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TechMecha Robosphere
A Global Journal on Intelligent Automation, Mechatronics, Robotics, Engineering, Management, and Sustainable Innovation
ISSN Online: 3155-6019
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Original Research
Exploring Construction Management Education in the Philippines: A Scientometric Investigation on the Impact of Industry-Academia Collaboration
TechMecha Robosphere
ISSN Online: 3155-6019
Volume 1 | Issue 1 | 2026 | 1 – 14
Jethro Jhames A. Jose 1, ORCID No. 0009 - 0005 - 5040 - 0154
Arvin R. De La Cruz 2, PhD, ORCID No. 0000 - 0001- 7325- 5301
1Master of Science in Construction Management , Polytechnic University of the Philippines, Sta. Mesa, Manila, Philippines
2Program Chair, PhD & MS Computer Engineering, Polytechnic University of the Philippines, Sta. Mesa, Manila, Philippines
Article History:
Initial submission: 27 March 2026
First decision: 30 March 2026
Revision received: 05 May 2026
Accepted for publication: 18 June 2026
Online release: 01 July 2026
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Abstract
This study examines the structure and recent evolution of construction management education (CME) research from 2020 to 2025 through a Scientometric and text-mining approach. It aims to identify publication productivity, institutional participation, distribution across sources and titles, keyword prominence, and latent thematic patterns that define the current CME knowledge landscape. Bibliographic records were retrieved from an indexed scholarly database using construction- and education-related search terms, then screened, cleaned, and normalized to retain relevant metadata, abstracts, keywords, affiliations, and citation counts. Descriptive Scientometric analyses were conducted to determine annual publication trends, leading institutions, and major publication venues, while Latent Dirichlet Allocation (LDA) was applied to the cleaned text corpus to uncover deeper conceptual structures. Results indicate a strong increase in publication output from 2020 to 2024, suggesting that CME research is undergoing a period of growth and consolidation, whereas the lower 2025 count is likely due to partial-year indexing effects. Institutional contributions are moderately concentrated, with a few universities leading output, while dissemination remains distributed across several interdisciplinary journals and proceedings. Keyword and topic-model results show that the field is anchored on the education-management-construction triad and is increasingly shaped by digital platforms, data-driven methods, quality assurance, and project-based learning. Overall, the findings suggest that CME is evolving toward a hybrid competency model that integrates traditional construction management foundations with analytics, technological fluency, and evidence-based decision-making. The study offers useful insights for curriculum innovation, institutional collaboration, and future research directions in construction management education.
Keywords: construction management education; scientometric analysis; text mining; Latent Dirichlet Allocation; digital transformation
Cite this article
APA (7th edition)
Jose, J. J. A., & De La Cruz, A. R. (2026). Exploring construction management education in the Philippines: A scientometric investigation on the impact of industry–academia collaboration. TechMecha RoboSphere, 1(1), 1–14. https://doi.org/10.62718/vmca.tech-robo.1.1.SC-0126-009.
Author contributions
Jethro Jhames A. Jose: Conceptualization, Data curation, Formal analysis, Methodology, Project administration, Resources, Software, Writing – original draft, Writing – review & editing
Arvin Dela Cruz: Supervision, Validation.
Funding
This research received no external funding.
Conflict of interest
The authors declare no conflict of interest.
Institutional ethics review statement
Ethical approval was obtained from the Polytechnic University of the Philippines-Open University Research Ethics Committee with reference code OUSREC 1001-0028.
Data availability statement
The dataset will be available upon request from the corresponding author of this study.
Declaration of generative AI use/assistance
AI-assisted language editing was conducted using ChatGPT and Grammarly. The authors carefully reviewed and approved all revisions generated through these tools. Their use was limited to improving grammar, clarity, and the organization of complex sentence structures. All substantive content, ideas, and analyses in the paper remain original.
Acknowledgement
The author expresses sincere gratitude to Polytechnic University of the Philippines–Open University for providing the academic environment and support necessary for the completion of this study. The author also acknowledges the valuable support of family, colleagues, and peers whose encouragement contributed to the successful completion of this work. Above all, the author is deeply thankful for the strength and perseverance that made this study possible.
Publisher’s disclaimer
The views expressed in this article are those of the authors and do not necessarily reflect the views of the publisher. The publisher disclaims any responsibility for errors or omissions.