Implementing a Five-Phase Experiential-Based Deep Learning Model to Support Students' Conceptual Understanding of Force in Secondary School

Christo Vincentius Goni; Orbanus Naharia; Marianus Marianus; Kenny Setiawan Lahope; Tineke Makahinda; Darius Ladbam Lihu

doi:10.26877/lpt.v5i3.979

Authors

Christo Vincentius Goni Science Education Program, Postgraduate Program, Universitas Negeri Manado, Jl. Kampus Unima, Tonsaru, Minahasa, North Sulawesi, Indonesia Author
Orbanus Naharia Department of Biology, Universitas Negeri Manado, Jl. Kampus Unima, Tonsaru, Minahasa, North Sulawesi, Indonesia Author https://orcid.org/0000-0003-3075-1107
Marianus Marianus Department of Phyisics, Universitas Negeri Manado, Jl. Kampus Unima, Tonsaru, Minahasa, North Sulawesi, Indonesia Author
Kenny Setiawan Lahope Department of Phyisics, Universitas Negeri Manado, Jl. Kampus Unima, Tonsaru, Minahasa, North Sulawesi, Indonesia Author
Tineke Makahinda Department of Phyisics, Universitas Negeri Manado, Jl. Kampus Unima, Tonsaru, Minahasa, North Sulawesi, Indonesia Author
Darius Ladbam Lihu Deparment of Electrical Engineering Education Program, Universitas Negeri Manado, Jl. Kampus Unima, Tonsaru, Minahasa, North Sulawesi, Indonesia Author

DOI:

https://doi.org/10.26877/lpt.v5i3.979

Keywords:

Experiential-Based Deep Learning (EBDL), conceptual understanding, force, secondary school, experiential learning, reflective inquiry

Abstract

Students' conceptual understanding of force is challenged by persistent difficulties in interpreting interactions, resultant forces, and changes in motion. This study examined the classroom implementation of a five-phase Experiential-Based Deep Learning (EBDL) instructional model designed to connect firsthand observation with reflection, evidence-based explanation, and transfer. A quasi-experimental nonequivalent pretest–posttest design involved 40 eighth-grade students at one Indonesian junior secondary school, with 20 students receiving EBDL and 20 receiving Direct Instruction. Conceptual understanding was assessed using five essay items on force; expert content ratings yielded an overall Aiken's V of 0.870 after recalculation. Available group-level posttest results favored the EBDL group (M = 85.85, SD = 5.51) over the control group (M = 81.30, SD = 7.00). The reported Mann–Whitney test indicated a between-group difference (U = 124.00, Z = −2.06, p = 0.039, r = 0.326). The model's distinctive instructional contribution is its explicit progression from discrepant experiences through reflective meaning-making and force-based reasoning to contextual application and transfer. However, aggregate posttest results do not establish which cognitive process benefited most, whether individual misconceptions were corrected, or the magnitude of pretest-to-posttest change. These findings support further testing of EBDL as a structured, context-sensitive alternative for junior secondary force instruction, with stronger item-level and implementation evidence required before wider causal or generalizable claims are made.

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References

Aiken, L. R. (1985). Three coefficients for analyzing the reliability and validity of ratings. Educational and Psychological Measurement, 45(1), 131–142. https://doi.org/10.1177/0013164485451012

Andayanie, L. M., Adhantoro, M. S., Purnomo, E., & Kurniaji, G. T. (2025). Implementation of deep learning in education: Towards mindful, meaningful, and joyful learning experiences. Journal of Deep Learning, 1(1), 1–12. https://doi.org/10.23917/jdl.v1i1.11157

Banda, H. J., & Nzabahimana, J. (2021). Effect of integrating physics education technology simulations on students' conceptual understanding in physics: A review of literature. Physical Review Physics Education Research, 17(2), Article 023108. https://doi.org/10.1103/PhysRevPhysEducRes.17.023108

Biggs, J., & Tang, C. (2011). Teaching for quality learning at university (4th ed.). Open University Press.

Chrysostomou, A., Cornell, A. S., & Naylor, W. (2024). A three-year comparative study of dominant misconceptions among first-year physics students at a South African university. Physics Education, 59(1), Article 015036. https://doi.org/10.1088/1361-6552/ad14ea

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage.

Docktor, J. L., & Mestre, J. P. (2014). Synthesis of discipline-based education research in physics. Physical Review Special Topics–Physics Education Research, 10(2), Article 020119. https://doi.org/10.1103/PhysRevSTPER.10.020119

Feri, M. (2025). Penerapan pembelajaran mendalam melalui joyful, meaningful, dan mindful learning: Tinjauan literatur. IBTIDA: Jurnal Kajian Pendidikan Dasar, 5(2), 145–163. https://doi.org/10.33507/ibtida.v5i2.3495

Feriyanto, F., & Anjariyah, D. (2024). Deep learning approach through meaningful, mindful, and joyful learning: A library research. Electronic Journal of Education, Social Economics and Technology, 5(2), 208–212. https://doi.org/10.33122/ejeset.v5i2.321

Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2019). How to design and evaluate research in education (10th ed.). McGraw-Hill Education.

Fullan, M., Quinn, J., & McEachen, J. (2018). Deep learning: Engage the world, change the world. Corwin.

