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Journals / International Journal of Assessment Tools in Education / 2022 / Cilt: 9 - Sayı: 3

To what extent are item discrimination values realistic? A new index for two-dimensional structures

Abdullah Faruk KILIÇ
İbrahim UYSAL
Pages
728–740
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

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

Accordingly, using this new item discrimination index could be recommended to researchers when investigating item discrimination in two-dimensional structures.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test.
📊
Key Findings & Data:Based upon the results of the study it can be claimed that the proposed item discrimination index proves acceptable performance for two-dimensional structures.
💡
Conclusion & Impact:Accordingly, using this new item discrimination index could be recommended to researchers when investigating item discrimination in two-dimensional structures.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Item discrimination · Multi-dimensional structures · Classical test theory

Abstract

Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the factors to which that item belongs; however, getting a general overview of the entire test is impossible. Based on this problem, this study aims to recommend a new index to investigate item discrimination in two-dimensional structures through a Monte Carlo simulation. The new item discrimination index is evaluated by identifying sample size, item discrimination value, inter-factor correlation, and the number of categories. Based upon the results of the study it can be claimed that the proposed item discrimination index proves acceptable performance for two-dimensional structures. Accordingly, using this new item discrimination index could be recommended to researchers when investigating item discrimination in two-dimensional structures.

Özet

Most researchers investigate the corrected item-total correlation of items when analyzing item discrimination in multi-dimensional structures under the Classical Test Theory, which might lead to underestimating item discrimination, thereby removing items from the test. Researchers might investigate the corrected item-total correlation with the factors to which that item belongs; however, getting a general overview of the entire test is impossible. Based on this problem, this study aims to recommend a new index to investigate item discrimination in two-dimensional structures through a Monte Carlo simulation. The new item discrimination index is evaluated by identifying sample size, item discrimination value, inter-factor correlation, and the number of categories. Based upon the results of the study it can be claimed that the proposed item discrimination index proves acceptable performance for two-dimensional structures. Accordingly, using this new item discrimination index could be recommended to researchers when investigating item discrimination in two-dimensional structures.

🔖

Cite This Article

KILIÇ, A. F., UYSAL, İ. (2022). To what extent are item discrimination values realistic? A new index for two-dimensional structures. International Journal of Assessment Tools in Education, Cilt: 9 - Sayı: 3, 728–740. https://ajindex.com/articles/540037

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References (11)

  1. Ak, M.O., & Alpullu, A. (2020). Alpak akış ölçeği geliştirme ve Doğu Batı üniversitelerinin karşılaştırılması [Alpak flow scale development and comparison of east west universities]. E Journal of New World Sciences Academy, 15(1), 1 16. https://doi.org/10.12739/NWSA.2019.14.4.2B0122
  2. Akyıldız, S. (2020). Eğitim programı okuryazarlığı kavramının kavramsal yönden analizi: Bir ölçek geliştirme çalışması [A conceptual analysis of curriculum literacy concept: A study of scale development]. Electronic Journal of Social Sciences, 19(73), 315–332. https://doi.org/10.17755/esosder.554205
  3. Bandalos, D.L., & Leite, W. (2013). Use of Monte Carlo studies in structural equation modeling research. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (2nd ed.). Information Age. Bazaldua, D.A.L., Lee, Y.-S., Keller, B., & Fellers, L. (2017). Assessing the performance of classical test theory item discrimination estimators in Monte Carlo simulations. Asia Pacific Education Review, 18, 585–598. https://doi.org/10.1007/s12564-017-9507-4
  4. Brown, J.D. (1988). Tailored cloze: Improved with classical item analysis techniques. Language Testing, 5(1), 19–31. https://doi.org/10.1177/026553228800500102
  5. Cho, S.-J., Li, F., & Bandalos, D.L. (2009). Accuracy of the parallel analysis procedure with polychoric correlations. Educational and Psychological Measurement, 69(5), 748–759. https://doi.org/10.1177/0013164409332229
  6. Crocker, L., & Algina, J. (2008). Introduction of classical and modern test theory. Cengage Learning. Cureton, E.E. (1957). The upper and lower twenty-seven per cent rule. Psychometrika, 22, 293-296. https://doi.org/10.1007/BF02289130
  7. Curran, P.J., West, S.G., & Finch, J.F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1(1), 16–29. https://doi.org/10.1037/1082-989X.1.1.16
  8. Çalışkan, A. (2020). Kriz yönetimi: Bir ölçek geliştirme çalışması [Crisis management: A scale development study]. Journal of Turkish Social Sciences Research, 5(2), 106–120.
  9. Deakin, R. (1998). 3-D coordinate transformations. Surveying and Land Information Systems, 58(4), 223–234.
  10. DeVellis, R.F. (2006). Classical test theory. Medical Care, 44(11), 50 59. https://doi.org/10.1097/01.mlr.0000245426.10853.30
  11. Fan, X. (1998). Item Response Theory and Classical Test Theory: An empirical comparison of their item/person statistics. Educational and Psychological Measurement, 58(3), 357–381. h