An AI-Driven Adaptive Gamification Framework for Systematic Improvement of Critical Thinking in Engineering Education

Authors

  • A M Viswa Bharathy Assistant Professor, AI&DS, GITAM School of CSE, GITAM University, Bengaluru

DOI:

https://doi.org/10.16920/jeet/2026/v39i4/26115

Keywords:

AI-driven gamification; Adaptive learning; Analytical reasoning; Critical thinking; Educational technology; Engineering education; Problem solving; Student engagement

Abstract

This research project describes an AI-based adaptive gamification platform that was developed, implemented, and validated to develop critical thinking skills including problem-solving and analytical reasoning, among undergraduate engineering students. Across three fields of theoretical foundation, cognitive load theory, self-determination theory, and constructivist learning tenets, the AI-based adaptive gamification platform has provided personalized challenges, feedback and social learning engagement. Furthermore, the application of the adaptive gamification platform was applied within the context of educational engagement on two university undergraduate engineering courses. Following a mixed-methods approach, a 12-week intervention with 120 students was conducted, integrating the adaptive gamification platform into the design of the undergraduate engineering courses. The study included a variety of quantitative measures pre and post intervention, longitudinal and cross-sectional, and assessment of engagement through measures of earned points, milestones, and sessions completed. The statistical analyses were significant across all components of critical thinking development (i.e., Problem Identification, Solutions Development, Solutions Evaluation, Decisions, Plans and Evidence Evaluation, and Final Decision) and averaged 22.9% improvement in performance on critical thinking activities (Effect size Cohen's d = 2.436). The project demonstrated the capacity for AI gamification to have a transformational impact on engineering education enabling the development of higher order cognitive skills and demonstrated clear implementation pathways for scaled transformative impact within individual university courses and developing a longer-lasting footprint within an institution.

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Published

2026-04-30

How to Cite

Bharathy, A. M. V. (2026). An AI-Driven Adaptive Gamification Framework for Systematic Improvement of Critical Thinking in Engineering Education. Journal of Engineering Education Transformations, 39(4), 151–158. https://doi.org/10.16920/jeet/2026/v39i4/26115

Issue

Volume 39, Issue 4, April 2026

Section

Articles
Crossref
Scopus
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Europe PMC

References

S. Vidalis and R. Subramanian, “Impact of AI Tools on Engineering Education,” Jan. 2024, doi: 10.18260/1-2--45122.

H. El-Hassan, A. Issa, M. A. Hamouda, M. A. Maraqa, and T. El‐Maaddawy, “Continuous Improvement of an Exit Exam Tool for the Effective Assessment of Student Learning in Engineering Education,” Trends in Higher Education, vol. 3, no. 3, p. 560, Jul. 2024, doi: 10.3390/higheredu3030033.

J. Lee, H. Su, D.-Y. Ji, and T. Minami, “Engineering artificial intelligence: framework, challenges, and future direction,” vol. 1, no. 1, p. 13001, Jul. 2025, doi: 10.1088/3049-4761/adce0d.

B. G. A. Enríquez et al., “AI in academia: How do social influence, self-efficacy, and integrity influence researchers’ use of AI models?,” Social Sciences & Humanities Open, vol. 11, p. 101274, Jan. 2025, doi: 10.1016/j.ssaho.2025.101274.

E. Dickey, A. Bejarano, R. Kuperus, and B. Fagundes, “Evaluating the AI-Lab Intervention: Impact on Student Perception and Use of Generative AI in Early Undergraduate Computer Science Courses,” 2025, doi: 10.48550/ARXIV.2505.00100.

L. Fan, K. K. Deng, and F. Liu, “Educational impacts of generative artificial intelligence on learning and performance of engineering students in China,” Scientific Reports, vol. 15, no. 1, Jul. 2025, doi: 10.1038/s41598-025-06930-w.

