Self-evolving engineering curricula: A Reinforcement Learning architecture to align academic training with industry demands in developing countries

Authors

DOI:

https://doi.org/10.65269/993p4h33

Keywords:

Reinforcement Learning, Self-Evolving Systems, Artificial Intelligence in Education, Employability, Skills-to-Market Alignment

Abstract

Engineering education in developing countries faces a widening gap between academic curricula and labor market needs, as traditional revision processes are too slow to keep pace with rapid technological change. This paper proposes a conceptual, self-evolving curricular architecture based on RL, formalizing academic programs as a Markov Decision Process in which curricular adjustments are actions, academic and employability indicators are state variables, and a multi-criteria reward function balances performance, employability, industrial alignment, and budget constraints. An Explainable AI layer and a human-governed workflow support institutional trust. As a proof-of-concept contribution, no deployment, dataset, or simulation has been carried out; the paper instead formalizes the problem, details the architecture, and outlines a validation protocol for future empirical work.

Article Metrics

300 Views
256 Downloads
0 Citations Citation count provided by Crossref.

Readers by Country Unique usage is based on OJS/COUNTER-style deduplication and should not be interpreted as a count of identifiable people.

38 countries
  • Canada 87
  • United States 23
  • Cameroon 20
  • Brazil 17
  • India 8
  • Mexico 7
  • Türkiye 6
  • China 5
  • Albania 4
  • Argentina 4

Unique usage is based on OJS/COUNTER-style deduplication and should not be interpreted as a count of identifiable people.

About these metrics

Views: Article landing-page/abstract views reported by OJS usage statistics.

Downloads: Full-text file accesses reported by OJS usage statistics.

Citations: Citation count provided by Crossref.

Readers by Country: Unique usage is based on OJS/COUNTER-style deduplication and should not be interpreted as a count of identifiable people.

Author Biographies

  • Leslie Erika Kouamouo Ndangang, Université de Douala

    Leslie Erika KOUAMOUO NDANGANG is a PhD candidate in Computer Science at the University of Douala, Cameroon, and a member of the Intelligent and Sustainable Decision-Making (ISDM) research team.

  • Justin Moskolaï Ngossaha, Université de Douala

    Prof. Justin Moskolaï Ngossaha is an Associate Professor in Department of Mathematics and Computer Science at the University of Douala, Cameroon, and leads the Intelligent and Sustainable Decision-Making (ISDM) research team.

  • Adolphe Ayissi Etémé, IUT of Ngaoundéré, Cameroun

    Prof. Adolphe Ayissi Etémé, PhD, is a Lecturer at the University Institute of Technology (IUT), University of Ngaoundéré, Cameroon. He has also taught at several other universities and higher education institutions, including IAI, ENS, FALSH, ESSTIC, and IUCSJP. In addition, he serves as a Studies Officer and is responsible for the Information Technology Directorate at the Presidency of the Republic of Cameroon.

References

David Mhlanga. “Digital transformation of education, the limitations and prospects of introducing the fourth industrial revolution asynchronous online learning in emerging markets”. In: Discover education 3.1 (2024), p. 32. DOI: https://doi.org/10.1007/s44217-024-00115-9

Ahmed Ayad. Réussir le transfert technologique: Guide pour les pays en développement. Chihab, 2025.

Rahma Sahali. “L’innovation en Algérie: quelle formation dans les écoles d’ingénieurs pour quelles innovations?” PhD thesis. HESAM Université; École Nationale Supérieure de Management (ENSM), 2022.

Vui-Yee Koon, Sin Kit Yeng, Chong Soon Meng, and Poon Wai Chuen. “Transformative trends and challenges: Navigating disruptive innovation in higher education through bibliometric insights”. In: Innovations in Education and Teaching International 63.2 (2026), pp. 356–369. DOI: https://doi.org/10.1080/14703297.2025.2469080

Hunter Hughes. “Education Technology & Digital Upskilling in Emerging Economies: Utilizing Innovation for Growth & Development”. In: Available at SSRN 5719702 (2025). DOI: https://doi.org/10.2139/ssrn.5719702

Amando Jr Singun. “Unveiling the barriers to digital transformation in higher education institutions: a systematic literature review”. In: Discover Education 4.1 (2025), p. 37. DOI: https://doi.org/10.1007/s44217-025-00430-9

Nelson Sizwe Madonsela. “Aligning Education and Workforce Training with Industry Needs: A Perspective on Human Capital Development”. In: Proceedings of the First Australian International Conference on Industrial Engineering and Operations Management. 2022, pp. 20–21.

