Inovasi Pembelajaran Bioteknologi Melalui Deep Learning Berbasis Lingkungan di MTsN Pangandaran - Erlina Erlina (CV. Intake Pustaka, 2025)
This study aims to enhance students’ conceptual understanding and scientific process skills through the implementation of environment-based Deep Learning in biotechnology learning. The classroom action research employed the Kemmis and McTaggart model, conducted in two cycles at MTsN 3 Pangandaran involving 24 ninth-grade students. Each cycle consisted of planning, action, observation, and reflection stages. The learning activities engaged students in producing tape (fermented cassava) as a local biotechnological product with probiotic potential. Data were collected through participatory observation, product assessment, motivation questionnaires, and student reflection journals, then analyzed qualitatively using triangulation techniques. The results indicated significant improvement in students’ engagement, scientific reasoning, and understanding of fermentation and probiotic mechanisms. Ninety-two percent of the student groups produced tape of optimal quality, while 87% demonstrated the ability to explain the relationship between fermentation processes and probiotic health benefits. Furthermore, the learning process fostered creativity, contextual thinking, and awareness of local potential. In conclusion, the implementation of environment-based Deep Learning effectively promotes contextual, meaningful, and science-literate biotechnology learning that integrates local resources with 21st-century competencies.