Impact of Artificial Intelligence Tools for Enhancing Instructional Delivery and Skill Acquisition in Building Technology in Tertiary Institutions in Rivers State
Year: 2025
Type: article
Study design: Observational Study
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.
Institution: Ignatius Ajuru University of Education
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4416723693