R Satheeskumar, Ch V Satyanarayana, Talatoti Ratna Kumar, and M Suresh. “AI-Driven alignment of educational programs with industry needs and emerging skillsets [J]”. In: International Journal of Modern Education and Computer Science 17.3 (2025), pp. 15–28. DOI: https://doi.org/10.5815/ijmecs.2025.03.02

Fabrizio Stasolla, Antonio Zullo, Roberto Maniglio, Anna Passaro, Mariacarla Di Gioia, Enza Curcio, and Elvira Martini. “Deep learning and reinforcement learning for assessing and enhancing academic performance in university students: A scoping review”. In: AI 6.2 (2025), p. 40. DOI: https://doi.org/10.3390/ai6020040

Rama Yusvana. “Addressing the skills gap in technical and vocational training for sustainable socio-economic growth and development”. In: International Journal of Research and Innovation in Social Science 8.IIIS (2025), pp. 6311–6325. DOI: https://doi.org/10.47772/IJRISS.2024.803474S

Md Jahangir Alam, SM Ali Reza, Keiichi Ogawa, and Abu Hossain Muhammad Ahsan. “Sustainable employment for vocational education and training graduates: the case of future skills matching in Bangladesh”. In: International Journal of Training Research 22.3 (2024), pp. 266–288. DOI: https://doi.org/10.1080/14480220.2024.2308224

Zinan Sharrad Arsha. An Undergraduate Internship/Project on Industry Academia Linkage and the Identification of Skills Gaps of the Graduating Engineering Students at Tertiary Level Education. Tech. rep. Independent University, Bangladesh, 2023.

Md Abu Issa Gazi, Md Kazi Hafizur Rahman, Mohd Faizal Yusof, Abdullah Al Masud, Md Aminul Islam, Abdul Rahman bin S Senathirajah, and Md Alamgir Hossain. “Mediating role of entrepreneurial intention on the relationship between entrepreneurship education and employability: a study on university students from a developing country”. In: Cogent Business & Management 11.1 (2024), p. 2294514. DOI: https://doi.org/10.1080/23311975.2023.2294514

Lin Xu, Jingxiao Zhang, Yiying Ding, Gangzhu Sun, Wei Zhang, Simon P Philbin, and Brian HW Guo. “Assessing the impact of digital education and the role of the big data analytics course to enhance the skills and employability of engineering students”. In: Frontiers in Psychology 13 (2022), p. 974574. DOI: https://doi.org/10.3389/fpsyg.2022.974574

Prince Dacosta Anaman, Deborah Morpkorpkor Zottor, and Julius Kumi Egyir. “Infrastructural challenges and student academic performance: Evidence from a developing nation”. In: International Journal of Innovative Science and Research Technology 7.11 (2022), pp. 1189–1200.

Boahemaa Brenya. “Higher education in emergency situation: Blended learning prospects and challenges for educators in the developing countries”. In: Journal of Applied Research in Higher Education 16.4 (2024), pp. 1015–1028. DOI: https://doi.org/10.1108/JARHE-01-2023-0044

Victor Olugbenga Ayoko, Thankgod Peter, and Deborah Oluwaseun Jegede. “Inadequacy of infrastructural facilities in public universities in Nigeria: Causes, effects and solutions”. In: International Journal on Integrated Education 6.3 (2023), p. 36.

