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The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria

Anthony Chekwube Asogwa 1,
Arinzechukwu Victor Okanya 1 *
1 University of Nigeria, Nsukka, NIGERIA* Corresponding Author
Educational Point, 3(3), 2026, e187, https://doi.org/10.71176/edup/19420
Publication date: Sep 25, 2026
Research Article
Open Access Open Access
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ABSTRACT

The global construction industry is undergoing a profound transformation driven by Construction 4.0, with Artificial Intelligence (AI) emerging as a pivotal technological force. Yet a critical skills gap persists in developing nations such as Nigeria, where the pace of educational curriculum development lags significantly behind industry demands. This study examines the integration of AI into Building Technology education programs in Nigerian universities and its implications for graduate employability. Employing an explanatory sequential mixed-methods design, the quantitative phase administered surveys to 120 final-year students, 40 faculty members across four universities in South-East Nigeria, and 60 construction industry employers, to assess the current level of AI integration and its perceived relationship with employability. A subsequent qualitative phase conducted semi-structured interviews with 12 faculty heads and 12 senior industry managers to identify the institutional barriers constraining AI-driven pedagogy. The study is theoretically anchored in the Construction 4.0 Maturity Model, adapted to evaluate educational program readiness. Findings reveal that Building Technology programs currently operate at a nascent 'Initial/Ad Hoc' stage of digital maturity. Institutional constraints, including inadequate infrastructure, limited faculty expertise, and absence of strategic vision were confirmed as significant predictors of low AI adoption. Employer data further revealed that graduates with AI competencies received significantly higher employability ratings than those with traditional skills alone. These findings provide a data-driven basis for curriculum reform, targeted policy investment, and strategic university-industry collaboration to equip Nigeria's construction workforce for the digital era of construction.

KEYWORDS

construction 4.0 artificial intelligence building technology education graduate employability skills gap Nigerian universities

CITATION (APA)

Asogwa, A. C., & Okanya, A. V. (2026). The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria. Educational Point, 3(3), e187. https://doi.org/10.71176/edup/19420
Harvard
Asogwa, A. C., and Okanya, A. V. (2026). The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria. Educational Point, 3(3), e187. https://doi.org/10.71176/edup/19420
Vancouver
Asogwa AC, Okanya AV. The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria. Educational Point. 2026;3(3):e187. https://doi.org/10.71176/edup/19420
AMA
Asogwa AC, Okanya AV. The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria. Educational Point. 2026;3(3), e187. https://doi.org/10.71176/edup/19420
Chicago
Asogwa, Anthony Chekwube, and Arinzechukwu Victor Okanya. "The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria". Educational Point 2026 3 no. 3 (2026): e187. https://doi.org/10.71176/edup/19420
MLA
Asogwa, Anthony Chekwube et al. "The Role of AI Integration in Building Technology Education for Graduate Employability in Nigeria". Educational Point, vol. 3, no. 3, 2026, e187. https://doi.org/10.71176/edup/19420

