Related Experiment Video
Updated: Aug 17, 2026

Qualitative and Quantitative Validation of Tools with Rating Scales Aimed at Assessing the Quality of University Service-Learning
Published on: August 29, 2025
Equating student satisfaction measures
Svetlana A Beltyukova1, Gregory E Stone, Christine M Fox
1University of Toledo, Mail Stop 404, 2809 W. Bancroft St., Toledo, OH 43606, USA. sbeltyu@utoledo.edu
Abstract:
Colleges and universities conduct student satisfaction studies for many important policy making reasons. However the differences in instrumentation and the use of students' self-reported ratings of satisfaction makes such decisions sample-, instrument-, and institution-dependent. A common metric of student satisfaction would assist decision makers by providing a richness of information not typically obtained. The present study investigated the extent to which two nationally known instruments of student satisfaction could be scaled on the same quantitative metric. Pseudo-common item equating (Fisher, 1997) based on five link items of low and high endorsability enabled comparisons of "similar, but not identical items, from different instruments, calibrated on different samples" (p. 87). Results suggest that both instruments measured similar constructs and could be reasonably used to create a single, common metric. While samples used in the experiment were less than ideal, results clearly demonstrated the usefulness and reasonability of the pseudo-common item equating process.
Related Concept Videos
Surveys
Reliability and Validity
Ratio Level of Measurement
A set of data measured using the ratio scale takes care of the ratio problem and provides complete information. Ratio scale data are like interval scale data, except they have a zero point and ratios can be calculated. For...
Review and Preview
Percentiles are a type of fractile that partition data into...
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Comparing Experimental Results: Student's t-Test