ALIGNAgent: Adaptive Learner Intelligence for Gap Identification and Next-step guidance

ALIGNAgent is a multi-agent LLM-based framework that identifies student skill gaps from quiz performance and recommends personalized learning resources, evaluated on undergraduate computer science courses with GPT-4o achieving 0.87-0.90 precision in knowledge proficiency estimation.

Personalized learning systems have emerged as a promising approach to enhance student outcomes by tailoring educational content, pacing, and feedback to individual needs. However, most existing systems remain fragmented, specializing in either knowledge tracing, diagnostic modeling, or resource recommendation, but rarely integrating these components into a cohesive adaptive cycle. In this paper, we propose ALIGNAgent (Adaptive Learner Intelligence for Gap Identification and Next-step guidance),

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