley
This study aims at implementing a simple and effective remedial learning system. Based on fuzzy inference, a remedial learning material selection system is proposed for a digital logic course. Two learning concepts of the course have been used in the proposed system: number systems and combinational logic. We conducted an experiment to validate the success of the proposed system where 88 students who studied a computer-related program at a vocational high school in Taiwan participated in the experiment. The participating students came from three different types of classes. The fuzzy expert system determined the numbers of the remedial material units according to the scores of the pre-test. Based on the results of the fuzzy expert system, each student then received personalized remedial learning materials by randomly selecting problem-based learning units from a learning material repository. After reading the remedial learning materials, the students took the post-test. The experimental results reveal that the students made significant progresses after studying the remedial learning materials. Both of high-achieving students and low-achieving students made significant progresses. Moreover, all of the three types of students made significant progresses.
Lin, C.‐., Guo, K.‐. & Lin, Y.‐. (2016). A simple and effective remedial learning system with a fuzzy expert system. Journal of Computer Assisted Learning, 32(6), 647-662. Wiley.