Research on the Evaluation of College Curriculum Teaching Effect Based on Association Rules

DOI

10.2991/978-94-6463-192-0_48How to use a DOI?

Keywords

University curriculum; Teaching effect; Association rules; Index evaluation; Data mining

Abstract

The effect of teaching monitoring and evaluation in colleges and universities is not ideal. External monitoring and internal monitoring indicators are inconsistent, which is unable to achieve the effective use of evaluation data. Part of the evaluation process is more inclined to the evaluation of management and teaching effect and lack of a monitoring index system for the teaching process. Some colleges and universities have carried out network evaluation, which broadens the time and space of evaluation in the form of evaluation. However, they do not make effective use of the large amount of data generated in the evaluation process. Based on the research of data mining algorithms, this paper proposes the effective application of data mining in the internal teaching quality monitoring and evaluation of colleges and universities. It combines with a large number of original data clustering analysis, puts forward a new model construction idea after the weight distribution of the original teaching evaluation model indicators, and applies association rules analysis. The data preparation and data processing are described in detail. The performance of the improved algorithm proposed in this paper is compared by using the same data set and running environment. The effect of this research is proven. By analyzing the results of teaching evaluation, teachers’ information, and curriculum characteristics, we can get the ideas and measures to effectively use the results of teaching evaluation and improve teachers’ teaching ability.

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  - Qiancheng Chen
PY  - 2023
DA  - 2023/07/04
TI  - Research on the Evaluation of College Curriculum Teaching Effect Based on Association Rules
BT  - Proceedings of the 2023 2nd International Conference on Educational Innovation and Multimedia Technology (EIMT 2023)
PB  - Atlantis Press
SP  - 369
EP  - 377
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-192-0_48
DO  - 10.2991/978-94-6463-192-0_48
ID  - Chen2023
ER  -