Comparison of Collaborative Learning Models to Improve Programming Competence
DOI:
https://doi.org/10.3991/ijoe.v17i10.24865Keywords:
Collaborative learning strategy, pre-test, post-testAbstract
The purpose of this research is how collaborative learning strategies should be arranged in three classes as Wang & Hwang model class, control class and experimental class with different treatments in Algorithm and Programming courses. Three learning strategies were tested to see students' cognitive abilities in computer programming skills. Three collaborative learning scenarios were tested, namely: 1) conventional collaborative learning 2) problem-based collaborative learning using an online environment and 3) inquiry-based collaborative learning also using an online environment. The results of the t-test with the one-way ANOVA test showed that the pretest results of the students' ability levels were not different because they had not been treated. While the results of the t-test with the posttest t-test results obtained a very significant difference in student final results, namely the control class 71.30, Wang & Hwang model class 73.0 and the experimental class 81.13. The benefit of the results of this study is that collaborative learning with an inquiry approach allows students to transfer knowledge and does not make lecturers the only source of learning
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