Implementing an Inquiry-Based Learning Model to Deepen Students’ Conceptual Understanding

  • Fida Hanum Program Study Petroleum Engineering, Islamic University Riau, Riau-28284, Indonesia
  • Alexander Sebayang Program Study Welding and Engineering Technology, Polytecnic of Medan, Medan-20155, Indonesia
  • Muhammad Ariyon Program Study Petroleum Engineering, Islamic University Riau, Riau-28284, Indonesia
  • Efrata Tarigan Program Study Conversion Energy Engineering, Polytecnic of Medan Medan-20155, Indonesia
  • Ira Herawati Program Study Conversion Energy Engineering, Polytecnic of Medan Medan-20155, Indonesia
Keywords: Inquiry-Based Learning, Welding Education, SMAW–GMAW, Conceptual Understanding

Abstract

This study examines the effectiveness of the Inquiry-Based Learning model in enhancing students’ conceptual understanding of the SMAW and GMAW welding processes, an area that remains underexplored in vocational education. The research addresses the gap between the development of procedural skills and the acquisition of conceptual reasoning by investigating whether inquiry-oriented instruction can promote deeper cognitive engagement. A quasi-experimental design was implemented involving two intact groups, with the control group receiving conventional teacher-centered instruction and the experimental group experiencing structured IBL activities. Data were collected through pretests, posttests, observations, and semi-structured interviews, and analyzed using paired-sample and independent-sample t-tests, ANCOVA, effect size calculations, and normalized gain measures. The findings reveal that the experimental group demonstrated a substantial and statistically significant improvement in conceptual understanding compared with the modest gains observed in the control group. The intervention produced a very large effect size and a medium-high normalized gain, indicating strong learning effectiveness. Students exposed to IBL were better able to analyze parameter interactions, interpret defect mechanisms, and connect theoretical principles with laboratory outcomes. Overall, the study provides strong empirical evidence that Inquiry-Based Learning is a highly effective pedagogical approach for strengthening conceptual mastery in welding technology and should be considered for broader integration into vocational curricula.

References

Aiken, C. S. (2003). The cotton plantation South since the Civil War. JHU Press.

Anthonysamy, L., Sugendran, P., Wei, L. O., & Hoon, T. S. (2024). An improved metacognitive competency framework to inculcate analytical thinking among university students. Education and Information Technologies, 29(17), 22475-22497. https://doi.org/10.1016/j.ssaho.2025.102021

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn (Vol. 11). Washington, DC: National academy press.

Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative research in psychology, 3(2), 77-101. https://doi.org/10.1191/1478088706qp063oa

Brown, E. M. (2024). Impacts of the Sequencing of Blended Virtual and Physical Laboratory Investigation on Experimental Design Skills and Conceptual Learning for IB Physics Students. University of Florida.

Buang, A. S., Bakar, M. S. A., & Rohani, M. Z. (2024). A review of trend advanced welding process and welding technology in industries. International Journal of Technical Vocational and Engineering Technology, 5(1), 133-145.

Chu, S. K. W., Reynolds, R. B., Tavares, N. J., Notari, M., & Lee, C. W. Y. (2021). 21st century skills development through inquiry-based learning from theory to practice. Springer International Publishing.

Cook, T. D., Campbell, D. T., & Shadish, W. (2002). Experimental and quasi-experimental designs for generalized causal inference (Vol. 1195). Boston, MA: Houghton Mifflin.

Dada, D., Laseinde, O. T., & Tartibu, L. (2023). Student-centered learning tool for cognitive enhancement in the learning environment. Procedia Computer Science, 217, 507-512. https://doi.org/10.1016/j.procs.2022.12.246

de Resende, A. A., & Duarte, C. A. R. (2025). The role of sustainability in the welding process: Context, technologies and challenges. Environment, Development and Sustainability, 1-28.

