<![CDATA[Education on climate change has become a national priority in response to the increasing impacts of global warming and the low level of students’ competencies and environmental awareness. This study aimed to analyse the effect of a project-based deep learning approach on students’ competencies and environmental care attitudes through a Deep Learning–Carbon Emission Project (DL-CEP). This study employed a mixed-methods approach with a one-group pretest–posttest design involving 36 tenth-grade students at SMA Juara Wirautama, Indramayu, Indonesia. Research instruments included competency tests, environmental care attitude questionnaires, project assessment rubrics, observations, and interviews with the science teacher. Quantitative data were analysed using paired-samples t-tests and Wilcoxon tests, along with effect size calculations, while qualitative data were analysed thematically. The results revealed a significant improvement in students’ competencies, with mean scores increasing from 65.07 to 89.93 (Z = −5.014; p < 0.05) and an effect size of 0.836, categorised as a very large effect. Environmental care attitudes also showed a significant increase, from a mean score of 66 to 79, based on the paired sample t-test results (t = −9.372; p < 0.05) with a Cohen’s d value of 1.562, indicating a very large effect. Qualitative findings supported the quantitative results by demonstrating the emergence of mindful, meaningful, and joyful learning experiences. It can be concluded that the DL-CEP approach is highly effective in enhancing students’ competencies and environmental care attitudes and has strong potential as an interdisciplinary cocurricular learning model to support sustainable education. Keywords: carbon emissions project; climate change education; deep learning; student competence, environmental care attitude.]]>
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