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Dergiler / International Journal of Assessment Tools in Education / 2016 / Cilt: 3 - Sayı: 1

Higher Education End-of-Course Evaluations: Assessing the Psychometric Properties Utilizing Exploratory Factor Analysis and Rasch Modeling Approaches

Angela K. TOMBARİ
Kelly D. BRADLEY
Eric M. SNYDER
Sayfa
3–22
Yayın Tarihi
2022-10-18
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

However, the lack of precise targeting of item difficulty to person ability combined with the low person separation index renders rank-ordering professors according to minuscule differences in overall subscale scores a highly questionable practice.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This paper offers a critical assessment of the psychometric properties of a standard higher education end-of-course evaluation.
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Temel Bulgular & Veri:Using both exploratory factor analysis (EFA) and Rasch modeling, the authors investigate the (a) an overall assessment of dimensionality using EFA, (b) a secondary assessment of dimensionality using a principal components analysis (PCA) of the residuals when the items are fit to the Rasch model, and (c) an assessment of item-level properties using item-level statistics provided when the items are fit to the Rasch model.
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Sonuç & Katkı:However, the lack of precise targeting of item difficulty to person ability combined with the low person separation index renders rank-ordering professors according to minuscule differences in overall subscale scores a highly questionable practice.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Course Evaluations · Rasch · Exploratory Factor Analysis

Özet

This paper offers a critical assessment of the psychometric properties of a standard higher education end-of-course evaluation. Using both exploratory factor analysis (EFA) and Rasch modeling, the authors investigate the (a) an overall assessment of dimensionality using EFA, (b) a secondary assessment of dimensionality using a principal components analysis (PCA) of the residuals when the items are fit to the Rasch model, and (c) an assessment of item-level properties using item-level statistics provided when the items are fit to the Rasch model. The results support the usage of the scale as a supplement to high-stakes decision making such as tenure. However, the lack of precise targeting of item difficulty to person ability combined with the low person separation index renders rank-ordering professors according to minuscule differences in overall subscale scores a highly questionable practice.

Abstract

This paper offers a critical assessment of the psychometric properties of a standard higher education end-of-course evaluation. Using both exploratory factor analysis (EFA) and Rasch modeling, the authors investigate the (a) an overall assessment of dimensionality using EFA, (b) a secondary assessment of dimensionality using a principal components analysis (PCA) of the residuals when the items are fit to the Rasch model, and (c) an assessment of item-level properties using item-level statistics provided when the items are fit to the Rasch model. The results support the usage of the scale as a supplement to high-stakes decision making such as tenure. However, the lack of precise targeting of item difficulty to person ability combined with the low person separation index renders rank-ordering professors according to minuscule differences in overall subscale scores a highly questionable practice.

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Bu Makaleye Atıf Yap

TOMBARİ, A. K., BRADLEY, K. D., SNYDER, E. M. (2022). Higher Education End-of-Course Evaluations: Assessing the Psychometric Properties Utilizing Exploratory Factor Analysis and Rasch Modeling Approaches. International Journal of Assessment Tools in Education, Cilt: 3 - Sayı: 1, 3–22. https://ajindex.com/articles/540262

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Kaynakça (13)

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