Design of teaching quality evaluation system for higher vocational education based on data mining technology
Published Online: Sep 20, 2023
Received: Nov 07, 2022
Accepted: Mar 31, 2023
DOI: https://doi.org/10.2478/amns.2023.2.00353
Keywords
© 2023 Yuanai Li, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
It is advantageous for schools to realize exact education management, the cornerstone for developing abilities, by constructing higher vocational education teaching quality evaluation systems. The division of frequent item sets based on the modified Apriori algorithm under the association rule algorithm is used for the evaluation algorithm of this system to examine the evaluation data in the evaluation system, which is created in this work using data mining technology. Data validation was carried out from system performance and application analysis of association rules for the teaching quality evaluation system constructed in this paper. Regarding system performance, the highest response time of the system in this paper is 8.34s, which is about 56.94% and 40.68% shorter than that of the evaluation system based on AHP and gray correlation theory, respectively. This shows that using association rule algorithms can realize the operation of the evaluation system faster, improve evaluation efficiency, and use visual data to achieve precise education management in schools.
