Impact of Artificial Intelligence Tools for Enhancing Instructional Delivery and Skill Acquisition in Building Technology in Tertiary Institutions in Rivers State


Authors : Osaji, Obiazi Augusta; Reagan Nnabio Robinso; Orji, Temple Chigozilem

Volume/Issue : Volume 10 - 2025, Issue 11 - November


Google Scholar : https://tinyurl.com/2s4bhxez

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DOI : https://doi.org/10.38124/ijisrt/25nov721

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Abstract : Despite the increasing relevance of Artificial Intelligence (AI) in education globally, its application in enhancing instructional delivery and practical skill acquisition in Building Technology programmes in Nigerian tertiary institutions remains limited and underexplored. This study investigated the impact of artificial intelligence tools for enhancing instructional delivery and skill acquisition in building technology in tertiary institutions in Rivers State. Specifically, the study investigated the impact of Intelligent Tutoring Systems on instructional delivery in Building Technology programmes and the impact of AI-powered Building Information Modelling on students’ practical skills development in Building Technology programmes in tertiary institutions in Rivers State. To that end, to research questions and two hypotheses were formulated and tested at .05 level of significance. The study adopted a descriptive survey research design, using a validated questionnaire administered to 50 Building Technology lecturers and 30 building consultants in construction firms in Rivers State. The reliability coefficient was determined using Cronbach’s Alpha, with a coefficient value of .78 and .81 for research questions 1 and 2 respectively. Data collected were analyzed using mean, standard deviation, and independent samples z- test. The findings revealed that both lecturers and students strongly agreed that Intelligent Tutoring Systems supports personalized learning, simplifies complex concepts, and bridges theory-practice gaps, while AI-powered Building Information Modelling enhances practical design competence, collaboration, and employability. No significant differences were found between the responses of lecturers and students, indicating shared positive perceptions of these AI tools. It is recommended that institutions provide adequate digital infrastructure and regular training for lecturers to ensure effective implementation of AI in Building Technology education.

Keywords : Artificial Intelligence, Intelligent Tutoring Systems, Building Information Modelling, Building Technology, Tertiary Institutions.

References :

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  3. Azhar, S., Khalfan, M., & Maqsood, T. (2012). Building Information Modeling (BIM): Now and  beyond. Australasian Journal of Construction Economics and Building, 12(4), 15–28.                https://doi.org/10.5130/AJCEB.v12i4.3032
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  7. Ogbuanya, T. C., & Usoro, A. A. (2023). Digital competence and technology integration readiness    among TVET teachers in Nigerian technical colleges. International Journal of Technology and Design Education, 33(2), 567–584. https://doi.org/10.1007/s10798-022-09728-2
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  13. Udofia, U. I., Akpan, J. P., & Etukudo, E. I. (2022). Strategies for bridging skill gaps in building technology through innovative instructional approaches. Nigerian Journal of Industrial and Technical Education, 9(1), 92–102.
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15. VanLehn, K. (2019). Intelligent tutoring systems: An overview. In F. Fischer, C. E. Hmelo-Silver, S. R. Goldman, & P. Reimann (Eds.), International Handbook of the Learning Sciences (pp. 259–271). Routledge.

Despite the increasing relevance of Artificial Intelligence (AI) in education globally, its application in enhancing instructional delivery and practical skill acquisition in Building Technology programmes in Nigerian tertiary institutions remains limited and underexplored. This study investigated the impact of artificial intelligence tools for enhancing instructional delivery and skill acquisition in building technology in tertiary institutions in Rivers State. Specifically, the study investigated the impact of Intelligent Tutoring Systems on instructional delivery in Building Technology programmes and the impact of AI-powered Building Information Modelling on students’ practical skills development in Building Technology programmes in tertiary institutions in Rivers State. To that end, to research questions and two hypotheses were formulated and tested at .05 level of significance. The study adopted a descriptive survey research design, using a validated questionnaire administered to 50 Building Technology lecturers and 30 building consultants in construction firms in Rivers State. The reliability coefficient was determined using Cronbach’s Alpha, with a coefficient value of .78 and .81 for research questions 1 and 2 respectively. Data collected were analyzed using mean, standard deviation, and independent samples z- test. The findings revealed that both lecturers and students strongly agreed that Intelligent Tutoring Systems supports personalized learning, simplifies complex concepts, and bridges theory-practice gaps, while AI-powered Building Information Modelling enhances practical design competence, collaboration, and employability. No significant differences were found between the responses of lecturers and students, indicating shared positive perceptions of these AI tools. It is recommended that institutions provide adequate digital infrastructure and regular training for lecturers to ensure effective implementation of AI in Building Technology education.

Keywords : Artificial Intelligence, Intelligent Tutoring Systems, Building Information Modelling, Building Technology, Tertiary Institutions.

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Paper Submission Last Date
30 - November - 2025

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