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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM63970

EduQuest: Evaluating Pedagogical Impact and User Experience of an AI-Powered Real-Time Quiz Platform

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM63970

Volume:

10 |

5 |

May 2026

Pages:

1-9

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM63970

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.

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Authors

AS

Aniket Sable

Information Technology

RMD Sinhgad

Download Author Certificate
SP

Sandesh Pasalkar

Information Technology

RMD Sinhgad

AL

Aryan Lokhande

Information Technology

RMD Sinhgad

SR

Shantanu Rohile

Information Technology

RMD Sinhgad

DM

Dewanand Meshram

Information Technology

RMD Sinhgad

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Abstract

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

Keywords— Pedagogical impact AI-powered assessment gamification student engagement System Usability Scale cognitive load real-time quiz educational technology Gemini API MERN stack

Cite This Article

Aniket Sable, Sandesh Pasalkar, Aryan Lokhande, Shantanu Rohile, Dewanand Meshram, "EduQuest: Evaluating Pedagogical Impact and User Experience of an AI-Powered Real-Time Quiz Platform," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-9, May 2026. https://doi.org/10.55041/IJSREM63970

Full Article/Conclusion

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.

References

[1] D. Nicol and D. Macfarlane-Dick, "Formative assessment and self-regulated learning: A model and seven principles of good feedback practice," Studies in Higher Education, vol. 31, no. 2, pp. 199–218, Apr. 2006. [2] L. Chen, P. Chen, and Z. Lin, "Artificial intelligence in education: A review," IEEE Access, vol. 8, pp. 75264–75278, 2020. [3] M. Prensky, "Digital natives, digital immigrants," On the Horizon, vol. 9, no. 5, pp. 1–6, Oct. 2001. [4] Y. Chaiyo and R. Nokham, "The effect of Kahoot, Quizizz, and Google Forms on the student perception in the classrooms," in Proc. Int. Conf. on Digital Arts, Media and Technology (ICDAMT), Chiang Mai, Thailand, 2017, pp. 178–182. [5] Google AI, "Gemini API Documentation," Google for Developers, 2024. [Online]. Available: https://ai.google.dev/docs [6] E. Kochmar et al., "Automated personalized feedback improves learning gains in an intelligent tutoring system," in Proc. Int. Conf. on Artificial Intelligence in Education (AIED), Online, 2021, pp. 140–146. [7] S. G. Hart and L. E. Staveland, "Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research," Advances in Psychology, vol. 52, pp. 139–183, 1988. [8] J. Brooke, "SUS: A quick and dirty usability scale," in Usability Evaluation in Industry, P. W. Jordan et al., Eds. London: Taylor and Francis, 1996, pp. 189–194. [9] J. Sweller, "Cognitive load during problem solving: Effects on learning," Cognitive Science, vol. 12, no. 2, pp. 257–285, Apr. 1988. [10] F. Paas, A. Renkl, and J. Sweller, "Cognitive load theory and instructional design: Recent developments," Educational Psychologist, vol. 38, no. 1, pp. 1–4, Mar. 2003.

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Publication Date

5/25/2026

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Review Rounds: 2

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