Pengembangan Modul Ajar Diffrensiasi Berbasis Deep Learning Untuk Meningkatkan Hasil Belajar Pada Materi Sistem Periodik Unsur Di SMAN 1 Sangatta Selatan
DOI:
https://doi.org/10.55606/jcsr-politama.v4i4.6485Keywords:
Deep Learning, Differentiated Instruction, Learning Outcomes, Periodic Table of Elements, Teaching ModuleAbstract
This study aimed to develop a differentiated teaching module based on the Deep Learning approach for the topic of the Periodic Table of Elements and to determine its development process, validity, practicality, and effectiveness in improving students' learning outcomes. The research employed a Research and Development (R&D) method using the 4-D development model, which consists of the Define, Design, Develop, and Disseminate stages. However, this study was limited to the Develop stage. The trial subjects were students of Class X-6. Data were collected using validation sheets to evaluate the module's validity, teacher and student response questionnaires to assess its practicality, and learning achievement tests to measure its effectiveness. The collected data were analyzed using descriptive qualitative and quantitative methods. The results showed that the development process began with an analysis of students' characteristics, including learning readiness, interests, and learning styles, followed by the integration of differentiated instruction elements (content, process, and product) with the principles of the Deep Learning approach (mindful, meaningful, and joyful learning). The teaching module was categorized as highly valid based on the evaluations of media, language, and subject-matter experts. It was also considered highly practical, as indicated by positive responses from teachers 94% and students, with practicality scores of 88%. Furthermore, the module proved to be effective in significantly improving students' learning outcomes, as demonstrated by the increase in the average post-test score, an N-Gain value of 0.74, which falls into the high category, and an effect size of 3.53, indicating a very large effect. These findings suggest that the differentiated teaching module based on the Deep Learning approach effectively enhances students' learning outcomes. In conclusion, the differentiated teaching module based on the Deep Learning approach for the topic of the Periodic Table of Elements is valid, practical, and effective for use in chemistry learning.
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