Field, A. E., Robertson, N. A., Wang, T., Havas, A., Ideker, T., & Adams, P. D. (2018). DNA methylation clocks in aging: categories, causes, and consequences. Molecular cell, 71(6), 882-895. https://doi.org/10.1016/j.molcel.2018.08.008

Fu, H., Tan, Y., Xia, Z., Feng, K., & Guo, X. (2024). Effects of construction workers’ safety knowledge on hazard-identification performance via eye-movement modeling examples training. Safety Science, 180, 106653. https://doi.org/10.1016/j.ssci.2024.106653

Greene, J. C. (2007). Mixed methods in social inquiry. John Wiley & Sons.

Hmelo-Silver, C. E., Duncan, R. G., & Chinn, C. A. (2007). Scaffolding and achievement in problem-based and inquiry learning: a response to Kirschner, Sweller, and. Educational psychologist, 42(2), 99-107. https://psycnet.apa.org/doi/10.1080/00461520701263368

Jalinus, N., Nabawi, R. A., & Arbi, Y. (2020). How project-based learning and direct teaching models affect teamwork and welding skills among students. Online Submission, 11(11), 85-111.

Jatavallabhula, J. K., Masubelele, F., Chikumba, S., & Rao, V. V. (2025). Artificial intelligence for quality assurance in friction stir welding–a review on opportunities and challenges. Engineering Research Express. https://doi.org/10.1088/2631-8695/adc877?urlappend=%3Futm_source%3Dresearchgate.net%26utm_medium%3Darticle

Ješková, Z., Lukáč, S., Šnajder, Ľ., Guniš, J., Klein, D., & Kireš, M. (2022). Active learning in STEM education with regard to the development of inquiry skills. Education Sciences, 12(10), 686. https://doi.org/10.3390/educsci12100686

Kilbrink, N., Axelsson, J., & Asplund, S. B. (2022). Defining critical aspects in interaction: Examples from a learning study on welding based on CAVTA. International Journal for Lesson & Learning Studies, 11(5), 16-29. https://doi.org/10.1108/ijlls-12-2021-0113

Kotsis, K. T. (2025). Inquiry-based learning in science: Mathematical reasoning’s support of critical thinking. Journal of Research in Mathematics, Science, and Technology Education, 2(1), 60-72. https://doi.org/10.70232/jrmste.v2i1.35

Kunar, S., & Mandal, G. (Eds.). (2025). Advanced Welding Technologies. John Wiley & Sons.

Lancaster, R. W. (2017). A comparison of student-centered and teacher-centered learning approaches in one alternative learning classroom environment. Arkansas State University.

Liao, C. W., Liao, H. K., Chen, B. S., Tseng, Y. J., Liao, Y. H., Wang, I. C., ... & Ko, Y. Y. (2023). Inquiry Practice Capability and Students’ Learning Effectiveness Evaluation in Strategies of Integrating Virtual Reality into Vehicle Body Electrical System Comprehensive Maintenance and Repair Services Practice: A Case Study. Electronics, 12(12), 2576. https://doi.org/10.3390/electronics12122576

Lino Alves, J., & Duarte, T. (2023). Teaching ceramic materials in mechanical engineering: An active learning experience. International Journal of Mechanical Engineering Education, 51(1), 23-46.

Liu, J., Cheng, Y., Jing, X., Liu, X., & Chen, Y. (2024). Prediction and optimization method for welding quality of components in ship construction. Scientific Reports, 14(1), 9353. https://doi.org/10.1038/s41598-024-59490-w

Lombardi, D., Shipley, T. F., & Astronomy Team, Biology Team, Chemistry Team, Engineering Team, Geography Team, Geoscience Team, and Physics Team. (2021). The curious construct of active learning. Psychological Science in the Public Interest, 22(1), 8-43. https://psycnet.apa.org/doi/10.1177/1529100620973974

Mackiewicz, J. (2022). Welding technical communication: Teaching and learning embodied knowledge. State University of New York Press.

Martin, P. P., & Graulich, N. (2023). When a machine detects student reasoning: a review of machine learning-based formative assessment of mechanistic reasoning. Chemistry Education Research and Practice, 24(2), 407-427. https://doi.org/10.1039/D2RP00287F

Mobaraki, M. (2025). Vision-based seam tracking and multi-modal defect detection in GMAW fillet welding using artificial intelligence (Doctoral dissertation, University of British Columbia).

