Volume: 3 Issue: Special Issue 1
Year: 2026, Page: 7-14, Doi: https://doi.org/10.70372/jeltp.v3.sp1.2
Gamified, data-driven learning models are evolving engineering education into a dimensional, facilitating improved motivation, analytics, and contextualization. This research study presents the implementation of a machine learning-abled gamified model for the Computer Organization and Architecture (COA) course employed to second-year AI and AIML engineering students at Anurag University. The solution was applied to 4 sections (n = 240) and comprised rewards, badges, leader boards, and scenario-based assignments systematized around real-world technical applications. Supervised learning was conducted on student performance using 8 engineered features encompassing attendance, submission patterns, and participation in gamified learning. The Random Forest model achieved an R² value of 0.89 and MAE value of 2.4, outperforming Linear Regression, and the resulting supervised learning, t-test, and ANOVA results show statistically significant enhancement of student performance (p < 0.05). The quantitative results suggest an increase in accuracy, engagement, and assignment completion by 2028% and the qualitative feedback is in line with enhanced motivation and better conceptual understanding. Ethical concerns for fairness, anonymization, and responsible Artificial Intelligence have been discussed. With a culmination of results, gamification scenario-based learning incorporating AI-based student performance analytics has proven a viable, scalable, and ethical approach for optimizing technical education.
Keywords: Academic performance; Application-oriented learning; Gamification; Higher education; Machine learning classification; Student engagement
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