Engineering Education Transformation for Education 5.0: Developing an Evidence-Based Transformation Framework Through Bibliometric and Systematic Literature Analysis

Authors

  • Muhamad Fahrezi Universitas Komputer Indonesia, Indonesia
  • Choriyeva Surayyo Olimovna New Uzbekistan University, Uzbekistans
  • Tejas Gopinath Sudake Solapur University, India
  • Khairul Azri Bin Azahri Universiti Malaysia Terengganu, Malaysia

DOI:

https://doi.org/10.34010/injuratech.v6i1.21329

Keywords:

Engineering Education 5.0,, Artificial Intelligence, Generative AI, Curriculum Transformation, Pedagogical Innovation

Abstract

Education 5.0 requires transforming engineering education to equip future engineers with technological, human-centered, and adaptive learning competencies. However, research remains fragmented across curriculum reform, artificial intelligence (AI), pedagogy, assessment, and competency development. This study develops an evidence-based Engineering Education 5.0 framework by identifying research trends, conceptual relationships, and transformation dimensions. A mixed systematic approach combining bibliometric analysis of 198 publications from 2022–2026 with thematic synthesis of 12 selected studies was employed. Bibliometric mapping identified five interconnected dimensions: curriculum transformation, AI-driven education, pedagogical innovation, assessment reform, and future engineering competencies. The findings indicate that AI, particularly Generative AI, supports adaptive learning, personalized instruction, and collaborative problem-solving, but requires ethical governance and human-centered implementation. Experiential, collaborative, and gamified learning enhance engagement and higher-order thinking, while assessment should emphasize authentic and competency-based evaluation. The proposed framework integrates AI literacy, systems thinking, sustainability, ethics, collaboration, and lifelong learning to develop future-ready engineers.

References

[1] Islam, M. T., Sepanloo, K., Woo, S., Woo, S. H., & Son, Y. J. (2025). A review of the industry 4.0 to 5.0 transition: exploring the intersection, challenges, and opportunities of technology and human–machine collaboration. Machines, 13(4), 267.

[2] Sharma, M., Tomar, A., & Hazra, A. (2024). Edge computing for industry 5.0: Fundamental, applications, and research challenges. IEEE Internet of Things Journal, 11(11), 19070-19093.

[3] Miranda, J., Navarrete, C., Noguez, J., Molina-Espinosa, J. M., Ramírez-Montoya, M. S., Navarro-Tuch, S. A., ... & Molina, A. (2021). The core components of education 4.0 in higher education: Three case studies in engineering education. Computers & Electrical Engineering, 93, 107278.

[4] Hernandez-de-Menendez, M., Escobar Díaz, C. A., & Morales-Menendez, R. (2020). Engineering education for smart 4.0 technology: a review. International Journal on Interactive Design and Manufacturing (IJIDeM), 14(3), 789-803.

[5] Wan, Y., Li, R., Li, W., & Du, H. (2025). Impact pathways of AI-supported instruction on learning behaviors, competence development, and academic achievement in engineering education. Sustainability, 17(17), 8059.

[6] Dehbozorgi, M. H., Postell, J., Ward, D., Leardi, C., Sullivan, B. P., & Rossi, M. (2024). Human in the loop: revolutionizing industry 5.0 with design thinking and systems thinking. Proceedings of the Design Society, 4, 245-254.

[7] He, Q., & Yang, Z. (2026). Generative AI-driven knowledge management in manufacturing firms: a five-stage framework for dynamic knowledge optimization and digital innovation. Journal of Knowledge Management, 30(4), 1447-1467.

[8] Babu, B. V. (2024). Education 5.0: an overview. Advances in technological innovations in higher education, 168-243.

[9] Carayannis, E. G., & Morawska, J. (2023). University and education 5.0 for emerging trends, policies and practices in the concept of industry 5.0 and society 5.0. In Industry 5.0: Creative and Innovative Organizations (pp. 1-25). Cham: Springer International Publishing.

