Deep Learning-Based Biology Learning with Ethnopedagogy and Local Wisdom to Support Sustainable Development Goals
DOI:
https://doi.org/10.15294/jpii.v15i1.32341Keywords:
learning models, Biology, deep learning, ethnopedagogy, local wisdom, SDGs, sustainable educationAbstract
This study aims to implement a deep learning-based Biology learning model that integrates ethnopedagogical approaches and local wisdom values to support the achievement of the Sustainable Development Goals (SDGs), specifically SDG 4 (quality education), SDG 13 (climate change), and SDG 15 (preservation of terrestrial ecosystems). The research method uses a quantitative approach with a pre-experimental design (one-group pretest-posttest) because the data are preliminary and the study is still in the research and development stage. The study subjects were students from a private high school in Bandung City, which has a rich local culture and high biodiversity. Data collection instruments included cognitive tests, affective and psychomotor observation sheets, and an ecological awareness questionnaire. The study found a significant increase in students' cognitive, affective, and psychomotor skills following the implementation of the learning model. In addition, culture-based learning succeeded in fostering meaningful connections between Biology concepts and traditional community practices. This study concludes that the implementation of the learning model shows great potential to shape students who are ecologically aware and rooted in cultural values. The integration of immersive learning and ethnopedagogy offers an innovative alternative in biology education that is locally relevant yet globally impactful. This research is still in its developmental stage and therefore uses pre-experimental methods.
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