Research on the Early Warning and Intervention of Learning Crisis Based on Smart Classroom

Abstract

Under the normal state of online and offline integrated learning of open courses, the low participation of learners and low learning results are hot issues that scholars in the industry pay more attention to. Accurate learning crisis warning and personalized teaching intervention are important measures to solve the above problems and improve teaching quality. Based on the analysis of the shortcomings of the existing learning early warning and teaching intervention, this study constructs a research framework of online open course learning early warning and intervention under the intelligent classroom learning environment. The framework diagnoses and warns learners' learning state from three aspects: knowledge mastery, learning behavior and learning mood. According to the diagnosis and warning report of learners, the corresponding intervention strategies are carefully designed, and learning analysis and data mining are applied to accurately match the implementation of intervention strategies to ensure the intervention effect and finally achieve the purpose of improving the learning effect.