Abstract

Education must follow the principle of teaching students in accordance with their aptitude. In this paper, we propose a novel method to generate personalized knowledge graphs based on graph convolutional network. We have summarized the methods of evaluating the difficulty of exercises, and apply them to the generation of knowledge graph. After that, the adjacency matrix corresponding to the knowledge graph and the eigenvectors corresponding to the nodes are used as inputs of the graph convolutional network, and the semi-supervised leaning node classification is adopted to continuously iterate the training to optimize the graph convolution neural network model. Meanwhile, the graph convolutional neural network is used to generate personalized knowledge graph for each student, more accurate personalized services can be provided. The experimental results show that our method can make a better to realize in-depth personalized services.

Highlights

  • Socrates, an ancient Greek educator, discovered more than 2000 years ago that the most common mistake in education is indoctrination, which mistakenly regards students as containers

  • We propose a novel method to generate personalized knowledge graphs based on graph convolutional network

  • The adjacency matrix corresponding to the knowledge graph and the eigenvectors corresponding to the nodes are used as inputs of the graph convolutional network, and the semi-supervised leaning node classification is adopted to continuously iterate the training to optimize the graph convolution neural network model

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Summary

Introduction

An ancient Greek educator, discovered more than 2000 years ago that the most common mistake in education is indoctrination, which mistakenly regards students as containers. Teachers are the center and lack of attention to students’ individual differences and different needs, which cannot stimulate students’ enthusiasm for learning. Experts and scholars in the field of education have noticed the shortcomings of traditional education and made. In the information age, personalized learning provides a wide and fair way to support educators in their efforts to endow learners with personal power and has become a new learning concept highly respected by the society. Different students have different ability to accept knowledge due to their different living environment, learning style, thinking style, gender differences and other factors. Personalized learning can tailor a set of exclusive learning programs for different students according to each person’s growth, background, interest and experience, so that students can give full play to their subjective initiative and learn efficiently

Related Work
Model Architecture
Classification Using Graph Convolutional Network
Generation of Personalized Knowledge Graph
Dataset
Experiment on Personalized Knowledge Graph
Conclusion and Future Work
Full Text
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