Policy Analysis and Effectiveness of Deep Learning–Based Project Learning for Green Entrepreneurship
DOI:
https://doi.org/10.59211/mjpjetl.v4i1.234Keywords:
Deep Learning, Project-Based Learning, Green Entrepreneurship, Vocational Education, Sustainability.Abstract
The integration of Deep Learning approaches into Project-Based Learning in vocational education, particularly for developing Green Entrepreneurship Competency, remains underexplored. This study aimed to measure the effectiveness of Deep Learning-based Project-Based Learning in improving the Green Entrepreneurship Competency of Grade XI–XII students in the Computer and Network Engineering Department at SMK Negeri 1 Kabupaten Sorong. A quantitative approach with a one-group pre-test and post-test design was employed, involving 184 students and 64 teachers. Data were analyzed using paired sample t-tests, Pearson correlation, and multiple linear regression. The findings revealed a significant improvement in Green Entrepreneurship Competency, with the average score increasing from 53.97% in the pre-test to 72.60% in the post-test (gain = 18.63; p < 0.001; Cohen’s d = 0.83). The Green Entrepreneurial Intention dimension showed the highest improvement, while Ecological Awareness demonstrated the strongest correlation with the quality of implementation. Regression analysis identified the quality of Deep Learning-based Project-Based Learning implementation as the strongest predictor of Green Entrepreneurship Competency (β = 0.412; R² = 0.621). This learning model proved effective and is recommended for sustainable implementation with adequate support in terms of media, teacher training, and institutional policies..
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