Leveraging AI to Transform Rail Higher Education:Opportunities, Challenges, and the Path Forward

Abstract

The rapid digital transformation, an aging workforce, and persistent skills shortages in rail industry has highlighted the need for railway higher education program that remains relevant and aligned with industry requirement. This paper explores the integration of Artificial Intelligence (AI) in higher education, specifically within the context of rail education. This paper proposes developing of an evaluation tool for railway programmes' curricula that integrates AI-driven methods. Employing data-driven analytics and predictive modelling, the tool will examine curriculum relevance, skills coverage, and the integration of emerging technologies. These results will underscore the potential of AI to revolutionise curriculum design and evaluation, bridging the gap between university provision and industry demands.

Publication DOI: https://doi.org/10.1109/EDCC-C66476.2025.00044
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
College of Engineering & Physical Sciences
Additional Information: Copyright ©2025 IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Event Title: 20th European Dependable Computing Conference Companion, EDCC-C 2025
Event Type: Other
Event Dates: 2025-04-08 - 2025-04-11
Uncontrolled Keywords: AI in education,curriculum evaluation,rail higher education,tool development,Computational Theory and Mathematics,Artificial Intelligence,Computer Vision and Pattern Recognition,Electrical and Electronic Engineering
ISBN: 9798331537425, 9798331537418
Last Modified: 29 Oct 2025 17:40
Date Deposited: 13 Mar 2025 15:16
Full Text Link:
Related URLs: https://ieeexpl ... cument/11144860 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Conference contribution
Published Date: 2025-09-03
Published Online Date: 2025-09-03
Accepted Date: 2025-02-14
Authors: Shinde, Prachiti
Marinov, Marin (ORCID Profile 0000-0003-1449-7436)
Hadeed, Reem (ORCID Profile 0009-0007-3907-5201)

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Access Restriction: Restricted to Repository staff only until 3 September 2026.

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