THE EFFECT OF AN INTEGRATED STEM APPROACH WITH DEEP LEARNING ON STUDENTS' CRITICAL THINKING ABILITIES IN RENEWABLE ENERGY MATERIAL

Ahmad Rifqi Syadi, Erina Hertanti

Abstract


Critical thinking is an essential 21st-century competency that remains insufficiently developed in physics learning, particularly in renewable energy topics. Integrating the Science, Technology, Engineering, and Mathematics (STEM) approach with Deep Learning is considered a promising strategy to address this issue. This study aimed to analyze the effect of the STEM-integrated Deep Learning approach on students' critical thinking abilities`, determine the improvement in these abilities, and describe students' responses to the learning approach. A quantitative method with a quasi-experimental design using the Nonequivalent Control Group Design was employed. The sample consisted of 68 tenth-grade students, including 34 students in the experimental class and 34 in the control class, selected through purposive sampling. Data were collected using an essay-based critical thinking test and a student response questionnaire and analyzed using normality and homogeneity tests, an Independent Samples t-test, and N-gain analysis. The results indicated a significant effect of the STEM-integrated Deep Learning approach on students' critical thinking abilities (p = 0.001). The experimental class achieved a higher average N-gain score (0.56, moderate) than the control class (0.46, moderate). Students also showed positive responses (89%). Therefore, the STEM-integrated Deep Learning approach is effective in improving students' critical thinking abilities in renewable energy learning.

Keywords


critical thinking; STEM; Deep Learning; renewable energy; physics education

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References


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DOI: https://doi.org/10.29100/eduproxima.v8i3.11259

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