The Application of ChatGPT to Enhance Collaborative Coding Learning in Computer Programming Courses The Application of ChatGPT to Enhance Collaborative Coding Learning in Computer Programming Courses
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Abstract
This research aimed to: 1) investigate the application of ChatGPT in a collaborative learning model for a computer programming course, and 2) compare the learning achievement of students using ChatGPT with that of students in a traditional instructional setting. The study employed a quasi-experimental, two-group pretest-posttest design. The sample comprised 30 digital technology students from an academic institution, selected via inclusion criteria and simple random sampling. Participants were divided into a control group (n=15), which received conventional instruction, and an experimental group (n=15), which engaged in ChatGPT-integrated activities. Data were collected using a knowledge assessment (reliability = .877) and a skills evaluation form. The latter, validated by the researcher, demonstrated a content validity index between 0.67 and 1.00 and a reliability of .778. Data analysis was conducted using descriptive statistics, the Chi-square test, and an independent samples t-test.
The results revealed that: 1) Students reported a high level of satisfaction with the use of ChatGPT in the learning process. 2) Post-experiment, the experimental group's average knowledge score (= 42.35, S.D. = 10.16) than the control group (
= 48.94, S.D. = 6.39) at the .05 level (p=.03). However, the experimental group achieved significantly higher programming skill scores (
= 67.82, S.D. = 5.16) compared with the control group (
= 48.64, S.D. = 6.37) at the .05 significance level (p < .001).
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