Developing IPAS Teaching Materials with an Integrated Deep Learning Approach and Character Values to Improve Elementary Students’ Critical Thinking Skills

Authors

  • Sunarsi Sunarsi Universitas Islam Negeri Alauddin Makassar, South Sulawesi, Indonesia
  • Muhammad Yaumi Universitas Islam Negeri Alauddin Makassar, South Sulawesi, Indonesia
  • Nur Akbar Rasyid Universitas Islam Negeri Alauddin Makassar, South Sulawesi, Indonesia
  • Rosdiana Rosdiana Universitas Islam Negeri Alauddin Makassar, South Sulawesi, Indonesia

DOI:

https://doi.org/10.59175/pijed.v4i2.793

Keywords:

Character Education, Critical Thinking, Elementary Education

Abstract

This study aims to develop Natural and Social Sciences (Ilmu Pengetahuan Alam dan Sosial/IPAS) teaching materials using a deep learning approach integrated with core character values to strengthen elementary students’ critical thinking skills. Employing a Research and Development design based on the ADDIE model, the study involved needs analysis through surveys of 100 teachers and 200 students across five elementary schools in Central Java, which revealed weaknesses in existing materials, particularly the lack of interactivity and moral content. The teaching materials were designed as project-based modules incorporating virtual simulations, case studies, and collaborative tasks that embed topics such as ecosystems and social dynamics with values of honesty, responsibility, and cooperation. The intervention was implemented in an experimental class of 50 fifth-grade students, compared with a control group using standard materials. Results showed a significant improvement in critical thinking, with students’ HOTS-based test scores increasing from 65% to 85% (p < 0.05, medium effect size). Qualitative observations also indicated enhanced cooperative and ethical behavior among 80% of students. Expert validation yielded a high feasibility rating (M = 4.5/5). The findings demonstrate that integrative deep learning–based IPAS materials can effectively advance both cognitive mastery and character formation, offering a holistic alternative to traditional instruction. This study contributes a validated, scalable model for strengthening critical thinking and character education, supporting broader adoption in the Indonesian national curriculum.

References

Ainillana, Q., & Louise, I. S. Y. (2024). Authentic Assessment Instrument on Redox Reactions to Assess Students’ Cognitive Skills. Journal of Science Education Research, Vol. 10, pp. 7437–7446. University of Mataram. https://doi.org/10.29303/jppipa.v10i10.8791

Abraham, J., Yame, L., Subroto, W., & Suprijono, A. (2022). Development of Local Culture-Based Textbooks (Lego-Lego) as Social Studies Learning Resources for Student Character Education in Elementary Schools. Education: Journal of Education and Learning. https://doi.org/10.62775/edukasia.v3i3.192

Aulia, S., Sundahry, & Habibie, Z. R. (2025). Active Learning with Problem-Based Learning for Problem-Solving Skills in Social and Natural Sciences. Open Academy, Vol. 10. University of Muhammadiyah Sidoarjo. https://doi.org/10.21070/acopen.10.2025.12195

Benedict, S. (2022). Deep learning for social good—an introduction. Deep Learning Technologies for Social Impact, p. 1. IOP Publishing. https://doi.org/10.1088/978-0-7503-4024-3ch1

Botes, W., & Philip, A. (2025). Research in Social Sciences and Technology Enhancing Pedagogical Development of Natural Science Teachers Through a Key Concepts in Science Project : A Social Constructivist Perspective. 191–208.

Clark, R. C., & Mayer, R. E. (2009). Multimedia Learning. Cambridge University Press.

Facione, P. A. (2011). Critical thinking: What it is and why it counts. Insight Assessment.

Fawzia, S., & Karim, A. (2024). Exploring the connection between deep learning and learning assessments: a cross-disciplinary engineering education perspective. Humanities and Social Sciences Communications, Vol. 11. Springer Science and Business Media LLC. https://doi.org/10.1057/s41599-023-02542-9

Fraser, C., Gunning, T., & Bali, A. K. (2023). Implementing and scaling authentic assessment through a pedagogical technology partnership. Ascilite Publications. Open Access Publishing Association. https://doi.org/10.14742/apubs.2023.633

Fullan, M. and A. P. (2018). The Meaning Of Educational Change. Canadian: Journal Of Education.

Guo, T. (2022). Learning from human correction for data-centric deep learning. Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.36227/techrxiv.13647974.v7

Henríquez, V. V., Rabanal, I. C., & Abásolo, J. S. (2025). Applying Kolb’s experiential learning cycle for deep learning: A systematic literature review. Social Sciences & Humanities Open, Vol. 12, p. 102096. Elsevier BV. https://doi.org/10.1016/j.ssaho.2025.102096

Jayanti, W., & Setyasto, N. (2024). Development of Kvisoft-Based Flipbook Learning Media on Learning Outcomes in Natural Sciences on the Human Circulatory System. Journal of Science Education Research. https://doi.org/10.29303/jppipa.v10i5.7025

Karim, F. (2021). Implementation of Social Sciences Learning on Natural Appearance Material to Improve Student Learning Outcomes. Proceedings of the 1st International Conference on Social Sciences, ICONESS 2021, 19 July 2021, Purwokerto, Central Java, Indonesia. EAI. https://doi.org/10.4108/eai.19-7-2021.2312482

Ministry of National Education. (2003). Law of the Republic of Indonesia Number 20 of 2003. Jakarta: Ministry of National Education.

