@inproceedings{7901a55e12fb4de6bfdbf85a5fe1a6e3,
title = "Research on construction of learner portrait based on learning analytics technology",
abstract = "With the development of big data, artificial intelligence, and wearable technology, the data generated by learners in the learning process can be fully recorded and stored. Using these data to study the characteristics of different types of learners and provide them with precise and personalized learning guidance is an urgent problem to be solved. This paper proposes a learner portrait construction method based on learning analysis technology. Firstly, the case frame relationship with {"}learning{"} as the central verb is established by using case grammar. Secondly, constructing a {"}learning-learner{"} feature layer with 6 sub-layers through qualitative analysis, and organizing the primary data of learners into 6 kinds of integrated data with specific meanings. Then, two methods of classifying learner types, cluster analysis and standard establishment, are proposed. Finally, giving an example of learner portrait construction.",
keywords = "analytics technology, cluster analysis, data mining, learner portrait",
author = "Yan Zhou and Haodong Fan",
note = "Publisher Copyright: {\textcopyright} 2023 SPIE.; 2022 International Conference on Artificial Intelligence and Industrial Design, AIID 2022 ; Conference date: 21-10-2022 Through 23-10-2022",
year = "2023",
doi = "10.1117/12.2673049",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Zhiyong Xiong and Renke He",
booktitle = "International Conference on Artificial Intelligence and Industrial Design, AIID 2022",
address = "美国",
}