Research Article
Construction of University Education Teaching and Evaluation System Based on Data Mining Algorithm
@INPROCEEDINGS{10.1007/978-3-030-87900-6_53, author={Juan Li}, title={Construction of University Education Teaching and Evaluation System Based on Data Mining Algorithm}, proceedings={Application of Big Data, Blockchain, and Internet of Things for Education Informatization. First EAI International Conference, BigIoT-EDU 2021, Virtual Event, August 1--3, 2021, Proceedings, Part I}, proceedings_a={BIGIOT-EDU}, year={2021}, month={10}, keywords={Data mining Teaching evaluation Decision tree algorithm Analytic hierarchy process}, doi={10.1007/978-3-030-87900-6_53} }
- Juan Li
Year: 2021
Construction of University Education Teaching and Evaluation System Based on Data Mining Algorithm
BIGIOT-EDU
Springer
DOI: 10.1007/978-3-030-87900-6_53
Abstract
This paper discusses the selection of teaching evaluation index, establishes and solves the decision tree model of teaching evaluation, and carries out the concrete application of mining conclusions. The evaluation of teachers’ teaching quality is an effective measure to improve teaching quality and regulate teaching behavior. In this paper, we set up a data mining system for teaching evaluation, hoping to find out the information and knowledge that is helpful to improve teaching quality from a large number of teaching data, and apply it to practice. The construction of index system is the basis and basis of teaching evaluation. This paper uses AHP method to analyze the model of teaching evaluation system, and finally defines the evaluation indicators: teaching attitude, teaching content and teaching method as the basis for selecting and mining the teaching information attributes in the database, so as to reduce the mining library attributes; on the one hand, it improves the mining efficiency, On the other hand, it can avoid the phenomenon that the decision tree is too large because of too many mining fields, which leads to the phenomenon of over fitting mining objects.