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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM68197
Volume:
10 |
10 |
Oct 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.
Electronics and Communication Engineering
Priyadarshini College of Engineering, Nagpur
Electronics and Communication Engineering
Priyadarshini College of Engineering, Nagpur
Electronics and Communication Engineering
Priyadarshini College of Engineering, Nagpur
Electronics and Communication Engineering
Priyadarshini College of Engineering, Nagpur
Electronics and Communication Engineering
Priyadarshini College of Engineering, Nagpur
The traditional "one-size-fits-all" approach in educational games often fails to address the diverse learning needs and paces of individual children, leading to disengagement and suboptimal learning outcomes. This paper presents "Learn with Me," a web-based AI adaptive learning game designed to provide personalized educational experiences for children. The system employs Bayesian Knowledge Tracing (BKT) , a machine learning technique that models a child's knowledge state by analyzing their response patterns in real-time. Based on this analysis, the game automatically adjusts question difficulty, ensuring that each child is challenged appropriately without becoming frustrated or bored. The system tracks key performance metrics including learning speed, accuracy, and overall progress. "Learn with Me" combines engaging gameplay with intelligent adaptation to make learning interactive, effective, and enjoyable. This paper details the system architecture, AI model implementation, and preliminary testing results, demonstrating the potential of AI-driven adaptive games to revolutionize early childhood education.
KEYWORDS
The system continuously monitors each skill's knowledge probability. When a skill drops below a threshold, the system provides additional practice opportunities. When a skill reaches mastery, the system introduces new, related skills.
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Publication Date
10/23/2026
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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