Volume: 3 Issue: Special Issue 1
Year: 2026, Page: 122-125, Doi: https://doi.org/10.70372/jeltp.v3.sp1.17
The integration of Artificial Intelligence (AI) into interdisciplinary engineering curricula is highly relevant in modern higher education. AI aligns education with Industry 4.0 by equipping students with skills in automation, data analytics, and smart systems. It promotes collaboration across civil, mechanical, electrical, IT, and chemical domains, enabling projects such as smart cities, autonomous robots, and healthcare IoT. AI enhances research through predictive modelling, simulations, and optimizations while fostering employability and entrepreneurship. Furthermore, AI supports personalized learning and adaptive assessments. This article presents a case study from AISSMS College of Engineering, illustrating the integration of AI, IoT, TRIZ and other professional student chapters to align postgraduate curricula with industry needs, making curriculum National Education Policy (NEP 2020) compliant. It also addresses challenges, ethical considerations, and governance policies for responsible adoption. Findings indicate that AI, when implemented with structured oversight, enhances industry readiness, academic quality, and holistic student development.
Keywords: Artificial Intelligence (AI), Curriculum Innovation, Industry-Relevant Content, Employability, Higher Education, TRIZ, IoT, IUCEE, Professional Student Chapters
[1] O. Zawacki-Richter, T. Marín, M. Bond, and F. Gouverneur, “Systematic review of research on artificial intelligence applications in higher education – where are the educators?,” Int. J. Educ. Technol. High. Educ., vol. 20, no. 1, pp. 1–27, 2023.
[2] U. Sivarajah, D. Irani, and V. Kumar, “A comprehensive overview of AI and ML in educational pedagogy: 21 years (2000–2021) of research indexed in Scopus database,” Soc. Sci. & Humanit. Open, vol. 8, no. 1, p. 100560, 2023.
[3] A. Alam, P. Patel, and N. Singh, “Artificial intelligence-assisted curriculum development: Innovations in designing educational content for the 21st century learner,” J. High. Educ. Theory Pract., vol. 24, no. 4, pp. 15–28, 2024.
[4] S. Muneer, F. Akhtar, and R. Hussain, “Artificial intelligence’s opportunities and challenges in engineering curricular design: A combined review and focus group study,” Societies, vol. 14, no. 6, p. 89, 2024.
[5] R. Shankar, M. O’Neill, and T. Mitchell, “Developing a model for AI across the curriculum: Transforming the higher education landscape via innovation in AI literacy,” Comput. & Educ.: AI, vol. 4, p. 100104, 2023.
[6] M. Bond, A. A. García, and P. Holenko Dlab, “Design and assessment of AI-based learning tools in higher education: A systematic review,” Int. J. Educ. Technol. High. Educ., vol. 22, no. 1, pp. 1–22, 2025.
[7] Vanitha, P., Banu, N. M. M., and Dhanaselvam, P. S. “Productive learning: CDIO project-based learning (PBL) assessment strategy for microcontroller course in engineering curriculum”. Journal of Engineering Education Transformations, Vol. 39 No.1, 2025.
M. V. Waghmare, S. H. Wankhade, D. S. Bormane.The Integration of Artificial Intelligence into Interdisciplinary Engineering Curricula and Industry Readiness. Journal of Effective Teaching and Learning Practices. 2026;3(Sp1):122-125