Ravikumar, D. and Sahaai, Madona B. and Sharanya, C. and Ravichandran, V. and Lavanya, S. and Robinson Joel, M. (2025) Revolutionising Training and Vocational Education With Ongoing AI Innovation:. In: AI Smart-Enabled Architecture and Infrastructure for Higher Education. IGI Global Scientific Publishing, pp. 101-128.
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Abstract
D. Ravikumar SRM Valliammai Engineering, Chennai, India Madona B. Sahaai Vels Institute of Science, Technology, and Advanced Studies, Chennai, India https://orcid.org/0009-0002-7633-8377 C. Sharanya Sathyabama Institute of Science and Technology, Chennai, India V. Ravichandran Kings Engineering College, Chennai, India S. Lavanya KCG College of Technology, India https://orcid.org/0009-0002-9566-8785 M. Robinson Joel KCG College of Technology, India https://orcid.org/0000-0002-3030-8431 Revolutionising Training and Vocational Education With Ongoing AI Innovation
Training and vocational education are undergoing a transformation thanks to artificial intelligence (AI), which is turning conventional teaching strategies into individualised, effective, and flexible experiences. By customising information to each user's needs and facilitating real-time feedback, AI-powered solutions such as chatbots, virtual tutors, and immersive simulations are revolutionising skill development. Especially in fields that demand practical experience, these technologies improve competency-based learning, increase engagement, and close knowledge gaps.AI-driven analytics make it easier to assess student development over time, providing institutions and teachers with data on trends and results to improve curriculum. AI also facilitates scalable educational approaches, which open up vocational training to a range of people, including underprivileged communities and distant learners. However, issues including ethical concerns, digital fairness, and opposition to implementing AI in the classroom need to be addressed.
chapter 5 5 23 2025 101 128 10.4018/979-8-3693-8915-7.ch005 20250703015911 https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-8915-7.ch005 https://www.igi-global.com/viewtitle.aspx?TitleId=385029 Understanding AI technology. Joint Artificial Intelligence Center (JAIC) G.Allen 2020 24 1 The Pentagon United States AllenG. (2020). Understanding AI technology. Joint Artificial Intelligence Center (JAIC). The Pentagon United States, 2(1), 24–32. 2 10.5539/jel.v7n5p92 Belaya, V. (2018). The Use of e-Learning in Vocational Education and Training (VET): Systematization of Existing Theoretical Approaches. Journal of education and learning, 7(5), 92-101. Quantitative research methods and applications in educational leadership, policy, and administration. A. J.Bowers 2017 29 1 Educational Leadership BowersA. J. (2017). Quantitative research methods and applications in educational leadership, policy, and administration.Educational Leadership, 29(1), 29–41. 29 10.46328/ijte.36 E.Brynjolfsson 2017 The second machine age: Work, progress, and prosperity in a time of brilliant technologies BrynjolfssonE.McAfeeA. (2017). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company. J.Bughin 2018 Skill shift: Automation and the future of the workforce BughinJ.HazanE.LundS.DahlströmP.WiesingerA.SubramaniamA. (2018). Skill shift: Automation and the future of the workforce. McKinsey Global Institute. 10.1145/3579605 10.1002/9781119239086 AI and the future of skills: Fostering learning, growth, and development. M.Dixon 2020 567 4 AI & Society DixonM.HongC. S.WilsonR. (2020). AI and the future of skills: Fostering learning, growth, and development.AI & Society, 35(4), 567–576. 35 Learning about learning: AI’s role in education. J. D.Fletcher 2018 17 2 AI Magazine FletcherJ. D.TobiasS. (2018). Learning about learning: AI’s role in education.AI Magazine, 39(2), 17–28. 39 10.1016/j.techfore.2016.08.019 10.1016/j.iheduc.2016.03.003 10.1016/j.rser.2021.111963 AI-driven simulations in medical education: Bridging the gap between theory and practice. A.Gupta 2020 35 4 Journal of Educational Technology GuptaA.SrivastavaS. (2020). AI-driven simulations in medical education: Bridging the gap between theory and practice.Journal of Educational Technology, 23(4), 35–42. 23 W.Holmes 2019 Artificial intelligence in education: Promises and implications for teaching and learning HolmesW.BialikM.FadelC. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. W.Holmes 2019 Artificial intelligence in education: Promises and implications for teaching and learning HolmesW.BialikM.FadelC. (2019). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign. 10.1109/ICEARS56392.2023.10085106 10.1109/ICEARS56392.2023.10085090 G.Kipper 2021 Augmented reality: An emerging technologies guide to AR KipperG.RampollaM.SmithT. (2021). Augmented reality: An emerging technologies guide to AR. Pearson Education. 10.3102/0034654315581420 Manyika, J., Chui, M., Miremadi, M., Bughin, J., George, K., Willmott, P., & Dewhurst, M. (2017). A future that works: Automation, employment, and productivity. McKinsey Global Institute. Bessen, J. (2019). AI and Jobs: The Role of Demand. National Bureau of Economic Research. McKinsey & Company. (2020). The future of work in Europe: Automation, workforce transitions, and the shifting geography of employment. Research on improvement of” six excellence and one top-notch” talent training in safety engineering. C. H. E. N.Na 2021 91 5 Zhongguo Anquan Kexue Xuebao NaC. H. E. N.XiuyingL. I.LanZ. H. A. N. G.YanR. O. N. G. (2021). Research on improvement of” six excellence and one top-notch” talent training in safety engineering.Zhongguo Anquan Kexue Xuebao, 31(5), 91. 31 J. F.Pane 2017 Continued progress: Promising evidence on personalized learning PaneJ. F.SteinerE. D.BairdM. D.HamiltonL. S. (2017). Continued progress: Promising evidence on personalized learning. RAND Corporation. Intelligent tutoring systems for assessment in computer-based learning environments. D.Pérez-Marín 2010 21 2 Journal of Educational Technology & Society Pérez-MarínD.Pascual-NietoI. (2010). Intelligent tutoring systems for assessment in computer-based learning environments.Journal of Educational Technology & Society, 13(2), 21–28. 13 Should robots replace teachers? AI and the future of education. N.Selwyn 2019 131 2 Learning, Media and Technology SelwynN. (2019). Should robots replace teachers? AI and the future of education.Learning, Media and Technology, 44(2), 131–146. 44 10.1080/00461520.2011.611369 10.1145/3579605 Vasconcelos, H., Jörke, M., Grunde-McLaughlin, M., Gerstenberg, T., Bernstein, M. S., & Krishna, R. (2023). Explanations can reduce overreliance on ai systems during decision-making. Proceedings of the ACM on Human-Computer Interaction, 7(CSCW1), 1-38. 10.1109/ICSSIT55814.2023.10061086
Item Type: | Book Section |
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Subjects: | Computer Science Engineering > Computer Network |
Domains: | Computer Science Engineering |
Depositing User: | Mr IR Admin |
Date Deposited: | 31 Aug 2025 10:45 |
Last Modified: | 31 Aug 2025 10:45 |
URI: | https://ir.vistas.ac.in/id/eprint/10760 |