Quality Evaluation Method of Agricultural Talents Distance Education Based on Improved Decision Tree

DOI

10.2991/978-94-6463-172-2_123How to use a DOI?

Keywords

Agricultural education; Online classroom; Education quality; Random forest; Decision tree

Abstract

With the rapid development of information technology and the emphasis on education at all levels of the country and society, wisdom education, as a new application of information technology in the field of education, has a lot of research space. Educational data mining is an interdisciplinary field arising from its application in the field of education. Compared with the traditional educational environment, the current research based on the field of education is no longer lack of student behavior data. As a result, data-rich educational environments have become the norm. Abundant data provides a data base for EDM. To some extent, the sampling of education indicators can improve the problem of unbalanced data, but they also have the problems of low accuracy and insufficient sampling. This paper firstly constructs the l evaluation system of learning quality index quality based on the distance education of agricultural talents, clarifies the changes in learning quality of various groups, and adopts the difference analysis of the random forest algorithm based on an improved decision tree. By comparing with the existing evaluation model, the experimental results indicate that the network model optimized by this algorithm has a better effect on the evaluation of education quality. And that detection accuracy and precision are further improved. It is helpful for educational indicators to develop personalized evaluation and intervention programs. Finally, some suggestions for learners to improve their learning are put forward, and the research results can provide practical guidance for teaching stakeholders.

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  - Qi Wang
AU  - Guanghai Li
AU  - Yang Liu
PY  - 2023
DA  - 2023/06/30
TI  - Quality Evaluation Method of Agricultural Talents Distance Education Based on Improved Decision Tree
BT  - Proceedings of the 2023 4th International Conference on Education, Knowledge and Information Management (ICEKIM 2023)
PB  - Atlantis Press
SP  - 1168
EP  - 1176
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-172-2_123
DO  - 10.2991/978-94-6463-172-2_123
ID  - Wang2023
ER  -