Implementing Deep Learning-Based Character Education to Foster Students' Environmental Awareness: A Policy Implementation Study in Indonesia
This study aims to analyze the implementation of deep learning-based character education in Social Studies (IPS) learning to foster students' environmental awareness and identify supporting and inhibiting factors. The study used a descriptive qualitative approach with the Edward III policy implementation framework, which includes communication, resources, disposition, and bureaucratic structure. The study was conducted at SMP Negeri 1 Muara Jawaq, West Kutai Regency. Informants were selected purposively, including the principal, IPS teachers, and students. Data were collected through semi-structured interviews, observation, and documentation, then analyzed through data condensation, data presentation, and drawing and verifying conclusions. The results showed that the implementation of deep learning-based character education was generally supported by ongoing communication at the organizational and learning levels, resource availability, implementer commitment, and coordination between school actors. Supporting factors included principal leadership, teacher competence and commitment, a conducive school culture, regulatory support, and stakeholder participation. Meanwhile, implementation still faces obstacles such as uneven teacher understanding of deep learning, suboptimal use of learning media, and limited family involvement. This implementation contributes to students' environmental awareness, as reflected in their knowledge, attitudes, and behavior. This research emphasizes the importance of integrating pedagogical approaches and policy implementation in strengthening environmental character education through social studies learning.
Authors
- 1Ratna.M, 2Bonaventura Ngarawula, 3Ana Mariani
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-15
- DOI
- https://doi.org/10.5281/zenodo.22761462
- Primary Topic
- Educational Methods and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00