James Hutson. The adoption of artificial intelligence and inertia in higher education: Exploring complex resistance to technological change. Taylor & Francis, 2025. DOI: https://doi.org/10.4324/9781003655862

Olatunde Fatai Badmus. “Transforming Program Management through Generative Artificial Intelligence”. In: International Journal of Latest Engineering and Management Research (IJLEMR) 8.12 (2023). DOI: https://doi.org/10.56581/IJLEMR.8.12.05-12

Peter Oeij, Karolien Lenaerts, Steven Dhondt, Wietse Van Dijk, Doris Schartinger, Sabrina Sorko, and Chris Warhurst. “A conceptual framework for workforce skills for industry 5.0: Implications for research, policy and practice”. In: Journal of Innovation Management 12.1 (2024), pp. 205–233. DOI: https://doi.org/10.24840/2183-0606_012.001_0010

Kathiravan Ravichandran. “Identifying learning difficulties at an early stage in education with the help of artificial intelligence models and predictive analytics”. In: International Research Journal of Multidisciplinary Scope (IRJMS) 5.4 (2024), pp. 1455–1461. DOI: https://doi.org/10.47857/irjms.2024.v05i04.01821

Yali Li, Laura Tolosa, Francklin Rivas-Echeverria, and Ronald Marquez. “Integrating AI in chemical education: Navigating UNESCO global guidelines, emerging trends, and its intersection with sustainable development goals”. In: (2025). DOI: https://doi.org/10.26434/chemrxiv-2025-wz4n9-v2

Shafika Isaacs and Sanjaya Mishra. “Smart education strategies for teaching and learning: Critical analytical framework and case studies”. In: (2022). DOI: https://doi.org/10.56059/11599/4464

Giada Lalli. “Defining interoperability: a universal standard”. In: Journal of ICT Standardization 13.2 (2025), pp. 139–156. DOI: https://doi.org/10.13052/jicts2245-800X.1323

Carmen Fattore, Michele Buldo, Arcangelo Priore, Sara Porcari, Vito Domenico Porcari, and Mariella De Fino. “A comprehensive overview of heritage bim frameworks: platforms and technologies integrating multi-scale analyses, data repositories, and sensor systems”. In: Heritage 8.7 (2025), p. 247. DOI: https://doi.org/10.3390/heritage8070247

Shihui Wang, Adzrool Idzwan Bin Ismail, and Panpan Qiao. “Optimized RE-CNN-Based Multi-Objective Decision Framework for Visual Feature Evaluation in Computational Art Analysis and Interactive Media”. In: Decision Making: Applications in Management and Engineering 7.1 (2024), pp. 752–770.

Abdul Wali Sirat, Musawer Hakimi, Bilal Himmat, and Wahidullah Enayat. “Artificial intelligence in educational leadership: Strategic, analytical, interactive, and decision-making applications for the digital age”. In: Jurnal Ilmiah Telsinas Elektro, Sipil dan Teknik Informasi 8.2 (2025), pp. 210–224. DOI: https://doi.org/10.38043/telsinas.v8i2.7044

Sanjai Vudugula, Sanath Kumar Chebrolu, Maniruzzaman Bhuiyan, and Farhana Zaman Rozony. “Integrating artificial intelligence in strategic business decision-making: A systematic review of predictive models”. In: International Journal of Scientific Interdisciplinary Research 4.1 (2023), pp. 01–26.

Keerthana Sivamayil, Elakkiya Rajasekar, Belqasem Aljafari, Srete Nikolovski, Subramaniyaswamy Vairavasundaram, and Indragandhi Vairavasundaram. “A systematic study on reinforcement learning based applications”. In: Energies 16.3 (2023), p. 1512. DOI: https://doi.org/10.3390/en16031512

Christopher J. C. H. Watkins. “Learning from Delayed Rewards”. PhD thesis. University of Cambridge, 1989.

Richard S. Sutton and Andrew G. Barto. Reinforcement Learning: An Introduction. Cambridge, MA: MIT Press, 1998. DOI: https://doi.org/10.1109/TNN.1998.712192

Mohamed-Amine Chadi and Hajar Mousannif. “Understanding reinforcement learning algorithms: The progress from basic Q-learning to proximal policy optimization”. In: arXiv preprint arXiv:2304.00026 (2023).

