Research Article

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

Volume: 9 Number: 3 September 30, 2022
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To what extent are item discrimination values realistic? A new index for two-dimensional structures

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.

Keywords

References

  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.
  4. 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
  5. Brown, J.D. (1988). Tailored cloze: Improved with classical item analysis techniques. Language Testing, 5(1), 19–31. https://doi.org/10.1177/026553228800500102
  6. 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
  7. Crocker, L., & Algina, J. (2008). Introduction of classical and modern test theory. Cengage Learning.
  8. Cureton, E.E. (1957). The upper and lower twenty-seven per cent rule. Psychometrika, 22, 293-296. https://doi.org/10.1007/BF02289130

Details

Primary Language

English

Subjects

Other Fields of Education

Journal Section

Research Article

Publication Date

September 30, 2022

Submission Date

April 5, 2022

Acceptance Date

September 1, 2022

Published in Issue

Year 2022 Volume: 9 Number: 3

APA
Kılıç, 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, 9(3), 728-740. https://doi.org/10.21449/ijate.1098757

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