Using the Margin of Error Statistic to Examine the Effects of Aggregating Student Evaluations of Teaching

Document Type

Article

Publication Date

2-14-2019

Publication Title

Assessment & Evaluation in Higher Education,

Volume

44

Issue

7

First page number:

1042

Last page number:

1052

Abstract

We proposed an extended form of the Govindarajulu and Barnett margin of error (MOE) equation and used it with an analysis of variance experimental design to examine the effects of aggregating student evaluations of teaching (SET) ratings on the MOE statistic. The interpretative validity of SET ratings can be questioned when the number of students enrolled in a course is low or when the response rate is low. A possible method of improving interpretative validity is to aggregate SET ratings data from two or more courses taught by the same instructor. Based on non-parametric comparisons of the generated MOE, we found that aggregating course evaluation data from two courses reduced the MOE in most cases. However, significant improvement was only achieved when combining course evaluation data for the same instructor for the same course. Significance did not hold when combining data from different courses. We discuss the implications of our findings and provide recommendations for practice.

Keywords

Margin of error; Student evaluations of teaching; Interpretative validity

Disciplines

Education | Higher Education | Physical Sciences and Mathematics | Statistics and Probability

Language

English

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