Psychometric Properties of Student Evaluation of Teachers’ Performance Scale: Evidence from Debre Markos University Students’ Evaluation Dataset

• Main Authors: Muluye Getie Ayaneh, Askalemariam Adamu Dessie, Dimetros Molla Fetene
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Education Research International
• Online Access: http://dx.doi.org/10.1155/2021/5543317

Introduction. Student evaluation of teachers’ effectiveness is one of the most common tools used as a measure of teaching performance and accountability by various universities across the globe. The major purpose of this study was to evaluate the validity and underlying structure of students’ evaluation of the higher education teaching effectiveness scale used by all public universities in Ethiopia. Methodology. Data collected from 1397 students at Debe Markos University were used for this analysis. Cronbach’s alpha values and average interitem correlation were used to study the internal consistency reliability of the scale. Composite reliability, average variance extracted, hetero trait-mono-trait ratio, maximum shared variance, average shared variance, and interconstruct correlations were used to assess the construct validity of the scale, and exploratory factor analysis and confirmatory factor analysis were performed with 20 items to test the hypothesis which introduced a four-dimensional construct for teachers’ evaluation scale. We used different goodness-of-fit indices to measure the fit of the models. Results. The scale was shown to have good internal consistency and convergent validity but lacked discriminant validity. Furthermore, confirmatory factor analysis indicated that the four-factor model produced inadequate fit indices, revealing that the original factor structure of the scale changed. Conclusions. The results showed that Student Evaluation of Teaching Effectiveness did not measure what it was supposed to be measuring. Moreover, the exploratory factor analysis and confirmatory factor analysis results indicate that a two-dimensional model is better than the four-dimensional model to explain the data structure, which places limitations on its use.