Exploration and Application of Personalized Education Management Model Driven by AI Technology

Abstract

Students' learning behavior hides a large number of personalized laws that can't be identified by human beings, which need to be mined and utilized with the help of AI technology. And with the development of AI technology and the importance of national planning, the in-depth application of AI technology to the education management system to promote the personalization and intelligence of education management has become one of the current and future research priorities. This paper conforms to the development trend of the times and constructs a knowledge tracking model of the dual-head attention mechanism of the long and short-term memory network, which effectively mines and predicts the students' historical learning behaviors and current knowledge state data. After obtaining students' knowledge mastery through knowledge tracking, the CIFW personalized resource recommendation model is further used to achieve targeted resource pushing for teachers and students according to a certain cycle frequency and presentation method. After the knowledge tracking model is introduced into the 3 technology modules, the prediction correctness in the 2 datasets reaches 0.8254 and 0.8239. The HR and NDCG values of the resource recommendation model can reach up to 0.9419 and 0.6753, and the resource recommendation effect is good.