Research on the Construction of Classroom Teaching Evaluation System Based on Analytic Hierarchy Process

DOI

10.2991/978-94-6463-040-4_54How to use a DOI?

Keywords

AHP; Classroom teaching evaluation; High quality classroom

Abstract

With the diversified and digital development of educational models, teaching quality needs more scientific evaluation. Teaching quality is not only related to the learning quality of students, but also related to the training of national talents. Objective and fair evaluation of classroom teaching quality is an important part of education. In order to evaluate the quality of classroom teaching scientifically, this paper uses analytic hierarchy process to evaluate the quality of classroom teaching. According to the rules of analytic hierarchy process, the high-quality classroom is the target level, the first and second level indicators are the criteria level, and the four classes are the scheme level. This paper calculates the weights of the first and second level classroom indicators, and constructs the classroom evaluation index system. Experts enter the classroom to score, and use the analytic hierarchy process to calculate and sort to get the optimal classroom. This paper provides a scientific calculation method for evaluating the quality of classroom teaching.

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  - Xiao Chen
PY  - 2022
DA  - 2022/12/27
TI  - Research on the Construction of Classroom Teaching Evaluation System Based on Analytic Hierarchy Process
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 356

EP  - 362

SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_54
DO  - 10.2991/978-94-6463-040-4_54
ID  - Chen2022
ER  -