Research on personalized learning recommendation mechanism based on deep learning
With the development of informatization,personalization and intelligence in education,it is an important issue for research to let machines read and understand students to explore the hidden features behind them to achieve adaptive learning and personalized development.This paper proposes an adaptive personalized learning recommendation model based on deep learning.Firstly,a learner model is constructed to reveal the deep semantic associations of students by analyzing their explicit and implicit features.Secondly,a comprehensive educational knowledge graph is designed,aiming to accurately describe and organize the knowledge structure of the educational domain through semantic representation.Finally,by fusing the knowledge graph with convolutional neural network technology,an adaptive personalized learning recommendation mechanism is developed.An adaptive personalized learning recommendation mechanism is developed,which is an algorithm capable of intelligently matching at the rule and semantic levels according to students'personal characteristics and learning needs to achieve personalized learning resource recommendation.
online learningknowledge graphpersonalized learningrecommender systems
NETL
NSTL
万方数据
