Research Article
Research on Data Mining Technology of Online Intelligent Education Under Collaborative Learning
@INPROCEEDINGS{10.1007/978-3-031-21161-4_48, author={Zhi Zhang}, title={Research on Data Mining Technology of Online Intelligent Education Under Collaborative Learning}, proceedings={e-Learning, e-Education, and Online Training. 8th EAI International Conference, eLEOT 2022, Harbin, China, July 9--10, 2022, Proceedings, Part I}, proceedings_a={ELEOT}, year={2023}, month={3}, keywords={Collaborative learning Online learning Wisdom education Data mining Data characteristics Learning behavior}, doi={10.1007/978-3-031-21161-4_48} }- Zhi Zhang
Year: 2023
Research on Data Mining Technology of Online Intelligent Education Under Collaborative Learning
ELEOT
Springer
DOI: 10.1007/978-3-031-21161-4_48
Abstract
The educational data mining technology is delayed and has limitations in the process of operation. It cannot effectively deal with the characteristics of behavioral sequence, which leads to the problem of low accuracy and recall rate. This paper proposes a data mining technology for online intelligent education under collaborative learning. Construct the learner portrait under collaborative learning from the four dimensions of curriculum learning characteristics, task completion characteristics, interpersonal interaction characteristics and learning performance, and extract the characteristics of educational data. The decision tree method is used to cluster the students’ behavior characteristics, and the online intelligent education data mining algorithm is designed to analyze the correlation between students’ behavior habits and comprehensive quality. The experimental results show that compared with the data mining technology based on model driven and homomorphic encryption privacy protection, the accuracy and recall of the data mining technology in this paper are improved, which can analyze educational data more sensitively and provide reference for decision-making.
