Indri Rezkyana. AM, Febby
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PENYUSUNAN PERANGKAT PEMBELAJARAN SEJARAH LOKAL BERBASIS DEEP LEARNING BAGI MGMP SEJARAH KOTA PEKANBARU Fikri, Asyrul; Isjoni, Isjoni; Bunari , Bunari; Indri Rezkyana. AM, Febby
Estungkara: Jurnal Pengabdian Pendidikan Sejarah Vol. 4 No. 3 (2025): Estungkaran: Jurnal Pengabdian Masyarakat
Publisher : Pendidikan Sejarah FKIP Universitas JAMBI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22437/est.v4i3.51792

Abstract

Deep learning-based learning is an approach that emphasizes in-depth understanding, interrelation between concepts, and critical and reflective thinking skills in the learning process. This approach is in line with the spirit of an independent curriculum that encourages meaningful and student-centered learning. The presence of learning tools that are systematically designed and based on deep learning approaches in the learning process can increase student engagement and understanding in depth. The use of appropriate learning tools not only helps teachers in delivering material effectively, but also encourages students to think critically, reflectively, and actively engage in the learning process. This Workshop is designed to provide an in-depth understanding of the concept of deep learning-based learning, which is a learning model that not only focuses on basic knowledge aspects, but also encourages learners to analyze, evaluate, create, and reflect on contextual learning. The method used in this community service project was implemented in Pekanbaru City, involving 50 history teachers who are members of the History MGMP. The community service activity was divided into three phases: preparation, implementation, and evaluation. The materials presented include: concepts and basic principles of Deep Learning in basic education, strategies to design learning outcomes that encourage deep thinking, the preparation of teaching modules that integrate the values of Pancasila student profiles, and the practice of preparing lesson plans and formative assessments based on deep learning.