Analysis of Deep Learning Approach to Improve Learning Effectiveness in Electric Motor Installation for Vocational Students

Abstract

This study aims to analyze the implementation of the deep learning approach in improving the effectiveness of learning in the Electrical Motor Installation subject for grade XI TITL students. This research employed a qualitative approach with a descriptive method. Data were collected through observation, interviews, and documentation. The research subjects consisted of teachers and students involved in the learning process. Data analysis was conducted through data reduction, data display, and conclusion drawing. The results showed that the implementation of the deep learning approach, which includes three main aspects mindful learning, meaningful learning, and joyful learning was able to improve the quality of the learning process. In the mindful learning stage, students demonstrated increased focus and learning readiness. In the meaningful learning stage, students found it easier to understand concepts through hands-on practice and were able to relate theory to its application. Meanwhile, in the joyful learning stage, there was an increase in student participation, collaboration, and learning motivation. Overall, students were not only able to complete practical tasks but also understood the working principles of electrical circuits and were capable of analyzing emerging problems. In conclusion, the deep learning approach is effective in improving the quality of learning in Electrical Motor Installation, both in terms of the learning process and student engagement. This approach also contributes to the development of critical thinking skills and problem-solving abilities relevant to vocational education.