A Genetic Algorithm-Based Personalized Remedial Learning System for Learning Object-Oriented Concepts of Java

Contribution: An online genetic algorithm-based remedial learning system is presented in order to strengthen students' understanding of object-oriented programming (OOP) concepts by tailoring personalized learning materials according to each student's strengths and weaknesses. Background:...

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Bibliographic Details
Published in:IEEE transactions on education Vol. 62; no. 4; pp. 237 - 245
Main Authors: Lin, Che-Chern, Liu, Zi-Cheng, Chang, Chih-Lin, Lin, Yu-Wen
Format: Journal Article
Language:English
Published: New York IEEE 01.11.2019
Institute of Electrical and Electronics Engineers, Inc
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive computer learning
Algorithms
Biological cells
Cognitive Style
College Students
Computer Assisted Instruction
Computer programming
computer science
Computer Science Education
Education
Educational materials
educational software
Electronic Learning
Foreign Countries
Genetic algorithms
High Achievement
individual differences
Individualized Instruction
Instructional Effectiveness
Instructional Materials
Java
Learning
Learning systems
Low Achievement
Machine learning
Mathematics
Object oriented programming
Programming
Programming Languages
Programming profession
Remedial Instruction
remedial learning
Students
Teaching methods
Test Construction
Taiwan
ISSN:0018-9359, 1557-9638
Online Access:Get full text
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Summary:Contribution: An online genetic algorithm-based remedial learning system is presented in order to strengthen students' understanding of object-oriented programming (OOP) concepts by tailoring personalized learning materials according to each student's strengths and weaknesses. Background: Prior studies on computer programming education have analyzed methods of learning OOP, and shown that teaching this topic is a challenge. A simple and personalized learning system for generating remedial learning materials would therefore be valuable, but had yet to be designed. Intended Outcomes: Students' grasp of OOP concepts is expected to improve through study of the tailored remedial learning materials generated by the system. Application Design: Students who had previously studied OOP were recruited to test the learning system in a two-semester pre-experiment using a one-group pre-test-post-test design. The students first took a pre-test that determined their individual strengths and weaknesses in these concepts. They then read three sets of quiz-based remedial learning materials; each set was generated by the system according to the individual student's answers in the pre-test and previous quizzes. Findings: 1) Overall, the changes between learners' pre-and post-test scores were significant; 2) Score changes for different learners (junior, senior, low-achievement, and high-achievement learners) and for different learning styles (intensive and non-intensive) were also significant; and 3) Score changes for low-achievement learners were greater than those for high-achievement learners.
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ISSN:0018-9359
1557-9638
DOI:10.1109/TE.2018.2876663