J. Batista, A. Mesquita, and G. Carnaz, “Generative AI and Higher Education: Trends, Challenges, and Future Directions from a Systematic Literature Review,”

Information, vol. 15, no. 11, p. 676, Oct. 2024, doi: 10.3390/info15110676.

M. Usher and M. Barak, “Unpacking the role of AI ethics online education for science and engineering students,” International Journal of STEM Education, vol. 11, no. 1, Aug. 2024, doi: 10.1186/s40594-024-00493-4.

V. Nguyen, “The Use of Generative AI Tools in Higher Education: Ethical and Pedagogical Principles,” Journal of Academic Ethics, Feb. 2025, doi: 0.1007/s10805-025-09607-1.

P. A. H. Aure and O. Cuenca, “Fostering social-emotional learning through human-centered use of generative AI in business research education: an insider case study,” Journal of Research in Innovative Teaching & Learning, vol. 17, no. 2, p. 168, Jun. 2024, doi: 10.1108/jrit-03-2024-0076.

E. Dickey, A. Bejarano, and C. Garg, “Innovating Computer Programming Pedagogy: The AI-Lab Framework for Generative AI Adoption,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2308.12258.

S. Krause, A. Dalvi, and S. K. Zaidi, “Generative AI in Education: Student Skills and Lecturer Roles,” 2025, doi: 10.48550/ARXIV.2504.19673.

K. Łodzikowski, P. W. Foltz, and J. T. Behrens, “Generative AI and Its Educational Implications,” in Postdigital science and education, Springer International Publishing, 2024, p. 35. doi: 10.1007/978-3-031-64487-0_2.

A. M. Al-Zahrani, “Unveiling the shadows: Beyond the hype of AI in education,” Heliyon, vol. 10, no. 9, May 2024, doi: 10.1016/j.heliyon.2024.e30696.

W. A. K. Salameh, “The dual role of AI in personalized learning: Enhancements and hindrances for diverse learners,” International Journal of Science and Research Archive, vol. 13, no. 2, p. 62, Nov. 2024, doi: 10.30574/ijsra.2024.13.2.2057.

C. Mahmoud and J. T. Sørensen, “Artificial Intelligence in Personalized Learning with a Focus on Current Developments and Future Prospects,” Research and Advances in Education, vol. 3, no. 8, p. 25, Aug. 2024, doi: 10.56397/rae.2024.08.04.

M. Joshi, “Adaptive Learning through Artificial Intelligence,” SSRN Electronic Journal, Jan. 2023, doi: 10.2139/ssrn.4514887.

J. C. G. Gutiérrez, A. Chiappe, D. F. B. Rodríguez, and L. I. González-Pérez, “The Transformative Journey of Artificial Intelligence Toward Personalized Learning,” The New Educator, p. 1, Mar. 2025, doi: 10.1080/1547688x.2025.2475811.

K. Karpouzis, “Artificial Intelligence in Education: Ethical Considerations and Insights from Ancient Greek Philosophy,” p. 1, Sep. 2024, doi: 10.1145/3688671.3688772.

O. O. Ayeni, N. M. A. Hamad, O. N. Chisom, B. Osawaru, and O. E. Adewusi, “AI in education: A review of personalized learning and educational technology,” GSC Advanced Research and Reviews, vol. 18, no. 2. p. 261, Feb. 20, 2024. doi: 10.30574/gscarr.2024.18.2.0062.

P. Sasikala and R. Ravichandran, “Study on the Impact of Artificial Intelligence on Student Learning Outcomes,” Journal of Digital Learning and Education, vol. 4, no. 2, p. 145, Aug. 2024, doi: 10.52562/jdle.v4i2.1234.

X. Zhai et al., “A Review of Artificial Intelligence (AI) in Education from 2010 to 2020,” Complexity, vol. 2021, no. 1. Hindawi Publishing Corporation, Jan. 01, 2021. doi: 10.1155/2021/8812542.