Muzata, A. R., Singh, G., Stepanov, M. S., & Musonda, I. (2024, November). Immersive learning: A systematic literature review on transforming engineering education through virtual reality. In Virtual Worlds (Vol. 3, No. 4, pp. 480-505). MDPI. https://www.mdpi.com/2813-2084/3/4/26

Nurbavliyev, O., Kaymak, S., & Sydykov, B. (2022). The effect of active learning method on students' academic success, motivation and attitude towards mathematics. Journal of Language and Linguistic Studies, 18(2).

Nykyporets, S. S., & Chopliak, V. V. (2023). Pedagogical strategies for cognitive empowerment: approaches to enhance analytical proficiency in technical university students. Grail of Science.№ 31: 372-382. https://doi.org/10.36074/grail-of-science.15.09.2023.58

Olalerea, B. I., Gidiagbab, J. O., Fawolec, A. A., Egbokhaebhod, B. A., Ninduwezuor-Ehiobue, N., & Okparaekef, J. I. (2023). Review Of Advanced Welding And Testing For Safety In Offshore Oil And Gas. Materials & Corrosion, 4(2), 37-43. https://doi.org/10.26480/macem.02.2023.37.43

Pedaste, M., Mäeots, M., Siiman, L. A., De Jong, T., Van Riesen, S. A., Kamp, E. T., ... & Tsourlidaki, E. (2015). Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational research review, 14, 47-61. https://doi.org/10.1016/j.edurev.2015.02.003

Pei, Z. (2025). Investigating the effectiveness of inquiry-based learning (IBL) on students’ academic achievement. Research Studies in English Language Teaching and Learning, 3(3), 469-482. https://doi.org/10.62583/rseltl.v3i3.89

Prince, M., & Felder, R. (2007). The many faces of inductive teaching and learning. Journal of college science teaching, 36(5), 14.

Purohit, Y., & Parkhi, S. (2024). Optimizing Standard Work Hours in Fabrication: A Multi-Attribute Decision-Making Approach Using SMART. Library of Progress-Library Science, Information Technology & Computer, 44(3).

Riantoni, C., Rusdi, R., Maison, M., & Yelianti, U. (2024). An analysis of students' concept application in problem-solving of electrical circuits through inquiry-based learning. Indonesian Journal of Science and Mathematics Education, 7(3), 451-465. https://doi.org/10.24042/ijsme.v7i3.22874

Ruijuan, L., Srikhoa, S., & Jantharajit, N. (2023). Blending of Collaborative and Active Learning Instructional Methods to Improve Academic Performance and Self-Motivation of Vocational Students. Asian journal of education and training, 9(4), 130-135. https://doi.org/10.20448/edu.v9i4.5211

Schmidt, H. G., Rotgans, J. I., & Yew, E. H. (2011). The process of problem‐based learning: what works and why. Medical education, 45(8), 792-806. https://doi.org/10.1111/j.1365-2923.2011.04035.x

Schulz, A. (2024). Assessing student teachers’ procedural fluency and strategic competence in operating and mathematizing with natural and rational numbers. Journal of Mathematics Teacher Education, 27(6), 981-1008. https://doi.org/10.1007/s10857-023-09590-7

Shure, V., & Liljedahl, P. (2024). The use of a scriptwriting task as a window into how prospective teachers envision teacher moves for supporting student reasoning. Journal of Mathematics Teacher Education, 27(3), 411-440. https://doi.org/10.1007/s10857-023-09570-x

Published
2025-11-28
How to Cite
Hanum, F., Sebayang, A., Ariyon, M., Tarigan, E., & Herawati, I. (2025). Implementing an Inquiry-Based Learning Model to Deepen Students’ Conceptual Understanding. Journal La Edusci, 6(5), 946-960. https://doi.org/10.37899/journallaedusci.v6i5.2645