Intelligent Learning Evaluation Method Based on Data Mining

DOI

10.2991/978-94-6463-276-7_48How to use a DOI?

Keywords

Data Mining; Intelligent Learning; Learning Assessment; Knowledge System

Abstract

With the development of artificial intelligence technology, the field of education has also begun to use artificial intelligence technology, and the intelligent learning system with intelligent assessment as the core has gradually become a research hotspot. Compared with traditional rule-based evaluation methods, intelligent evaluation methods comprehensively evaluate learners from multiple aspects, which can effectively improve the comprehensiveness and objectivity of learning evaluation. The article first introduces the relevant concepts in the intelligent learning system, and then introduces the data mining technology used in the intelligent learning system based on data mining. Then this paper analyzes the learner feature extraction method, knowledge system construction method and evaluation strategy design method used in the intelligent learning system, finally, based on this, expounds an evaluation method of intelligent learning system based on data mining and knowledge system construction. The experimental results show that the reliability of the evaluation method based on data mining can reach 9.5 points at the highest.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Lilong Zhang
AU  - Yang Liu
AU  - Xuefeng Ying
PY  - 2023
DA  - 2023/10/27
TI  - Intelligent Learning Evaluation Method Based on Data Mining
BT  - Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
PB  - Atlantis Press
SP  - 453
EP  - 463
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-276-7_48
DO  - 10.2991/978-94-6463-276-7_48
ID  - Zhang2023
ER  -