C. León, J. Lipuma, and X. Oviedo-Torres, “Artificial intelligence in STEM education: a transdisciplinary framework for engagement and innovation,” Frontiers in Education, vol. 10, Jul. 2025, doi: 10.3389/feduc.2025.1619888.

R. Silva, G. Godwin, and O. Jayanagara, “The Impact of AI on Personalized Learning and Educational Analytics,” International Transactions on Education Technology (ITEE), vol. 3, no. 1, p. 36, Oct. 2024, doi: 10.33050/itee.v3i1.669.

C. Merino-Campos, “The Impact of Artificial Intelligence on Personalized Learning in Higher Education: A Systematic Review,” Trends in Higher Education, vol. 4, no. 2. Multidisciplinary Digital Publishing Institute, p. 17, Mar. 26, 2025. doi: 10.3390/higheredu4020017.

H. Li et al., “Bringing Generative AI to Adaptive Learning in Education,” arXiv (Cornell University), Feb. 2024, doi: 10.48550/arxiv.2402.14601.

E. Barnes and J. Hutson, “Navigating the ethical terrain of AI in higher education: Strategies for mitigating bias and promoting fairness,” Forum for education studies., vol. 2, no. 2, p. 1229, Jun. 2024, doi: 10.59400/fes.v2i2.1229.

F. Kamalov and I. Gurrib, “New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution,” arXiv (Cornell University), Jan. 2023, doi: 10.48550/arxiv.2305.18303.

A. K. Das, S. Malaviya, and M. K. Singh, “The Impact of AI-Driven Personalization on Learners Performance,” International Journal of Computer Sciences and Engineering, vol. 11, no. 8, p. 15, Aug. 2023, doi: 10.26438/ijcse/v11i8.1522.

M. J. K. O. Jian, “Personalized learning through AI,” Advances in Engineering Innovation, vol. 5, no. 1, p. 16, Dec. 2023, doi: 10.54254/2977-3903/5/2023039.

X. Du, M. L. Dû, Z. Zhou, and Y.-M. Bai, “Facilitator or hindrance? The impact of AI on university students’ higher-order thinking skills in complex problem solving,” International Journal of Educational Technology in Higher Education, vol. 22, no. 1, Jul. 2025, doi: 10.1186/s41239-025-00534-0.

A. Ullrich, G. Vladova, F. Eigelshoven, and A. Renz, “Data mining of scientific research on artificial intelligence in teaching and administration in higher education institutions: a bibliometrics analysis and recommendation for future research,” Discover Artificial Intelligence, vol. 2, no. 1, Sep. 2022, doi: 10.1007/s44163-022-00031-7.

M. Dabingaya, “Analyzing the Effectiveness of AI-Powered Adaptive Learning Platforms in Mathematics Education,” Interdisciplinary Journal Papier Human Review, vol. 3, no. 1, p. 1, Jun. 2022, doi: 10.47667/ijphr.v3i1.226.

S. Maghsudi, A. Lan, J. Xu, and M. van der Schaar, “Personalized Education in the Artificial Intelligence Era: What to Expect Next,” IEEE Signal Processing Magazine, vol. 38, no. 3, p. 37, Apr. 2021, doi: 10.1109/msp.2021.3055032.

C. G. Demartini, L. Sciascia, A. Bosso, and F. Manuri, “Artificial Intelligence Bringing Improvements to Adaptive Learning in Education: A Case Study,” Sustainability, vol. 16, no. 3, p. 1347, Feb. 2024, doi: 10.3390/su16031347.

B. Jose, J. Cherian, A. M. Verghis, S. M. Varghise, S. Mumthas, and S. Joseph, “The cognitive paradox of AI in education: between enhancement and erosion,” Frontiers in Psychology, vol. 16, Apr. 2025, doi: 10.3389/fpsyg.2025.1550621.

S. Chakraborty, “Generative AI in Modern Education Society,” arXiv (Cornell University), Dec. 2024.