Adaptive Learning Path Navigation Based on Knowledge Tracing and Reinforcement Learning

This paper proposes an Adaptive Learning Path Navigation (ALPN) system that combines Attentive Knowledge Tracing (AKT) to assess students' knowledge states with an Entropy-enhanced Proximal Policy Optimization (EPPO) algorithm to recommend tailored learning materials, creating personalized adaptive learning paths in E-learning platforms. The system dynamically updates knowledge states as students complete materials and demonstrates 8.2% improvement in learning outcomes and 10.5% higher diversity in learning path generation compared to previous approaches.

This paper introduces the Adaptive Learning Path Navigation (ALPN) system, a novel approach for enhancing E-learning platforms by providing highly adaptive learning paths for students. The ALPN system integrates the Attentive Knowledge Tracing (AKT) model, which assesses students' knowledge states, with the proposed Entropy-enhanced Proximal Policy Optimization (EPPO) algorithm. This new algorithm optimizes the recommendation of learning materials. By harmonizing these models, the ALPN system ta

Study Type

Source

Framework Categories

Tool Types

Tags