[10] Torres-Rivera, A. D., Rendón Peña, A. A., Díaz-Torres, S. T., & Díaz-Torres, L. A. (2025). Ethical integration of AI and STEAM pedagogies in higher education: A sustainable learning model for society 5.0. Sustainability, 17(19), 8525.

[11] Chigbu, B. I., & Makapela, S. L. (2025). AI in education, sustainability, and the future of work: An integrative review of industry 5.0, education 5.0, and work 5.0. Journal of Open Innovation: Technology, Market, and Complexity, 100645.

[12] Cañavate, J., Martínez-Marroquín, E., & Colom, X. (2025). Engineering a sustainable future through the integration of generative AI in engineering education. Sustainability, 17(7), 3201.

[13] Broo, D. G., Kaynak, O., & Sait, S. M. (2022). Rethinking engineering education at the age of industry 5.0. Journal of Industrial Information Integration, 25, 100311.

[14] Ciolacu, M. I., Boetcher, K. E., Alves, G. R., Pester, A., & Zoubi, A. Y. (2026). Engineering Education 5.0: Navigating Pedagogy and Technology in the Age of Generative AI. Procedia Computer Science, 277, 3540-3549.

[15] Ho, S. H., Mohamad Basir, M. N. A., Affendy, N. A. R., & Katim, N. I. A. (2025). Engineering education: does Industry 5.0 need Education 5.0?.

[16] Johri, A., Katz, A. S., Qadir, J., & Hingle, A. (2023). Generative artificial intelligence and engineering education. Journal of Engineering Education, 112(3).

[17] Beagon, U., Kövesi, K., Tabas, B., Nørgaard, B., Lehtinen, R., Bowe, B., ... & Spliid, C. M. (2023). Preparing engineering students for the challenges of the SDGs: what competences are required?. European Journal of Engineering Education, 48(1), 1-23.

[18] Pacher, C., Woschank, M., Zunk, B. M., & Gruber, E. (2024). Engineering education 5.0: a systematic literature review on competence-based education in the industrial engineering and management discipline. Production & Manufacturing Research, 12(1), 2337224.

[19] Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Grundy, S., ... & Sandison, C. (2023). ChatGPT versus engineering education assessment: a multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559-614.

[20] Schleiss, J., Manukjan, A., Bieber, M. I., Lang, S., & Stober, S. (2026). Designing an interdisciplinary artificial intelligence curriculum for engineering: evaluation and insights from experts. Computer Applications in Engineering Education, 34(2), e70151.

[21] Bond, M., Khosravi, H., De Laat, M., Bergdahl, N., Negrea, V., Oxley, E., ... & Siemens, G. (2024). A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour. International journal of educational technology in higher education, 21(1), 4.

[22] Baltà‐Salvador, R., El‐Madafri, I., Brasó‐Vives, E., & Peña, M. (2025). Empowering engineering students through artificial intelligence (AI): Blended human–AI creative ideation processes with ChatGPT. Computer Applications in Engineering Education, 33(1), e22817.

[23] Pérez‐González, A., Andrés‐Esperanza, J., Iserte, J. L., & Roda‐Casanova, V. (2026). Assessment of Five Generative Artificial Intelligence Tools in Theory of Machines and Mechanisms Through Bloom's Taxonomy. Computer Applications in Engineering Education, 34(4), e70234.

[24] Milakovic, A., Jocovic, V., Draskovic, D., & Nikolic, B. (2026). A Game‐Based Learning Approach to Artificial Intelligence Topics. Computer Applications in Engineering Education, 34(4), e70237.

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Published

2026-06-06

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Articles

How to Cite

Fahrezi, M., Olimovna, C. S., Sudake, T. G., & Azahri, K. A. B. (2026). Engineering Education Transformation for Education 5.0: Developing an Evidence-Based Transformation Framework Through Bibliometric and Systematic Literature Analysis. International Journal of Research and Applied Technology, 6(1), 272-291. https://doi.org/10.34010/injuratech.v6i1.21329