5 CONCLUSIONS
To sum up, with the rapid development of
globalization and the wide application of
information technology, English, as the most widely
used language, has become a public compulsory
basic course offered by various colleges and
universities. In recent years, China's requirements
for College English teaching standards, teaching
methods and evaluation methods have become
higher and higher. Therefore, in the evaluation of
College English teachers' teaching and learning, it is
necessary to formulate a systematic and perfect
evaluation mechanism to truly reflect the teaching
situation in the classroom, so as to promote the
development of the teaching evaluation system.
Regarding classroom evaluation, Bill Gates once
said, "there is a kind of work in the world that is
very important, but every time these people get
feedback at work, they only get 'satisfaction' or
'dissatisfaction'. How can we ask them to do their
work better by relying on this word alone?" As a
basic course of general education in Colleges and
universities, College English has always attracted
much attention for its teaching effect.
Firstly, this paper analyzes the present situation
of teaching quality evaluation in colleges and
universities, and finds that the data analysis function
of most teaching quality evaluation systems is weak
and the data can't be fully utilized. On this basis, it
uses big data analysis to analyze the data of
teachers' teaching quality evaluation from multiple
angles, and obtains some information with certain
reference value for teachers, students and
administrators. Based on this, it constructs a
teaching evaluation analysis model, with a view to
providing reference for the improvement of
teachers' teaching quality evaluation in the future.
REFERENCES
Aslan D, Aydin H. Evaluation of the teaching processes at
science high schools based on a constructivist
approach. A scale development study. Oxidation
Communications, vol. 38, no. 1A, pp. 472-491, 2015.
Chen Z. Using Big Data Fuzzy K-Means Clustering and
Information Fusion Algorithm in English Teaching
Ability Evaluation. Complexity, vol. 2021, no. 5, pp.
1-9, 2021.
Guo J, Bai L, Yu Z, et al. An AI-Application-Oriented
In-Class Teaching Evaluation Model by Using
Statistical Modeling and Ensemble Learning. Sensors,
vol. 21, no. 1, pp. 241, 2021.
Hasani H, Bahrami M,Malekpour A, et al. Evaluation of
Teaching Methods in Mass CPCR Training in
Different Groups of the Society, an Observational
Study.. Medicine, vol. 94, no. 21, pp. e859, 2015.
Liu L. Smart teaching evaluation model using weighted
naive bayes algorithm. Journal of Intelligent and
Fuzzy Systems, vol. 40, no. 1, pp. 1-11, 2020.
Lu Y, Li N, Lin H, et al. A Multiple and
Multidimensional Linguistic Truth-Valued Reasoning
Method and its Application in Multimedia Teaching
Evaluation. International Journal of Computational
Intelligence Systems, vol. 15, no. 1, pp. 1-11, 2022.
M Martínez-Gómez, Sierra J, Jabaloyes J, et al. A
multivariate method for analyzing and improving the
use of student evaluation of teaching questionnaires: a
case study. Quality & Quantity, vol. 45, no. 6, pp.
1415-1427, 2011.
Steinberg M P, Kraft M A. The Sensitivity of Teacher
Performance Ratings to the Design of Teacher
Evaluation Systems. Educational Researcher, vol. 46,
no. 7, pp. 378-396, 2017.
Yueh H P, Chen T L, Chiu L A, et al. Student Evaluation
of Teaching Effectiveness of a Nationwide Innovative
Education Program on Image Display Technology.
IEEE Transactions on Education, vol. 55,no. 3, pp.
365-369, 2012.
Zhou L, Li H, Sun K. Teaching performance evaluation
by means of a hierarchical multifactorial evaluation
model based on type-2 fuzzy sets. Applied
Intelligence, vol. 46, no. 1, pp. 1-11, 2016.