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内蒙古自治区呼和浩特市赛罕区大学西街235号 邮编: 010021
作者机构:Natl Kaohsiung Normal Univ Dept Software Engn & Management Kaohsiung Taiwan Natl Sun Yat Sen Univ Kaohsiung Taiwan Natl Cheng Kung Univ Tainan Taiwan Natl Kaohsiung Normal Univ Kaohsiung Taiwan
出 版 物:《IEEE TRANSACTIONS ON EDUCATION》 (IEEE教育汇刊)
年 卷 期:2019年第62卷第4期
页 面:237-245页
核心收录:
学科分类:0401[教育学-教育学] 0808[工学-电气工程] 08[工学]
主 题:Java Genetic algorithms Learning systems Biological cells Programming profession Education Adaptive computer learning computer science educational software genetic algorithms individual differences object-oriented programming remedial learning
摘 要: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.