Journals / Hacettepe Üniversitesi Eğitim Fakültesi Dergisi / 2019 / Cilt: 34 - Sayı: 2

The Measurement Invariance of University Students’ Ratings of Instruction

Üniversitede Öğretimi Değerlendirme Puanlarının Ölçme Değişmezliği

Pages
402–417
Publication Date
2022-10-19
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It seems that comparing the rating results across the classrooms and courses independent of the achievement levels of the students may be misleading especially for the high-stake decisions since the origin of the scale is not the same across high and low achieving groups.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The invariance in the scores of student rating of instruction was studied across high and low achieving classrooms.
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Key Findings & Data:The data included 625 classrooms.
💡
Conclusion & Impact:It seems that comparing the rating results across the classrooms and courses independent of the achievement levels of the students may be misleading especially for the high-stake decisions since the origin of the scale is not the same across high and low achieving groups.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

The invariance in the scores of student rating of instruction was studied across high and low achieving classrooms. Achievement levels were determined by the two criteria such as self-reported expected grades and end of semester grades. The data included 625 classrooms. The equality of (i) factorial structure, (ii) factor loadings, (iii) item intercepts, and (iv) error variances of the 7 item rating scale were studied across these groups. With respect to self-reported expected grades, high and low achieving classes produced invariant scale characteristics except strict invariance. On the other hand, with respect to end of semester grades, full equality in item intercepts and error variances were not achieved. It seems that comparing the rating results across the classrooms and courses independent of the achievement levels of the students may be misleading especially for the high-stake decisions since the origin of the scale is not the same across high and low achieving groups.

Özet

Bu çalışmada üniversite düzeyinde öğretimi değerlendirme anketi puanlarının üst ve alt başarı grupları arasındaki ölçme değişmezliği incelenmiştir. Başarı düzeyleri öğrencilerin not beklentileri ve dersin sene sonu başarı ortalaması şeklinde iki ölçüt ile belirlenmiştir. Çalışmanın verisi 625 dersten oluşmaktadır. Yedi maddelik anketin (i) faktör yapısı, (ii) faktör yükleri, (iii) madde ortalamaları ve (iv) hata varyanslarının değişmezliği iki başarı grubu arasında analiz edilmiştir. Öğrencilerin not beklentilerine göre, üst ve alt başarı grupları hata varyanslarının değişmezliği dışında değişmez ölçek özellikleri görülmüştür. Diğer yandan, sene sonu notlarına göre yapılan inceleme sonucunda, madde ortalamaları ve hata varyanslarında tam değişmezlik gözlemlenmemiştir. Çalışma sonuçları öğretim elemanı değerlendirme puanlarının sınıflar ve dersler arasında başarı düzeylerinden bağımsız olarak karşılaştırılmasının yanıltıcı sonuçlar doğurabileceğini göstermektedir. Üst ve alt başarı gruplarının ölçek başlangıç noktaları farklı olduğu için bu durum özellikle ciddi kararlar alınması aşamalarında daha önem kazanmaktadır.

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Cite This Article

BERBEROĞLU, G., KALENDER, İ. (2022). The Measurement Invariance of University Students’ Ratings of Instruction. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, Cilt: 34 - Sayı: 2, 402–417. https://ajindex.com/articles/532236

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References (12)

  1. Ackerman, D., Gross, B. L., & Vigneron, F. (2009). Peer observation reports and student evaluations of teaching: Who are the experts? Alberta Journal of Educational Research, 55(1), 18-39.
  2. Baas, M., De Dreu, C. K. W., & Nijstad, B. A. (2011). When prevention promotes creativity: the role of mood, regulatory focus, and regulatory closure. Journal of Personality and Social Psychology, 100, 794–809.
  3. Benton, S. L. & Cashin, W. E. (2012). Student ratings of teaching: A summary of research and literature. (No. 50). Manhattan, KS: IDEA Center. Benton, S. L., Duchon, D., & Pallett, W. H. (2013). Validity of self-reported student ratings of instruction. Assessment & Evaluation in Higher Education, 38, 377-389.
  4. Bowman, N. A. (2010). Can 1st-year college students accurately report their learning and development? American Educational Research Journal, 47(2), 466-496.
  5. Brockx, B., Spooren, P., & Mortelmans, D. (2011). Taking the grading leniency story to the edge. The influence of student, teacher, and course characteristics on student evaluations of teaching in higher education. Educational Assessment, Evaluation and Accountability, 23(4), 289-306.
  6. Byrne, B. M. (2004). Testing for multigroup invariance using AMOS graphics: A road less traveled. Structural Equation Modeling, 11, 272–300.
  7. Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming. Routledge. Byrne, B. M., Shavelson, R. J., & Muthén, B. (1989). Testing for the equivalence of factor covariance and mean structures: the issue of partial measurement invariance. Psychological Bulletin, 105, 456-466.
  8. Bryant, F. B., & Satorra, A. (2012). Principles and practice of scaled difference chi-square testing. Structural Equation Modeling, 19(3), 372-398.
  9. Clayson, D. E. (2009). Student evaluations of teaching: are they related to what students learn?: a meta-analysis and review of the literature. Journal of Marketing Education, 31, 16-30.
  10. Cole, J. S., & Gonyea, R. M. (2010). Accuracy of self-reported sat and act test scores: Implications for research. Research in Higher Education, 51(3), 305–319.
  11. Cruse, D. B. (1987). Student evaluations of the university professor: caveat professor. Higher Education, 16, 723- 737. Dimitrov, D. M. (2010). Testing for factorial invariance in the context of construct validation. Measurement and Evaluation in Counselling and Development, 43(2), 121-149.
  12. Ehie, I. C., & Karathanos, K. (1994). Business faculty performance evaluation based on the n