Analisis Implementasi Deep Learning Mata Pelajaran PJOK : Analisis Implementasi Deep Learning Mata Pelajaran PJOK - Sahiddannasa Sahiddannasa; Ani Kurniawati; Asep Angga Permadi (Jurnal Porkes, 2026)
This study was motivated by the fact that PJOK learning tends to be instructional and focused on technical skills, thus failing to develop students' deep understanding and critical thinking skills. The purpose of this study was to analyze the implementation of the deep learning model in PJOK subjects at SMK PGRI Bungbulang. The method used was descriptive quantitative with 34 students selected through purposive sampling as subjects. The instrument consisted of a 46-item questionnaire that had been tested for validity and reliability, grouped into eight dimensions of deep learning. Data analysis used descriptive statistics, normality tests, and One-Sample T-Test hypothesis testing using SPSS version 25. The results showed that the implementation of deep learning in PJOK learning was in the high category with an average score of 193.03 (84.36%). All items had a significance value of 0.000 (p < 0.05) with a t-value of 12.324 to 46.278. The Character and Learning Independence dimensions were the strongest contributors (Mean = 25.47; t = 16.891). The research conclusion proves that the implementation of deep learning has a very significant effect on PJOK learning, improving high-level cognitive aspects, active engagement, meaningful understanding, as well as students' character and learning independence. The deep learning model is effectively applied in PJOK to create a holistic and relevant learning experience.