REFERENCES

  1. Abioye, S. O., Oyedele, L. O., Akanbi, L., Ajayi, A., Delgado, J. M. D., Bilal, M., Akinade, O. O., & Ahmed, A. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44, Article 103299. https://doi.org/10.1016/j.jobe.2021.103299
  2. Aghimien, D. O., Aigbavboa, C. O., Oke, A. E., & Koloko, N. (2018). Digitalisation in construction industry: Construction professionals' perspective. Proceedings of International Structural Engineering and Construction, 5(2), 1-6. https://doi.org/10.14455/ISEC.res.2018.90
  3. Aliu, J., & Aigbavboa, C. O. (2020). Employers' perception of employability skills among built environment graduates. Journal of Engineering, Design and Technology, 18(4), 847-864. https://doi.org/10.1108/JEDT 06 2019 0162
  4. Barbosa, F., Woetzel, J., Mischke, J., Ribeirinho, M. J., Sridhar, M., Parsons, M., Bertram, N., & Brown, S. (2017, February 27). Reinventing construction through a productivity revolution. McKinsey Global Institute. https://www.mckinsey.com/capabilities/operations/our-insights/reinventing-construction-through-a-productivity-revolution
  5. Borrmann, A., König, M., Koch, C., & Beetz, J. (Eds.). (2018). Building information modeling: Technology foundations and industry practice. Springer. https://doi.org/10.1007/978-3-319-92862-3
  6. Chukwu, D. U., & Anaele, E. O. (2025). Understanding sustainability consciousness and construction sustainable behaviours of preservice teachers of Building Technology Education programme: The moderating role of subjective norms. Discover Education, 4, Article 476. https://doi.org/10.1007/s44217-025-00829-4
  7. Chukwu, D. U., Omeh, C. B., & Ayanwale, M. A. (2026). Predicting sustainable behaviours on building construction sites in Nigeria using the value-belief-norm theory. Discover Sustainability, 7, Article 255. https://doi.org/10.1007/s43621-026-02606-1
  8. Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). Sage Publications. https://collegepublishing.sagepub.com/products/designing-and-conducting-mixed-methods-research-3-241842
  9. Das, P., Perera, S., Senaratne, S., & Osei-Kyei, R. (2023). Paving the way for industry 4.0 maturity of construction enterprises: A state of the art review. Engineering, Construction and Architectural Management, 30(10), 4665–4694. https://doi.org/10.1108/ECAM-11-2021-1001
  10. Draucker, C. B., Rawl, S. M., Vode, E., & Carter-Harris, L. (2020). Integration through connecting in explanatory sequential mixed method studies. Western Journal of Nursing Research, 42(12), 1137–1147. https://doi.org/10.1177/0193945920914647
  11. Ebekozien, A., Aigbavboa, C. O., & Samsurijan, M. S. (2024). Appraising alternative building technologies adoption in low-cost housing provision to achieving Sustainable Development Goal 11. Engineering, Construction and Architectural Management, 31(13), 41–58. https://doi.org/10.1108/ECAM-06-2023-0538
  12. Etikan, I., Musa, S. A., & Alkassim, R. S. (2015). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
  13. Forcael, E., Ferrari, I., Opazo-Vega, A., & Pulido-Arcas, J. A. (2020). Construction 4.0: A literature review. Sustainability, 12 (22), Article 9755. https://doi.org/10.3390/su12229755
  14. Fraser, P., Moultrie, J., & Gregory, M. (2002). The use of maturity models/grids as a tool in assessing product development capability. In Proceedings of the 2002 IEEE International Engineering Management Conference (IEMC 2002) (pp. 244–249). IEEE. https://doi.org/10.1109/IEMC.2002.1038431
  15. George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference (4th ed.). Allyn & Bacon.
  16. Guadu, A., Dibekulu, D., & Menberu, A. W. (2025). Artificial intelligence in African higher education: Uses, misuses, and ethical dilemmas. Advances in Artificial Intelligence and Machine Learning, 5(3), 4196–4221. https://doi.org/10.54364/AAIML.2025.53234
  17. Han, Y., Du, H., & Zhao, C. (2025). Development of a digital transformation maturity model for the construction industry. Engineering, Construction and Architectural Management, 32(7), 4384–4412. https://doi.org/10.1108/ECAM-10-2023-1009
  18. Heidenwolf, O., & Szabó, I. (2024). Justification of Construction 4.0 maturity model with a case study of a data-driven façade company. In Proceedings of the 41st International Symposium on Automation and Robotics in Construction (ISARC 2024) (pp. 1272-1279). International Association for Automation and Robotics in Construction. https://doi.org/10.22260/isarc2024/0164
  19. Jäkel, J.-I., & Klemt-Albert, K. (2023). Construction 4.0 maturity tool with ontology development methodology for organisations. In Proceedings of the 2023 Creative Construction Conference (CCC) (pp. 272–281). https://doi.org/10.3311/CCC2023-033
  20. Jäkel, J.-I., Fischerkeller, F., Oberhoff, T., & Klemt-Albert, K. (2024). Development of a maturity model for the digital transformation of companies in the context of construction industry 4.0. Journal of Information Technology in Construction, 29, 778–809. https://doi.org/10.36680/j.itcon.2024.034