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. “Proximal Policy Optimization Algorithms”. In: arXiv preprint arXiv:1707.06347 (2017).

Volodymyr Mnih et al. “Human-level control through deep reinforcement learning”. In: Nature 518.7540 (2015), pp. 529–533. doi: 10.1038/nature14236. DOI: https://doi.org/10.1038/nature14236

Agus Perdana Windarto, Solikhun Solikhun, and Anjar Wanto. “Enhancing autonomous vehicle navigation in urban traffic using CNN-based deep Q-networks”. In: Journal of Applied Data Sciences 6.4 (2025), pp. 2565–2581. DOI: https://doi.org/10.47738/jads.v6i4.896

Juan Escobar-Naranjo, Gustavo Caiza, Paulina Ayala, Edisson Jordan, Carlos A Garcia, and Marcelo V Garcia. “Autonomous navigation of robots: optimization with DQN”. In: Applied Sciences 13.12 (2023), p. 7202. DOI: https://doi.org/10.3390/app13127202

Yusong Liu and Jianjun Song. “Research on real-time dynamic adjustment strategy of industry-teaching integration practical training process in higher vocational education based on reinforcement learning”. In: J. Combin. Math. Combin. Comput 127 (2025), pp. 3161–3176. DOI: https://doi.org/10.61091/jcmcc127a-179

Claudia-Melania Chituc. “Exploring the Role of Semantic Web Technologies and Ontologies in the Digital Education Ecosystems for Education 4.0”. In: 2025 IEEE 12th International Conference on E-Learning in Industrial Electronics (ICELIE). IEEE. 2025, pp. 1–6. DOI: https://doi.org/10.1109/ICELIE64733.2025.11244746

Ana Perisic, Ines Perisic, Marko Lazic, and Branko Perisic. “The foundation for future education, teaching, training, learning, and performing infrastructure-The open interoperability conceptual framework approach”. In: Heliyon 9.6 (2023). DOI: https://doi.org/10.1016/j.heliyon.2023.e16836

Idrees Alsolbi. “Enabling Data-Driven Innovation in the Third Sector: A Framework for Leveraging Big Data”. In: Cloud Computing and Data Science (2026), pp. 126–153. DOI: https://doi.org/10.37256/ccds.7120268852

Jesus Kombaya Touckia, Nadia Hamani, and Lyes Kermad. “Digital twin framework for reconfigurable manufacturing systems (RMSs): design and simulation”. In: The International Journal of Advanced Manufacturing Technology 120.7 (2022), pp. 5431–5450. DOI: https://doi.org/10.1007/s00170-022-09118-y

Carter Cousineau. “Advancing Trustworthy Artificial Intelligence (AI): Practical Approaches for Enhancing Interpretability and Transparency”. PhD thesis. The University of Guelph, 2025.

Bery Leouro Mbaiossoum, Mahamat Atteib Ibrahim Doutoum, Apollinaire Batoure Bamana, Narkoy Baoutma, et al. “Self-Efficacy Prediction Model Using Bayesian Networks”. In: International Journal on Interactive Systems and Engineering Management (JISEM) 10.37s (2024). doi: 10.52783/jisem.v10i37s.6447. DOI: https://doi.org/10.52783/jisem.v10i37s.6447

Downloads

Published

2026-08-17 — Updated on 2026-09-28

Versions

Issue

Vol. 1 No. 1 (2026): AI, Education, Environment and Future Mobility: Machine Learning Applications for Sustainable Intelligent Systems

Section

Research Articles

License

Copyright (c) 2026 Leslie Erika Kouamouo Ndangang, Prof. Justin Moskolaï Ngossaha, Prof. Adolphe Ayissi Etémé (Author)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

KOUAMOUO NDANGANG, L. E., MOSKOLAI NGOSSAHA, J. ., & AYISSI ETEME, A. (2026). Self-evolving engineering curricula: A Reinforcement Learning architecture to align academic training with industry demands in developing countries. Canadian Journal of Artificial Intelligence for Learning and Engineering Innovation, 1(1), 11–26. https://doi.org/10.65269/993p4h33 (Original work published 2026)