Research on the development of deep learning-based teaching modules with the Problem Based Learning model on electron configuration materials aims to determine the feasibility, response of students and teachers, and its effectiveness on student learning outcomes. The method used is Research and Development (R&D) with a 4-D development model which includes the define, design, develop, and disseminate stages. However, this research is only limited to the development stage which includes product development and trials limited to 12 students. Data was collected through expert validation sheets, teacher and student response questionnaires, and learning outcome tests, then analyzed descriptively quantitative and the effectiveness of the modules were analyzed using N-Gain. Based on the results of the limited trial, it was shown that the teaching modules developed were feasible and practical to use, and the N-Gain analysis showed that 75% of students were in the high category, 25% in the medium category, and there was no low category, with an average N-Gain of 0.77 (high category). This shows that deep learning-based teaching modules with the Problem Based Learning model are effective in improving student learning outcomes in electron configuration materials. ABSTRAKPenelitian pengembangan modul ajar berbasis deep learning dengan model Problem Based Learning pada materi konfigurasi elektron bertujuan untuk mengetahui kelayakan, respons peserta didik dan guru, serta efektivitasnya terhadap hasil belajar peserta didik. Metode yang digunakan yaitu Research and Development (R&D) dengan model pengembangan 4-D yang meliputi tahap define, design, develop, dan disseminate. Namun, penelitian ini hanya dibatasi sampai tahap develop yang mencakup pengembangan produk dan uji coba terbatas pada 12 peserta didik. Data dikumpulkan melalui lembar validasi ahli, angket respons guru dan peserta didik, serta tes hasil belajar, lalu dianalisis secara deskriptif kuantitatif dan efektivitas modul dianalisis menggunakan N-Gain. Berdasarkan hasil uji coba terbatas menunjukkan bahwa modul ajar yang dikembangkan layak dan praktis digunakan, serta analisis N-Gain menunjukkan bahwa 75% peserta didik berada pada kategori tinggi, 25% kategori sedang, dan tidak terdapat kategori rendah, dengan rata-rata N-Gain sebesar 0,77 (kategori tinggi). Hal ini menunjukkan bahwa modul ajar berbasis deep learning dengan model Problem Based Learning efektif dalam meningkatkan hasil belajar peserta didik pada materi konfigurasi elektron.
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