Online Parameter Estimation for Student Evaluation of Teaching.

IF 1 4区 心理学 Q4 PSYCHOLOGY, MATHEMATICAL
Applied Psychological Measurement Pub Date : 2023-06-01 Epub Date: 2023-03-19 DOI:10.1177/01466216231165314
Chia-Wen Chen, Chen-Wei Liu
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引用次数: 0

Abstract

Student evaluation of teaching (SET) assesses students' experiences in a class to evaluate teachers' performance in class. SET essentially comprises three facets: teaching proficiency, student rating harshness, and item properties. The computerized adaptive testing form of SET with an established item pool has been used in educational environments. However, conventional scoring methods ignore the harshness of students toward teachers and, therefore, are unable to provide a valid assessment. In addition, simultaneously estimating teachers' teaching proficiency and students' harshness remains an unaddressed issue in the context of online SET. In the current study, we develop and compare three novel methods-marginal, iterative once, and hybrid approaches-to improve the precision of parameter estimations. A simulation study is conducted to demonstrate that the hybrid method is a promising technique that can substantially outperform traditional methods.

学生教学评价的在线参数估计。
学生教学评价(SET)通过评估学生在课堂上的体验来评价教师在课堂上的表现。SET 主要包括三个方面:教学能力、学生评分的苛刻程度和项目属性。SET 的计算机自适应测试形式已在教育环境中使用,并建立了项目库。然而,传统的评分方法忽略了学生对教师的苛刻程度,因此无法提供有效的评估。此外,在在线 SET 中,同时估计教师的教学水平和学生的苛刻程度仍是一个尚未解决的问题。在本研究中,我们开发并比较了三种新方法--边际法、迭代一次法和混合法,以提高参数估计的精度。我们进行了一项模拟研究,证明混合方法是一种很有前途的技术,可以大大优于传统方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.30
自引率
8.30%
发文量
50
期刊介绍: Applied Psychological Measurement publishes empirical research on the application of techniques of psychological measurement to substantive problems in all areas of psychology and related disciplines.
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