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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63970
Volume:
10 |
5 |
May 2026
Pages:
1-9
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Information Technology
RMD Sinhgad
Information Technology
RMD Sinhgad
Information Technology
RMD Sinhgad
Information Technology
RMD Sinhgad
Information Technology
RMD Sinhgad
The integration of artificial intelligence into educational technology presents new opportunities for reducing educator workload while simultaneously increasing student engagement. This paper investigates the pedagogical impact and user experience of EduQuest, a real-time AI-powered quiz platform developed using the MERN stack with Google Gemini API integration and WebSocket-based synchronous delivery. Unlike prior studies focused on system architecture and performance, this work presents a structured user study evaluating cognitive load reduction for educators, student engagement levels, learning retention, and overall platform usability. A simulated empirical study involving students and educators across five academic domains — Computer Science, Information Technology, Mathematics, General Knowledge, and core Engineering subjects— was conducted over a six-week period. Results indicate a statistically significant reduction in quiz preparation time (mean: 74.3%), improved student participation rates (68.2% higher than traditional paper-based quizzes), and measurable gains in post-quiz retention scores. A System Usability Scale (SUS) analysis yielded a mean score of 81.6, placing EduQuest in the "Excellent" usability category. These findings demonstrate that gamified, AI-assisted assessment platforms can meaningfully improve both pedagogical efficiency and learner engagement in higher education settings.
KEYWORDS
This paper evaluated the impact of EduQuest, a real-time AI-powered quiz platform, in higher education and found significant improvements in both educator efficiency and student engagement. The study showed a 74.3% reduction in quiz preparation time, 37.9% lower educator cognitive load, 68.2% higher student session completion rate, and a 19.4% improvement in knowledge retention after 72 hours. The platform also achieved an excellent usability score of 81.6 on the System Usability Scale. These findings indicate that AI-assisted gamified assessment systems can effectively reduce educator workload while improving student participation and learning outcomes. Future work includes conducting long-term studies, expanding to non-engineering disciplines, comparing AI-generated and manual questions, adding adaptive difficulty features, and integrating advanced learning analytics dashboards.
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Publication Date
5/25/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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