<![CDATA[Chemistry learning at the high school level often faces challenges due to conventional methods that rely on one-way lectures and routine, meaningless exercises, which hinder students' conceptual understanding of abstract topics like acid-base. This study aimed to examine the effectiveness, student activities, and responses toward the use of a Deep Learning-based Teaching Module integrated with the Project-Based Learning (PjBL) model for eleventh-grade students at SMAN 8 Kendari on acid-base material. This quantitative research employed a quasi-experimental design with a Control Group Pretest-Posttest structure. The sample was selected using purposive sampling, consisting of 31 students in class XI.2 as the experimental group and 31 students in class XI.3 as the control group. Data were collected through cognitive pretests and posttests, learning activity observation sheets, and affective response questionnaires. The results showed a significant increase in learning outcomes; the experimental group achieved a sharp increase in posttest average score to 86.12 with a 100% classical pass rate, while the control group only reached an average of 64.35 with a 48.38% pass rate. Furthermore, the Normalized Gain (N-gain) analysis confirmed that the deep learning-based module was highly effective, yielding an average N-gain of 77.22% (Effective category) compared to the control group's 47.50% (Less Effective category). This academic success was strongly supported by an excellent student learning activity average of 91.98% and highly positive affective responses across mindful, meaningful, and joyful learning aspects.]]>
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