Revolutionizing System Thinking Pedagogy for Innovation using AI-Augmented Gamified DFMEA Framework

Authors

  • Meenakshi Devi M. Department of Electrical and Electronics Engineering, Thiagarajar College of Engineering, Tamil Nadu
  • Kavitha D. EEE Department, Thiagarajar College of Engineering, Madurai, Tamilnadu – 625015

DOI:

https://doi.org/10.16920/jeet/2026/v39is2/26010

Keywords:

System thinking, System Engineering, Classroom venture, Gamified DFMEA framework, Sustainable Development Goals, AI.

Abstract

Systems thinking explores how interconnected components form a cohesive whole, emphasizing feedback loops and dynamic interactions. Accordingly, the goal of systems thinking is to comprehend how components relate to one another, how this impact the system outcomes and how a system fits into the real-time context of its surroundings. This study in Engineering makes a student an able person to face the competitive World with innovative ideas. The current investigation focuses on system thinking abilities in Engineering studies. About one-forty students from third year Under Graduation Engineering program were included in the sample population. The teaching- learning methodology introduces a concept of Classroom venture and details about the AI- Augmented Gamified DFMEA framework to improve the quality of the projects developed by the students. The paper focuses on (i) How do the cognitive elements of system thinking relate to one another? (ii)Are the students able to handle complicated systems? The framework fosters continuous reflection, collaborative decision-making, and deeper cognitive engagement, aligning with outcome-based education goals. The implementation shows promise in bridging the gap between theoretical risk analysis and practical innovation, especially in systems-thinking-based prototyping courses. This interdisciplinary approach offers a transformative model for engineering education, demonstrating how AI and gamification can coalesce to create meaningful, high-impact learning experiences in a rapidly evolving technological world.

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Published

2026-02-18

How to Cite

M., M. D., & D., K. (2026). Revolutionizing System Thinking Pedagogy for Innovation using AI-Augmented Gamified DFMEA Framework. Journal of Engineering Education Transformations, 39(Special Issue 2), 77–84. https://doi.org/10.16920/jeet/2026/v39is2/26010

Issue

Volume 39, Special Issue 2, January 2026

Section

Articles
Crossref
Scopus
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Europe PMC

References

Stamatis, D. H. (2003). Failure Mode and Effect Analysis: FMEA from Theory to Execution. ASQ Quality Press.

Anitha, D., & Kavitha, D. (2021). Is long-serving teaching experience a barrier of transformation in online teaching?–An exploration. Journal of Engineering Education Transformations, 34, 201–205.

Pahl, G., Beitz, W., Feldhusen, J., & Grote, K. H. (2007). Engineering Design: A Systematic Approach. Springer.

Zhang, Y., et al. (2021). Artificial intelligence in reliability and risk analysis. Reliability Engineering & System Safety, 207.

Serugga, J., Kagioglou, M., & Tzortzopoulos, P. (2020). A framework for emergent needs analysis during front-end design in social housing. Proceedings of the International Structural Engineering and Construction Conference, Paper AAW-04.

Lee, J., Bagheri, B., & Kao, H. A. (2015). A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manufacturing Letters, 3.

Kordova, S., & Frank, M. (2018). Systems thinking as an engineering language. American Journal of Systems Science, 6(1), 16–28.

Mitrovic, Z. M., Rakicevic, A. M., Petrovic, D. C., Mihic, M. M., Rakicevic, J. D., & Jelisic, E. T. (2020). Systems thinking in software projects—An artificial neural network approach. IEEE Access, 8, 213619–213635.

Anitha, D., Kavitha, D., Prakash, R. R., & Raja, S. C. (2020). Identification of opinion difference in teaching-learning methods and recommendation to faculty. Journal of Engineering Education Transformations, 33, 421–424.

Camelia, F., Ferris, T. L. J., & Cropley, D. H. (2018). Development and initial validation of an instrument to measure students’ learning about systems thinking: The affective domain. IEEE Systems Journal, 12(1), 115–124.

Nagahi, M., Ibne Hossain, N. U., El Amrani, S., Jaradat, R., Khademibami, L., Goerger, S. R., & Buchanan, R. (2022). Investigating the influence of demographics and personality types on practitioners’ systems thinking skills. IEEE Transactions on Engineering Management, 69(6), 3923–3937.

Jaradat, R. M., Keating, C. B., & Bradley, J. M. (2018). Individual capacity and organizational competency for systems thinking. IEEE Systems Journal, 12(2), 1203–1210.

Camelia, F., Ferris, T. L. J., & Behrend, M. B. (2020). The effectiveness of a systems engineering course in developing systems thinking. IEEE Transactions on Education, 63(1), 10–16.

Klein, M., & Maimon, O. (2021). Fundamentals of soft logic. New Mathematics and Natural Computation, 17(3), 703–737.

Kavitha, D., & Anitha, D. (2018). Flipped classroom using ICT tools to improve outcome for the course ‘Soft Computing’—A case study. Journal of Engineering Education Transformations, 32(2), 39–45.

Klein, M., & Maimon, O. (2020). The dynamics in the soft numbers coordinate system. Journal of Advanced Mathematics, 18, 1–17.

Fivel, O., Klein, M., & Maimon, O. (2022). Decision trees with soft numbers. International Journal of Circuits, Systems, and Signal Processing, 15, 1803–1816.

Hirschprung, R. S., Klein, M., & Maimon, O. (2022). Harnessing soft logic to represent the privacy paradox. Informatics, 9(3), 54.

Almutairi, M. S. (2021). A comprehensive review of soft computing models for permeability p rediction. IEEE Access, 9, 4911–4922.

Peretz, R., Tal, M., Akiri, E., Dori, D., & Dori, Y. J. (2023). Fostering systems thinking and conceptual modeling skills among engineering and science students and teachers. Instructional Science, 51(3), 509–543.

Kordova, S. K., Frank, M., & Miller, A. N. (2018). Systems thinking education—Seeing the forest through the trees. Systems, 6(3), 29.

Huang, Z., Kougianos, E., Ge, X., Wang, S., Chen, P. D., & Cai, L. (2021). A systematic interdisciplinary engineering and technology model using cutting-edge technologies for STEM education. IEEE Transactions on Education, 64(4), 390–397.

Farrar, E. J. (2020). Implementing a design thinking project in a biomedical instrumentation course. IEEE Transactions on Education, 63(4), 240-245.

Gonzales, M., Nassaji, H., & Chao, K. (2021). Student engagement with teacher written corrective feedback in a French as a foreign language classroom. Journal of Response to Writing, 7(2), 37–73.

Cruz, M. L., van den Bogaard, M. E. D., Saunders-Smits, G. N., & Groen, P. (2021). Testing the validity and reliability of an instrument measuring engineering students’ perceptions of transversal competency levels. IEEE Transactions on Education, 64(2), 180–186.

Alcaraz, R., Martinez-Rodrigo, A., Zangroniz, R., & Rieta, J. J. (2020). Blending inverted lectures and laboratory experiments in an introductory digital systems course. IEEE Transactions on Education, 63(3), 144–154.

Chevalier, K., Dekemele, J., Juchem, J., & Loccufier, M. (2021). Student feedback on educational innovation in control engineering: Active learning in practice. IEEE Transactions on Education, 64(4), 432–437.

Schwartz, M., Smits, K., Smith, J. M., & Phelan, T. J. (2022). Teaching students to incorporate community perspective into environmental engineering problem definition through iterative conceptual site models. Proceedings of the American Society for Engineering Education Conference, Minneapolis, MN.