Validation of Deep Learning-Based Instructional Materials for Pancasila Education: Integrating Digital Citizenship Skills and Moral Intelligence
Nisrina Nurul Insani, Marshelayanti Mohamad Razali, Aim Abdul Karim, Kokom Komalasari, Rahmat, Muhammad Arief Rakhman, Suriaman, Laila Puspita Anggraeni

Universitas Pendidikan Indonesia, Universiti Pendidikan Sultan Idris

Abstract

Pancasila Education plays an important role in cultivating civic values and national identity among Indonesian students. However, existing instructional materials used in senior high schools still emphasize ideological knowledge and moral values without sufficiently integrating digital citizenship competencies. This condition creates a gap between traditional civic education and the realities of students^ participation in digital environments. In the digital era, instructional materials must not only transmit civic values but also foster responsible digital behavior, ethical awareness, and critical engagement. Therefore, strengthening instructional materials that integrate deep learning, digital citizenship, and moral intelligence is essential. This study aims to validate deep learning based instructional materials for Pancasila Education that integrate digital citizenship skills and moral intelligence for senior high school students in Bandung, West Java, Indonesia. The research employed a Research and Development (R&D) design focusing on the product validation stage. Source triangulation involved seven sources through two mechanisms: four expert validators who assessed the materials using structured validation instruments and three Focus Group Discussion (FGD) participants representing the Provincial Pancasila Education Teachers^ Association (MGMP), a practitioner-author, and research promotors. The validation instrument evaluated four dimensions: book text quality, moral intelligence integration, digital citizenship skills, and the deep learning approach. Quantitative data were analyzed using a five-category feasibility rubric, while qualitative data were coded using NVivo 15. The results categorized the instructional materials as feasible, with an overall score of 71.50%. The deep learning dimension achieved the highest score (75.00%), followed by book text quality and moral intelligence (each 72.50%). Digital citizenship integration obtained the lowest score (65.00%), indicating the need for further strengthening. NVivo coding confirmed that digital citizenship was the main area for improvement. Source triangulation showed convergence across all seven sources, indicating that the materials are feasible for refinement rather than redevelopment before field implementation.

Keywords: instructional materials validation- deep learning- Pancasila Education- moral intelligence digital citizenship-

Topic: STEM Education