Improving Refrigerant Flow Analysis and Diagnostic Reasoning among BTLED-IA 3 Students Through a Metacognitive Diagnostic Problem-Based Learning Approach with Realia Integration

Authors

  • Shiela Marie S. Leonardo Faculty of Teacher Education, Davao Oriental State University, Philippines Author
  • John Joshua L. Bensig Faculty of Teacher Education, Davao Oriental State University, Philippines Author
  • Rojelyn L. Pangaya Faculty of Teacher Education, Davao Oriental State University, Philippines Author
  • Jepoy B. Felimon Faculty of Teacher Education, Davao Oriental State University, Philippines Author
  • Keysa O. Dijon Faculty of Teacher Education, Davao Oriental State University, Philippines Author
  • Ladely Inob Faculty of Teacher Education, Davao Oriental State University, Philippines Author

DOI:

https://doi.org/10.5281/zenodo.24155646

Keywords:

metacognitive diagnostic problem-based learning, refrigerant flow, diagnostic reasoning, realia, BTLED-Industrial Arts, action research

Abstract

Understanding refrigerant flow, pressure–temperature relationships, and component functions is a core competency in Domestic Refrigeration and Air-Conditioning (DomRAC), yet students often struggle because these processes cannot be directly observed. This classroom-based action research examined written-test performance and diagnostic task outcomes among 20 third-year Bachelor of Technology and Livelihood Education–Industrial Arts (BTLED-IA) students at Davao Oriental State University following a four-week Metacognitive Diagnostic Problem-Based Learning (MD-PBL) intervention with realia integration. Using a single-group pre-test/post-test design, the intervention combined instructor think-aloud modeling, team diagnostic rotations following a Plan, Test, Monitor, and Fix Proposal sequence with an actual air-conditioning unit, manifold gauge, and diagnostic scenario cards, a defense symposium, and reflection journals. Data were gathered through content-validated 20-item written tests and four-point analytic rubrics for scenario analysis, practical demonstration, diagnostic defense, and reflection journals, and were analyzed using means, standard deviations, percentages, a paired-samples t-test, and Cohen’s dz. Mean written-test scores increased from 10.95 (SD = 1.54; 54.75%) to 18.35 (SD = 1.04; 91.75%), a gain of 7.40 points, t(19) = 15.85, p < .001, dz = 3.54. Reported weighted rubric means were 3.78 for scenario analysis, 3.62 for demonstration, 3.38 for the defense symposium, and 3.56 for reflection journals, with planning, monitoring, and evaluation each rated 3.75. These ratings describe assessed performance rather than improvement from baseline. The written-test increase was associated with the intervention period, but the absence of a control group, unestablished test-form equivalence, and the lack of a reported reliability coefficient limit causal interpretation. The MD-PBL approach offers a structured, low-cost instructional sequence for further classroom use and evaluation in refrigeration and air-conditioning education.

Downloads

Download data is not yet available.

References

Ahmadova, K. (2026). Real objects, real language: A study of realia in second language acquisition. Euro-Global Journal of Linguistics and Language Education, 3(2), 104–111. https://egarp.lt/index.php/EGJLLE/article/view/578

Bajet, M. A., Jr., & Bajet, N. A. (2014). Development of domestic refrigerator trainer: An instructional material for beginner technicians. JPAIR Multidisciplinary Research. https://www.philair.org/index.php/jpair/article/view/272

Barrows, H. S. (1986). A taxonomy of problem-based learning methods. Medical Education, 20(6), 481–486. https://doi.org/10.1111/j.1365-2923.1986.tb01386.x

Dadivas, Y., Alojacin, C., Ledesma, J. R., & Talingting, C. A. (2025). Development of dual evaporator air conditioning with heating system trainer. Cognizance Journal, 5(7), 45–52. https://cognizancejournal.com/vol5issue7/V5I745.pdf

Ferdiansyah, Maksum, H., Rizal, F., & Ulya, R. H. (2023). Problem-based blended learning models in vocational education: Developmental research. International Journal of Information and Education Technology, 13(12), 1968–1976. https://doi.org/10.18178/ijiet.2023.13.12.2011

Fisher, D., & Frey, N. (2014). Better learning through structured teaching: A framework for the gradual release of responsibility (2nd ed.). ASCD.

Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906–911. https://doi.org/10.1037/0003-066X.34.10.906

Ismail, H. B., Sharipudin, S. S., Noorezam, M., Abu Bakar, A. A., Che Hassan, A., & Juhari, N. (2025). Students’ performance in learning air conditioning building system through experience-based learning method. International Journal of Modern Education, 7(24), 663–679. https://doi.org/10.35631/IJMOE.724047

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Prentice-Hall.

Made, A. M., & Ambiyar. (2023). The use of AC simulator problem base learning approach for control system course. In Proceedings of the 9th International Conference on Technical and Vocational Education and Training (ICTVET 2022) (pp. 3–13). Atlantis Press. https://doi.org/10.2991/978-2-38476-050-3_2

Mendoza, J. M. R. (2024). Management of experiential learning loss of Bachelor of Technical-Vocational Teacher Education students. Journal of Interdisciplinary Perspectives, 2(7), 41–58. https://doi.org/10.69569/jip.2024.0153

Mertler, C. A. (2016). Action research: Improving schools and empowering educators (5th ed.). SAGE Publications.

Rivas, S. F., Saiz, C., & Ossa, C. (2022). Metacognitive strategies and development of critical thinking in higher education. Frontiers in Psychology, 13, Article 913219. https://doi.org/10.3389/fpsyg.2022.913219

Shehadi, M. (2020, June). Refrigeration cycle educational training unit development [Paper presentation]. 2020 ASEE Virtual Annual Conference, American Society for Engineering Education. https://peer.asee.org/refrigeration-cycle-educational-training-unit-development.pdf

Stanton, J. D., Sebesta, A. J., & Dunlosky, J. (2021). Fostering metacognition to support student learning and performance. CBE—Life Sciences Education, 20(2), Article fe3. https://doi.org/10.1187/cbe.20-12-0289

Downloads

Published

2026-11-12

How to Cite

Leonardo, S. M., Bensig, J. J., Pangaya, R., Felimon, J., Dijon, K., & Inob, L. (2026). Improving Refrigerant Flow Analysis and Diagnostic Reasoning among BTLED-IA 3 Students Through a Metacognitive Diagnostic Problem-Based Learning Approach with Realia Integration. International Journal of Education, Research, and Innovation Perspectives, 2(11), 1100-1110. https://doi.org/10.5281/zenodo.24155646

Similar Articles

1-10 of 1145

You may also start an advanced similarity search for this article.