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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM61208
Volume:
10 |
4 |
April 2026
Pages:
1-5
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.
Dept. of Information Technology
AIMT Lucknow, India
Dept. of Information Technology
AIMT Lucknow, India
Dept. of Information Technology
AIMT Lucknow, India
Most students who enroll in online courses never finish them. They watch a few videos, lose interest, and the platform does nothing to stop them. BrainBox is our response to this — a web-based e-learning system built around a mandatory quiz checkpoint called the Brain Breaker Quiz, where learners must score at least 60 percent before the next module unlocks. Beyond this gate, the platform uses points, achievement badges, and a leaderboard to sustain motivation. A personal dashboard shows each learner where they stand, and an admin panel gives instructors control over course content and quiz creation. The system was developed using React.js on the frontend, Node.js with Express.js on the backend, and MongoDB for data storage. We ran a four-week study with 45 undergraduate students divided between BrainBox and a conventional video-based LMS. The BrainBox group completed around 75 percent of assigned modules against roughly 40 percent for the other group. Average session time rose from 15 minutes to about 35 minutes, and user satisfaction was rated 4.5 out of 5. This paper covers how the system was designed, what was implemented, what problems came up, what the evaluation found, and what we would improve in future work.
KEYWORDS
The central question behind BrainBox was whether mandatory quizzes — rather than optional ones — would change how much students engaged with online course content. Over four weeks with 45 students, the answer was yes. Completion rates were close to double those of the comparison group. Sessions were longer. Students were retrying quizzes and going back to rewatch videos. The platform did what it was designed to do. BrainBox is not a finished product at scale. The evaluation was small and the groups were not randomly assigned, which introduces selection bias. What it provides is a working prototype covering the full cycle — content delivery, mandatory assessment, gamification, and progress tracking — on a solid and maintainable technical base. High-priority future improvements include automatic quiz generation from uploaded content, adaptive difficulty based on individual performance history, a native mobile application, and offline content access. Instructor-facing analytics — showing where students get stuck, which questions fail most often, and where drop- off occurs — would also add significant value. Live collaborative sessions and multilingual support are longer-term targets once the core product matures.
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Publication Date
4/30/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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