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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM55200
Volume:
9 |
12 |
Dec 2025
Pages:
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.
The digital learning process was growing rapidly and the main challenge faced by students is keeping the concepts in mind for a longer period, while traditional revision does not match human forgetting patterns. This makes performance go low and the study cycle ineffective. This paper proposes an AI-based Memory Curve Retention System which will remind or help learners revise at the right time through its mobile application. The system is based on Ebbinghaus’s Forgetting Curve and implements intelligent scheduling when to forget a topic by making predictions about when the student is likely to forget the topic. On this prediction, personalized reminders in spaced-repetition intervals together with progress insights and analytics will be generated by the app, hence increasing memory retention and building strong revision consistency that can be tracked by the students on their overall learning progress, mobile interface, backend services plus structured database for storing topics, revision logs, and retention scores. Results demonstrate improved student engagement and better reinforcement of previously learned material.
KEYWORDS
Publication Date
12/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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