  21. Kalu, Y. O., Odoh, C. E., Kalu, S. U., Ukoji, C. K., Okorie, S. A. (2026). The virtual constructor: AI-powered simulation for enhancing experiential learning in building technology education. International Journal of Research and Innovation in Social Science, 10(26), 2636-2643. https://doi.org/10.47772/IJRISS.2026.1026EDU0215
  22. Muhammad, S. Y., & Bulama, K. H. (2024). Technical skills required for enhancing the employability of building technology education undergraduates in degree awarding institutions in North-East Nigeria. International Journal of Multidisciplinary Research in Science, Technology and Innovation, 2(1), 1–12. https://www.ijmrsti.com/2024/03/09/technical-skills-required-for-enhancing-the-employability-of-building-technology-education-undergraduates-in-degree-awarding-institutions-in-north-east-nigeria/
  23. National Universities Commission. (2023). Core curriculum and minimum academic standards for Nigerian universities (CCMAS). https://shorturl.at/LQ9oX
  24. Ngalburgi, S. A. (2024). Challenges of practical skills acquisition among building trade students of federal polytechnics in North Eastern Nigeria. International Journal of Innovative Research in Technology, Basic and Applied Sciences, 7(1), 55 74. https://internationalpolicybrief.org/wp-content/uploads/2024/04/ARTICLE-7.pdf
  25. Nnaji, C., & Karakhan, A. A. (2020). Technologies for safety and health management in construction: Current use, implementation benefits and limitations, and adoption barriers. Journal of Building Engineering, 29, Article 101212. https://doi.org/10.1016/j.jobe.2020.101212
  26. Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
  27. Nwakile, T. C., Ugwuoke, C. U., Okadi, A., Ali, C. C., Nnadi, H. S., Ikehi, M., Ekwueme, S. U., Okanya, V. A., Eya, C. C., & Emeka, O. (2025). Retrospective assessment of academic and psychological readiness of final-year technical and vocational education students in Nigeria after the 2022 ASUU strike. Discover Education, 4, Article 409. https://doi.org/10.1007/s44217-025-00893-w
  28. Nwibe, K. J., & Bakare, J. (2022). Self-efficacy belief and entrepreneurial intention of electrical/electronics technology education students in South-Eastern Nigerian universities: A moderated mediation analyses. Journal of Global Entrepreneurship Research, 12, 131-141. https://doi.org/10.1007/s40497-022-00318-0
  29. Nwibe, K. J., & Ogbuanya, T. C. (2024). Emotional intelligence and entrepreneurial intention among university undergraduates in Nigeria: Exploring the mediating roles of self-efficacy domains. Journal of Innovation and Entrepreneurship, 13, Article 13. https://doi.org/10.1186/s13731-024-00367-7
  30. Nwobodo-Anyadiegwu, E. N., & Okanya, V. A. (2026). Impact of student-centred learning on motivation and learning outcomes among engineering and building technology students in a Nigerian university. Discover Education, 5, Article 135. https://doi.org/10.1007/s44217-026-01231-4
  31. Ogunrinde, O., Idrissi Gartoumi, K., Osuizugbo, I. C., Hatamleh, M. T., & Oyeyipo, O. (2026). Construction 4.0 technologies for advancing quality management processes. Engineering, Construction and Architectural Management, 33(9), 7395-7414. https://doi.org/10.1108/ECAM-01-2025-0007
  32. Okanya, A. V., Asogwa, J. O., & Vincent, D. A. (2025). Enhancing graduate employability through the introduction of artificial intelligence in building technology education in Nigerian universities. Vocational and Technical Education Journal, 5(1), 183–197. https://votej.com.ng/index.php/votej/article/view/39
  33. Okanya, V. A., Chukwu, D. U., & Ojo, S. A. (2019). Strategies to promote improved construction practices in building construction industry: A case study of building contractors in Nsukka LGA of Enugu State. International Journal of Vocational Education and Training Research, 5(2), 53–58. https://doi.org/10.11648/j.ijvetr.20190502.13
  34. Okereke, G. K., & Okanya, V. A. (2024). Achieving sustainable housing for low and middle-income earners. In M. Noguchi (Ed.), Prefabricated construction for sustainability and mass customization (pp. 1–17). IntechOpen. https://doi.org/10.5772/intechopen.111870
  35. Okereke, G. K., Okanya, V. A., Okereke, J., Umar, L., Yakubu, A., Ezugwu, C., & Kontei, E. (2024). Perception of building technology lecturers on the adoption of wearable technologies for worker safety in Nigeria's building construction sector. Global Journal of Information Technology: Emerging Technologies, 14(2), 79–88. https://doi.org/10.18844/gjit.v14i2.9591
  36. Okonkwo, C., Lan, R., Awolusi, I., & Cai, J. (2025). Integrating artificial intelligence into construction education: Assessing the impact on students' perception of knowledge, confidence, and relevance to career. Proceedings of the 2025 ASEE Gulf Southwest Annual Conference. Proceedings of the 2025 ASEE Gulf-Southwest Annual Conference The University of Texas at Arlington, Arlington, TX. https://peer.asee.org/integrating-artificial-intelligence-into-construction-education-assessing-the-impact-on-students-perception-of-knowledge-confidence-and-relevance-to-career
