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Integration of artificial intelligence in industrial education: a review of current trends and future directions
Digital revolution and the resultant emergence of Industry 4.0 has driven the incorporation of Artificial intelligence (AI) in Industrial education to enhance skills development in the industry. However, there is a lack of adequate empirical evidence on the integration of Artificial intelligence in...
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| Format: | Article |
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2025
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| LEADER | 00000njm a2000000a 4500 | ||
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| 001 | oai:repository.ui.edu.ng:123456789/11474 | ||
| 042 | |a dc | ||
| 720 | |a Momoh, A. M. |e author | ||
| 720 | |a Olajide, F. O. |e author | ||
| 720 | |a Ogundipe, R. O. |e author | ||
| 720 | |a Adesina, A. D. |e author | ||
| 260 | |c 2025 | ||
| 520 | |a Digital revolution and the resultant emergence of Industry 4.0 has driven the incorporation of Artificial intelligence (AI) in Industrial education to enhance skills development in the industry. However, there is a lack of adequate empirical evidence on the integration of Artificial intelligence in industrial education. To fill this gap, this study reviewed previous studies on the adoption of AI in Industrial education and examined the frequency of occurrence of variables obtained in the studies reviewed. Relevant literature was screened and reviewed to find empirical evidence to support findings. A systematic review of 14 studies provided insights into the current applications, benefit and challenges of AI integration in industrial education. The study found that the most cited applications of AI is Adaptive and personalized learning systems, which customise workers/learners’ information based on their interaction with learning content. Other applications are augmented simulators for real-time feedback, virtual mentors, and intelligent tutoring systems which replicate real-life interaction with professionals among others. Majority of the studies found increased engagement and improved learning outcomes and skills development as benefit of AI integration in Industrial education. Other benefits are promotion of early identification of learning challenges and timely intervention and feedback, improvement in administrative efficiency and support, personalisation of learning. Notable challenges were skills and capacity gaps, lack of infrastructure and AI resources, curriculum issues and difficulty in integrating AI into current curriculum, ethical and privacy concerns among others. Based on the findings of the study, it was recommended that the skill gap should be filled with training in AI applications and use, investment in AI infrastructural development should be explored, industry collaboration and partnership in the area of needs should be considered, AI marketing and literacy should be adopted in industries, all AI intervention should be a continuing and lifelong process to ensure sustainability. | ||
| 024 | 8 | |a 3007-9756 | |
| 024 | 8 | |a ui_art_momoh_integration_2025 | |
| 024 | 8 | |a Journal of Computer, Software, and Program (JCSP) 2(2), pp. 1-9 | |
| 024 | 8 | |a https://repository.ui.edu.ng/handle/123456789/11474 | |
| 653 | |a Machine Learning | ||
| 653 | |a Technology in Industrial Education | ||
| 653 | |a Vocational Education and Training | ||
| 653 | |a Workplace Training | ||
| 245 | 0 | 0 | |a Integration of artificial intelligence in industrial education: a review of current trends and future directions |