Hake, R. R. (1998). Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. American Journal of Physics, 66(1), 64–74. https://doi.org/10.1119/1.18809

Hattie, J. (2023). Visible learning: The sequel. Routledge.

Hestenes, D., Wells, M., & Swackhamer, G. (1992). Force concept inventory. The Physics Teacher, 30(3), 141–158. https://doi.org/10.1119/1.2343497

Koç, A., & Kanadlı, S. (2025). Effect of interactive learning environments on learning outcomes in science education: A network meta-analysis. Journal of Science Education and Technology, 34(4), 681–703. https://doi.org/10.1007/s10956-025-10202-7

Kolb, D. A. (2015). Experiential learning: Experience as the source of learning and development (2nd ed.). Pearson.

Kulgemeyer, C., & Wittwer, J. (2023). Misconceptions in physics explainer videos and the illusion of understanding: An experimental study. International Journal of Science and Mathematics Education, 21, 417–437. https://doi.org/10.1007/s10763-022-10265-7

Marjana, R., Samsudin, A., Saepuzaman, D., & Rusdiana, D. (2026). Misconception in physics learning: A systematic review of the research trend, misconception profile, diagnosis, and remediation strategies. Jurnal Pendidikan Fisika, 14(1), 240–262. https://doi.org/10.26618/7wdrxx78https://doi.org/10.26618/7wdrxx78

Marton, F., & Säljö, R. (1976). On qualitative differences in learning: I—Outcome and process. British Journal of Educational Psychology, 46(1), 4–11. https://doi.org/10.1111/j.2044-8279.1976.tb02980.x

Morris, T. H. (2020). Experiential learning: A systematic review and revision of Kolb's model. Interactive Learning Environments, 28(8), 1064–1077. https://doi.org/10.1080/10494820.2019.1570279

Nafi'ah, J., & Faruq, D. J. (2025). Conceptualizing deep learning approach in primary education: Integrating mindful, meaningful, and joyful. Journal of Educational Research and Practice, 3(2), 225–237. https://doi.org/10.70376/jerp.v3i2.384

OECD. (2023). PISA 2022 assessment and analytical framework. OECD Publishing. https://doi.org/10.1787/dfe0bf9c-en

OECD. (2023). PISA 2022 results (Volume I): The state of learning and equity in education. OECD Publishing. https://doi.org/10.1787/53f23881-en

Piaget, J. (1977). The development of thought: Equilibration of cognitive structures. Viking Press.

Rahmawati, Y., Mu'ti, A., Suyanto, S., & Herianingtyas, N. L. R. (2025). Pembelajaran mendalam: Transformasi pembelajaran menuju pendidikan bermutu. Jurnal Penelitian Kebijakan Pendidikan, 18(1). https://doi.org/10.24832/jpkp.v18i1.1281

Ramadhan, A. (2025). Pengaruh meaningful, joyful, dan mindful learning sebagai pilar deep learning terhadap hasil belajar: Literature review. Jurnal Pendidikan Tematik, 6(2), 215–225. https://doi.org/10.62159/jpt.v6i2.1736

Ratri, S. Y., Wagiran, W., Riyadi, A., Firdaus, F. M., & Delosa, J. (2026). Deep learning (Pembelajaran mendalam) dalam pendidikan Indonesia: Tinjauan sistematis teori dan praktik. Jurnal Ilmu Pendidikan dan Pembelajaran, 4(2), 176–191. https://doi.org/10.58706/jipp.v4n2.p176-191

Retnawati, H. (2017). Validitas dan reliabilitas karakteristik butir (2nd ed.). Parama Publishing.

Savinainen, A., & Scott, P. (2002). Using the Force Concept Inventory to monitor student learning and to plan teaching. Physics Education, 37(1), 53–58. https://doi.org/10.1088/0031-9120/37/1/307

Siregar, T., Fauzan, A., Yerizon, Y., & Syafriandi, S. (2025). Designing mathematics teaching through deep learning pedagogy: Toward meaningful, mindful, and joyful learning. Journal of Deep Learning, 1(2), 85–97. https://doi.org/10.23917/jdl.v1i2.11969

Syafi'i, A., & Darnanengsih. (2025). Pendekatan pembelajaran berbasis deep learning: Mindful learning, meaningful learning, dan joyful learning. Al-Mumtaz: Jurnal Manajemen Pendidikan Islam, 2(1), 1–15. https://doi.org/10.47945/al-mumtaz.v2i1.199

Taber, K. S. (2018). The use of Cronbach's alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2

Wandi, W., Mardianti, F., Suwarma, I. R., & Liliawati, W. (2023). Theory and practice of conceptual understanding in physics education: A literature review and bibliometric analysis of recent decades. Kasuari: Physics Education Journal (KPEJ), 6(2), 107–117. https://doi.org/10.37891/kpej.v6i2.483

Widagdo, T. B. (2025). Pandangan konseptual pembelajaran mendalam menuju transformasi pendidikan. Jurnal Cerdik: Jurnal Pendidikan dan Pengajaran, 4(2). https://doi.org/10.21776/ub.jcerdik.2025.004.02.05

Yardley, S., Teunissen, P. W., & Dornan, T. (2012). Experiential learning: Transforming theory into practice. Medical Teacher, 34(2), 161–164. https://doi.org/10.3109/0142159X.2012.643264