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

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.

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Publication Details

Published
2025-11-26
DOI
https://doi.org/10.38124/ijisrt/25nov721
Primary Topic
Intelligent Tutoring Systems and Adaptive Learning
Type
article
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article

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

Obiazi Augusta Osaji, Reagan Nnabio Robinso, Temple Chigozilem Orji
Intelligent Tutoring Systems and Adaptive Learning
article

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

Obiazi Augusta Osaji, Reagan Nnabio Robinso, Temple Chigozilem Orji
article en

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.

Openalex Percentile: Top 80%
Intelligent Tutoring Systems and Adaptive Learning
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