Kemouss, H. (2023). The ADDIE pedagogical engineering model: From analysis to evaluation. Handbook of Research on Scripting, Media Coverage, and Implementation of E-Learning Training in LMS Platforms, pp. 42–70. https://doi.org/10.4018/978-1-6684-7634-5.ch003

Lickona, T. (2020). Educating for Character: How Our Schools Can Teach Respect and Responsibility. Free Press.

Marniyanti, M., Auliyani, N., Saajidah, S., Munirah, S., Putra, A. P., Zaini, M., ... Yulinda, R. (2024). Optimizing natural resource learning through the interaction of science skills and problem solving approaches. Journal of Biology Creative Education. https://doi.org/10.20527/bioco.v1i2.13929

Oskolkov, N. (2024). Deep Learning for the Life Sciences. Instats Inc. https://doi.org/10.61700/zjxxse1x3u05y1846

Pașca-Tușa, A. (2021). Teachers’ Opinion About Deep Learning. European Proceedings of Social and Behavioural Sciences, pp. 105–112. European Publisher. https://doi.org/10.15405/epsbs.2021.03.02.12

Pillai, A. S., & Tedesco, R. (2023). Introduction to Machine Learning, Deep Learning, and Natural Language Processing. Machine Learning and Deep Learning in Natural Language Processing, pp. 3–14. CRC Press. https://doi.org/10.1201/9781003296126-2

Pressley, M., & McCormick, C. B. (1995). Advanced educational psychology for educators, researchers, and policymakers. New York, USA: HarperCollins College Publishers.

Prihatina, S. A., Sukarno, S., & Triyanto, T. (2022). Internalizing the Social Care Value of Elementary School Students through Character Education. QALAMUNA: Journal of Education, Social, and Religion. https://doi.org/10.37680/qalamuna.v14i2.3417

Rukajat, A., & Krisnayansyah. (2023). Character Formation of Fifth Grade Elementary School Students in Science Learning Through the Reflective Pedagogy Paradigm (RPP) Learning Model. Journal of Science Education Research. https://doi.org/10.29303/jppipa.v9i10.5460

Salmia, Nursalam, & Bancong, H. (2024). Effectiveness of Local Wisdom-Based Independent Curriculum Teaching Modules in Improving Learning Outcomes Indonesia. Journal of Ecohumanism, 3(6), 1719–1726. https://doi.org/10.62754/joe.v3i6.4131

Stošić, A. D. S., Stanojević, D. L., Stojadinović, A. M., Djukic, T. B. M., & Mitić, I. D. T. (2025). Discovery-Based Learning and Problem-Based Learning In Social Sciences And Natural Sciences Lessons. Facta Universitatis, Series: Teaching, Learning and Teacher Education, Vol. 9, p. 113. University of Nis. https://doi.org/10.22190/futlte250226004s

Sudarmin. (2024). Development of a Pancasila Education Teaching Module with Integration of Mattabe’ Culture for Strengthening Student Character Values. Journal of Ecohumanism, 3(6), 1743–1753. https://doi.org/10.62754/joe.v3i6.4136

Sukmawati, Sudarmin, S. (2023). Development of Quality Instrument and Data Collection. Journal of Elementary School Teacher Education and Teaching, 6(1), 119–124.

Sukmawati 1 , Salmia 2, S. 3 *. (2023). Population, sample (quantitative) and selection of participants/key informants (qualitative). 7(1), 131–140.

Tam, P., Corrado, R., Eang, C., & Kim, S. (2023). Applicability of Deep Reinforcement Learning for Efficient Federated Learning in Massive IoT Communications. Applied Sciences, Vol. 13, p. 3083. MDPI AG. https://doi.org/10.3390/app13053083

Winda, N., Farhanissa, F., & Lorenza, V. (2025). Increasing Learning Creativity in Elementary Schools with a Project-Based Learning Model. LANCAH: Journal of Innovation and Trends. https://doi.org/10.35870/ljit.v3i1.3664

Yuan, L., Niu, T., & Li, Z. (2022). Study on Teaching Strategies of Scratch Programming in Elementary Schools based on Deep Learning Theory. BCP Social Sciences & Humanities. https://doi.org/10.54691/bcpssh.v20i.2398

Downloads

Published

2025-11-26

How to Cite

Sunarsi, S., Yaumi, M., Rasyid, N. A., & Rosdiana, R. (2025). Developing IPAS Teaching Materials with an Integrated Deep Learning Approach and Character Values to Improve Elementary Students’ Critical Thinking Skills. PPSDP International Journal of Education, 4(2), 254–265. https://doi.org/10.59175/pijed.v4i2.793