A character education model based on deep learning in the teaching of Pancasila

Authors

DOI:

https://doi.org/10.21831/jc.v23i2.94534

Keywords:

character education, deep learning, learning model, Pancasila, teaching

Abstract

This study developed and tested a Deep Learning-Based Character-Strengthening Education Model for Pancasila Education at the junior high school level in Bandar Lampung City, Indonesia. Using a mixed-methods design integrated with Research and Development (R&D), the study proceeded through six stages, from preliminary participatory observation and prototype development to expert and teacher validation, quasi-experimental testing, multilevel statistical analysis, and final model refinement. Participants comprised teachers and students from junior high schools across Bandar Lampung City, selected through random sampling. The results showed that understanding of Pancasila concepts increased by 25% in the experimental group, compared with 10% in the control group, with character-strengthening indicators – tolerance, integrity, responsibility and cooperation – also registering significantly greater gains (p < 0.05). Teacher implementation quality, school environmental support and student engagement emerged as key mediators of the model’s effectiveness. The findings indicate that embedding mindful, meaningful and joyful learning principles within Pancasila Education strengthens both conceptual understanding and student character more effectively than conventional, teacher-centred approaches. The model offers a practical, empirically validated framework for character-based citizenship education in Indonesian schools and contributes to broader debates on deep-learning pedagogies in civic and moral education.

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Published

2026-10-01

How to Cite

Yanzi, H., Hariri, H., Fakhruddin, F. M., Seftriyana, E., Mentari, A., & Fernanda, F. E. (2026). A character education model based on deep learning in the teaching of Pancasila . Jurnal Civics: Media Kajian Kewarganegaraan, 23(2), 697–711. https://doi.org/10.21831/jc.v23i2.94534

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