Pengaruh Pendekatan Deep Learning Berbasis Etnosains terhadap Hasil Belajar Siswa - Huriana Huriana; Akhmad Sukri; Agus Muliadi; Sri Nopita Primawati (Biocaster : Jurnal Kajian Biologi, 2026)
Students' low level of understanding regarding biological concepts may stem from a lack of connection between learning materials and real-life contexts or local wisdom within their immediate environment. Therefore, instructional innovation is needed to link scientific concepts with local knowledge through an ethnoscience-based deep learning approach. This study aims to determine the effect of an ethnoscience-based deep learning approach on student learning outcomes in biology. A quantitative approach was employed using a quasi-experimental method with a pretest-posttest control group design. The sample consisted of 34 Grade X students from SMA Islam Al-Azhar NW Kayangan (2025/2026 academic year), selected via total sampling and divided into an experimental group (18 students) and a control group (16 students). An essay-based learning outcome test served as the research instrument, and data analysis was conducted using a one-way ANOVA test. The results indicate a difference in learning outcomes between the experimental and control groups following the intervention. The experimental group's mean pretest score was 53.68, rising to 68.16 in the posttest, while the control group's mean pretest score was 32.81, rising to 56.88 in the posttest. The one-way ANOVA test yielded a significance value of 0.000 (< 0.05); thus, the null hypothesis (H0) was rejected and the alternative hypothesis (H1) was accepted. This demonstrates that the ethnoscience-based deep learning approach has a significant impact on students' biology learning outcomes. The novelty of this research lies in the application of a deep learning approach integrated with ethnoscience rooted in local wisdom as a contextual and meaningful biology learning strategy for students.