A Simple and Effective Remedial Learning System with a Fuzzy Expert System

Saved in:
Bibliographic Details
Title: A Simple and Effective Remedial Learning System with a Fuzzy Expert System
Language: English
Authors: Lin, C.-C, Guo, K.-H, Lin, Y.-C
Source: Journal of Computer Assisted Learning. Dec 2016 32(6):647-662.
Availability: Wiley-Blackwell. 350 Main Street, Malden, MA 02148. Tel: 800-835-6770; Tel: 781-388-8598; Fax: 781-388-8232; e-mail: cs-journals@wiley.com; Web site: http://www.wiley.com/WileyCDA
Peer Reviewed: Y
Page Count: 16
Publication Date: 2016
Document Type: Journal Articles
Reports - Research
Education Level: High Schools
Secondary Education
Descriptors: Remedial Instruction, Artificial Intelligence, Intelligent Tutoring Systems, Electronic Learning, Vocational High Schools, High School Students, Foreign Countries, Problem Based Learning, Instructional Materials, Pretests Posttests, Instructional Effectiveness, High Achievement, Low Achievement
Geographic Terms: Taiwan
DOI: 10.1111/jcal.12160
ISSN: 0266-4909
Abstract: 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.
Abstractor: As Provided
Entry Date: 2016
Accession Number: EJ1119381
Database: ERIC
Description
Abstract: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.
ISSN:0266-4909
DOI:10.1111/jcal.12160