Artificial intelligence-based personalized teaching tutoring method and system

Abstract

The present invention discloses an artificial intelligence-based personalized teaching tutoring method and system, comprising: acquiring real-time status and interest preferences through student interaction logs and evaluation data, constructing a knowledge network using a graph algorithm where nodes represent knowledge points with labeled difficulty levels and association relationships to obtain an initial three-dimensional network structure; based on the obtained three-dimensional network structure and student real-time status, determining a preliminary knowledge expansion direction by selecting relevant node expansion paths if the strength of the association relationship between interest preferences and current knowledge points exceeds a preset threshold; for the obtained path planning sequence, adjusting node order and integrating more association relationships to obtain a revised sequence if the matching degree between the difficulty levels in the sequence and the student’s ability level is lower than a preset threshold.