<![CDATA[This research aims to develop a physics module based on deep learning on the topic of static fluids to improve the learning outcomes of eleventh-grade students. The ADDIE model (Analysis, Design, Development, Implementation, Evaluation) was used as the development framework. The module integrates three deep learning principles: mindful, meaningful, and joyful, along with the stages of understanding, applying, and reflecting. The product's quality was assessed through validity tests by material and media experts, practicality tests based on teacher and student responses, and effectiveness tests using a pretest-posttest design with N-Gain analysis. The material expert validation resulted in a score of 83.33% (very valid), while the media expert validation reached 81.4% (very valid). The practicality level based on teacher responses was 90.25% (very practical). Small group trials yielded 95%, and large group trials yielded 95.43% (both very practical). The effectiveness test showed an N-Gain value of 0.81, which falls into the high category. Based on these results, the deep learning-based physics module on static fluid material is declared valid, practical, and effective in improving student learning outcomes.]]>
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