Case-Based Digital Learning Media for Enhancing Troubleshooting Skills in Refrigeration and Air Conditioning Education
DOI:
https://doi.org/10.61255/jupiter.v4i3.1698Keywords:
Case-Based Learning, Digital Learning Media, Refrigeration and Air Conditioning Education, Troubleshooting Skills, Vocational EducationAbstract
Purpose: This study aimed to develop and evaluate case-based digital learning media designed to enhance students’ troubleshooting skills in refrigeration and air-conditioning education. Methods: The study employed a research and development approach using the ADDIE-ID model, comprising the Analyze, Design, Develop, Implement, Evaluate, and Integrate and Disseminate stages. The resulting web-based digital learning media, COOLTRACE (Case-Based Learning for Refrigeration Troubleshooting), was evaluated by two subject matter experts and two media experts. Practicality testing involved 20 undergraduate students, while effectiveness testing was conducted with 81 students using a one-group pretest–posttest design. The data were analyzed using descriptive statistics and normalized gain (N-Gain) analysis. Findings: COOLTRACE obtained validity scores of 97.50% from subject matter experts and 97.22% from media experts, indicating that the product met the required instructional and technical quality standards. The overall practicality score was 93.69%, demonstrating that students could access and use the media with minimal difficulty. Students’ mean scores increased from 71.46 on the pretest to 96.69 on the posttest, with a mean N-Gain of 0.84, classified as high. These findings indicate a substantial improvement in students’ troubleshooting knowledge and diagnostic decision-making following the intervention. Research Implications: COOLTRACE provides a practical digital learning resource for supporting systematic troubleshooting practice, particularly in learning contexts where opportunities for repeated fault-diagnosis activities using physical equipment are limited. Originality: This study contributes interactive web-based digital learning media that integrates authentic cases, guided diagnosis, corrective action sequencing, and immediate feedback within a systematic troubleshooting learning process.
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