  37. Olagunju, A. R., Kayode, I. A., & Olagunju, M. I. (2025). Factors influencing the employability of built environment graduates in Nigeria's construction sector. International Journal of Builders in Academia, 1(1), 102–1115. http://www.ijba.org.ng/index.php/ijba/article/download/58/11
  38. Onatere-Ubrurhe, J. O., Chinyio, E., & Georgakis, P. (2025). Enhancing building technology education through the integration of virtual reality. International Journal of Education, Learning and Development, 13(1), 65–84. https://doi.org/10.37745/ijeld.2013/vol13n16584
  39. Orji, C. T., & Ogbuanya, T. C. (2022). Mediating roles of ability beliefs and intrinsic motivation in PBL and engagement in practical skills relations among electrical/electronic education undergraduate. Innovations in Education and Teaching International, 59(3), 326–336. https://doi.org/10.1080/14703297.2020.1813188
  40. Pan, Y., & Zhang, L. (2021). Roles of artificial intelligence in construction engineering and management: A critical review and future trends. Automation in Construction, 122, Article 103517. https://doi.org/10.1016/j.autcon.2020.103517
  41. Perrier, N., Bled, A., Bourgault, M., Cousin, N., Danjou, C., Pellerin, R., & Roland, T. (2024). Construction 4.0: A comparative analysis of research and practice. Journal of Information Technology in Construction, 29, 16–39. https://doi.org/10.36680/j.itcon.2024.002
  42. Rane, N. L. (2023) Integrating building information modelling (BIM) and artificial intelligence (AI) for smart construction schedule, cost, quality, and safety management: Challenges and opportunities. SSRN. http://dx.doi.org/10.2139/ssrn.4616055
  43. Rane, N. L. (2024). Roles and challenges of ChatGPT and similar generative artificial intelligence in architectural engineering. International Journal of Artificial Intelligence and Machine Learning, 4(1), 22-47. https://doi.org/10.2139/ssrn.4607767
  44. Sawhney, A., Riley, M., & Irizarry, J. (Eds.). (2020). Construction 4.0: An innovation platform for the built environment. Routledge. https://doi.org/10.1201/9780429398100
  45. Szeszulski, J., Schaefers, A., de Mello, G. D., Gardner, J., George, A., MacMillan Uribe, A. L., Rethorst, C. D., Seguin Fowler, R., & Xin, L. (2025). Design and methodology of a cluster randomized factorial trial to optimize implementation strategies for the Healthy School Recognized Campus initiative. Frontiers in Public Health, 13, Article 1652485. https://doi.org/10.3389/fpubh.2025.1652485
  46. Tapeh, A. T. G., & Naser, M. Z. (2023). Artificial intelligence, machine learning, and deep learning in structural engineering: A scientometrics review of trends and best practices. Archives of Computational Methods in Engineering, 30(1), 115–159. https://doi.org/10.1007/s11831-022-09793-w
  47. Toyin, J. O., & Mewomo, M. C. (2023). An investigation of barriers to the application of building information modelling in Nigeria. Journal of Engineering, Design and Technology, 21(2), 442-468. https://doi.org/10.1108/JEDT-10-2021-0594
  48. Toyin, J. O., & Mewomo, M. C. (2023). Assessing the innovative skills and competencies required of construction management graduates. Organization, Technology and Management in Construction, 15(1), 90–106. https://doi.org/10.2478/otmcj-2023-0002
  49. Tuma Neto, A. A., & Araujo de Souza Junior, A. (2022). Industry 4.0 innovations in construction: Proposal of a maturity model. International Journal for Innovation Education and Research, 10(9), 418-436. https://doi.org/10.31686/ijier.vol10.iss9.3892
  50. Turkyilmaz, A. H., Polat, G., & Gurkan, A. (2024). Application of Construction 4.0 technologies: Empirical findings from the Turkish construction industry. Journal of Information Technology in Construction, 29, 179–197. https://doi.org/10.36680/j.itcon.2024.009
  51. Ukala, C. C., & Iheukwumere, S. C. (2025). Integrating artificial intelligence (AI) in technical and vocational education and training in public (TVET) institutions in Abia State, Nigeria: Bridging skills gaps for future workforce. International Journal of Scientific Research in Education, 18(1), 35–43. https://www.ijsre.com.ng/assets/vol.18-ukala-iheukwumere.pdf
  52. UNESCO. (2025, July 20). The cultural cost of AI in Africa's education systems. https://www.unesco.org/en/articles/cultural-cost-ai-africas-education-systems
  53. Zabala-Vargas, S., Jaimes-Quintanilla, M., & Jimenez-Barrera, M.H. (2023). Big data, data science, and artificial intelligence for project management in the architecture, engineering, and construction industry: A systematic review. Buildings, 13(12), Article 2944. https://doi.org/10.3390/buildings13122944

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