Pendampingan Pengembangan Perangkat Pembelajaran Sosiologi Berbasis Deep Learning berbantuan AI dengan Konteks Kearifan Lokal - Safitri, Erna Retna (MATAPPA: Jurnal Pengabdian Kepada Masyarakat, 2026)
Deep learning approach integrated with Artificial Intelligence (AI) technology needs to take into account the context of local wisdom so that it becomes a strength in instilling character values and learning relevance. However, teachers do not yet fully possess adequate digital literacy to integrate technological elements into learning. This activity is carried out to improve the knowledge and skills of Sociology teachers in developing sociology learning tools based on deep learning assisted by AI within the context of local wisdom. The activity methods include training and mentoring, using techniques such as lectures, discussions, and assignments. Questionnaire techniques were used to collect data on perceptions and evaluations of the implementation of activities. Meanwhile, test techniques were conducted by administering pre-tests and post-tests to assess the effectiveness of the training in improving teachers’ competence in understanding learning tools. The collected data were analyzed both qualitatively and quantitatively. Qualitative analysis was conducted by detailing findings from observations and interviews, while quantitative analysis involved processing test results from both pre-tests and post-tests. The analysis results indicate that this training and mentoring can effectively provide participants with an understanding of how to design and develop AI-assisted deep learning-based sociology learning tools in the context of local wisdom. The effectiveness of the training quantitatively is reflected in the increase in the average pre-test and post-test scores, with an N-gain of 0.74, categorized as high. The evaluation results also showed that participants gave a positive response to the training activities of 84.33% and did not experience difficulties during the activities, allowing them to develop learning tools that meet adequate standard requirements, with ratings ranging from good to very good in each aspect.