A Multivariate Generalizability Theory Approach to College Students' Evaluation of Teaching

Teachers' teaching level evaluation is an important component in classroom teaching and professional promotion in the institutions of higher learning in China. Many self-made questionnaires are currently being administered to Chinese college students to evaluate teachers' classroom teachin...

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Bibliographic Details
Main Authors: Guangming Li, Guiyun Hou, Xingjun Wang, Dong Yang, Hu Jian, Weijun Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-06-01
Series:Frontiers in Psychology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fpsyg.2018.01065/full
Description
Summary:Teachers' teaching level evaluation is an important component in classroom teaching and professional promotion in the institutions of higher learning in China. Many self-made questionnaires are currently being administered to Chinese college students to evaluate teachers' classroom teaching performance. Quite often, due to the absence of strong educational, and psychological measurements and theoretical foundations for these questionnaires, their dependability remains open to doubt. Evaluation time points, the number of students, major type, and curriculum type were examined in relation to college students' perceptions on their teachers' classroom teaching performance, using Teachers' Teaching Level Evaluation Scale for Colleges (TTLES-C). Data were collected in a sample of 556 students at two time points from three Chinese universities and were analyzed using multivariate generalizability theory. Results showed that evaluations at the beginning of the spring semester produced better outcomes than did evaluations at the end of the fall semester, and 20 student evaluators were sufficient to ensure good dependability. Results also revealed that the evaluation dependability of science curriculum appeared higher than that of liberal arts curriculum. Recommendations were discussed on the evaluation criteria and mode.
ISSN:1664-1078