The Effect of Chance Success on Equalization Error in Test Equation Based on Classical Test Theory

Duygu Koçak

doi:https://doi.org/10.29329/ijpe.2020.241.15

Original article | International Journal of Progressive Education 2020, Vol. 16(2) 218-229

The Effect of Chance Success on Equalization Error in Test Equation Based on Classical Test Theory

Duygu Koçak

pp. 218 - 229 | DOI: https://doi.org/10.29329/ijpe.2020.241.15 | Manu. Number: MANU-1910-07-0005

Published online: April 02, 2020 | Number of Views: 185 | Number of Download: 767

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Abstract

The aim of this study was to determine the effect of chance success on test equalization. For this purpose, artificially generated 500 and 1000 sample size data sets were synchronized using linear equalization and equal percentage equalization methods. In the data which were produced as a simulative, a total of four cases were created with no chance success, and three different levels (20%, %25, %33) of chance success and the default chance success were corrected by the correction formula. In the simulated data, four different scenarios have been created that do not include chance success and contain three different success rates (20%, 25%, 33%). Accordingly, the test equalization was performed by using linear equalization and equipercentile equalization methods under two different sample sizes and four different chance success conditions. Weighted mean square error of equating methods was found for each situation, and the method with the lowest weighted mean square error was accepted as the most suitable equating method. At the end of the study, it was found out that; while linear equating is the most suitable method for equating test points with chance success; equipercentile equating is the most suitable method for equating test points without chance success.

Keywords: Test Equating, Linear Equating, Equipercentile Equating, Single Group Design, Chance Cucces

How to Cite this Article?

APA 6th edition
Kocak, D. (2020). The Effect of Chance Success on Equalization Error in Test Equation Based on Classical Test Theory . International Journal of Progressive Education, 16(2), 218-229. doi: 10.29329/ijpe.2020.241.15

Harvard
Kocak, D. (2020). The Effect of Chance Success on Equalization Error in Test Equation Based on Classical Test Theory . International Journal of Progressive Education, 16(2), pp. 218-229.

Chicago 16th edition
Kocak, Duygu (2020). "The Effect of Chance Success on Equalization Error in Test Equation Based on Classical Test Theory ". International Journal of Progressive Education 16 (2):218-229. doi:10.29329/ijpe.2020.241.15.

References

Angoff, W. H. (1971). Scales, Norms and Equivalent Scores. Thorndike, R. L. (Ed.) Educational Measurement, 2nd ed., Washington, D. C. American Council on Education. [Google Scholar]
Araz, G. (2001). Aynı davranışı ölçmeye yönelik kısa cevaplı, üç ve beş Seçenekli çoktan seçmeli testlerin madde ve test özelliklerini şans başarısı ile birlikte incelenmesi. (Unpublished master’s thesis). Hacettepe University, Ankara. [Google Scholar]
Barnard, J. J. (1996). In search for equity in educational measurement: Traditional versus modern equating methods. Paper presented at ASEESA’s National Conference, Pretoria South Africa. [Google Scholar]
Bozdağ, S. (2007). Şans başarısının test eşitlemeye etkisi. (Unpublished master’s thesis). Mersin University, Mersin. [Google Scholar]
Budescu, D. V. (1987). Selecting an equating method: Linear or equipercentile?. Journal of Educational Statistics, 12(1), 33-43. https://doi.org/10.3102/10769986012001033. [Google Scholar] [Crossref]
Cook,L.L., & Eignor, D.R. (1991). NCME instructional module on IRT equating methods. Educational Measurment:Issuse and Practice,10(3),37-45. [Google Scholar]
Crocker, L., & Algina, J. (1986). Introduction to Classical and Modern Test Theory. CBS Collage Publishing, New York. [Google Scholar]
Çelen, Ü. (2002). Şans başarısı için düzeltme formülü kullanılacağına ilişkin yönergenin testin psikometrik özelliklerine etkisinin Araştırılması. (Unpublished master’s thesis) Ankara University, Ankara. [Google Scholar]
Dorans, N.J. (2000). Research Notes: Distinctions Among Classes of Linkages. The College Board, Office of Research and Development. [Google Scholar]
Felan, G.D. (2002). Test equating: Mean, linear, equipercentile and Item Response Theory. Paper presented at the Annual Meeting of the Southwest Educational Research Association, Austin. [Google Scholar]
Gulliksen, H. (1967). Theory of Mental Tests. New York: John Wiley & Sons [Google Scholar]
Hambleton, R. K., & Swaminathan, H. (1985). Item Response Theory: Principles and Applications. Kluwer Academic Publishers Group, Boston [Google Scholar]
Kelecioğlu, H. (1993). Öğrenci seçme sınavı puanlarının eşitlenmesi üzerine bir çalışma. (Unpublished doctoral thesis). Hacettepe University, Ankara. [Google Scholar]
Kim S. H., & Cohen A. S. (2002). A comparison of linking and concurrent calibration under the graded response model. Applied Psychological Measurement, 26, 25-41. https://doi.org/10.1177/0146621602026001002. [Google Scholar] [Crossref]
Koçak, D. (2013). Farklı yönergelerle verilen çoktan seçmeli testlerde yanıtlama davranışlarının incelenmesi. (Unpublished master’s thesis). Ankara University, Ankara. [Google Scholar]
Kolen, M. J. (1988). An NCME instructional module on traditional equating methodology. Educational Measurement: Issues and Practice. 7(4), 29-36. https://doi.org/10.1111/j.1745-3992.1988.tb00843.x. [Google Scholar] [Crossref]
Lee, W.C., & Ban, J.C. (2010). A comparison of IRT linking procedures. Applied Measurement in Education, 23(1), 23-48. https://doi.org/10.1080/08957340903423537. [Google Scholar] [Crossref]
Livingston, S. A.(2004). Equating Test Scores (Without IRT). Educational Testing Service. [Google Scholar]
Masse, L. C., Allen, D., Wilson, M., & Williams, G. (2006). Introducing equating methodologies to compare test scores from two different self-regulation scales. Health Education Research 21(1), 110-120. https://doi.org/10.1093/her/cyl088. [Google Scholar] [Crossref]
Skagg, G. & Lissitz R. W. (1986). An Exploration of the Robustness of Four Test Equating Models. Applied Psychological Measurement. 10, 303-317. https://doi.org/10.1177/014662168601000308. [Google Scholar] [Crossref]
Şahhüseyinoğlu, D. (1998). Sayısal yetenek testlerinde seçenek sayısının test ve madde istatistikleri üzerindeki etkisinin şans başarısı ile birlikte incelenmesi. (Unpublished master’s thesis). Hacettepe University, Ankara. [Google Scholar]
Şahhüseyinoğlu, D. (2005). İngilizce yeterlik sınavı puanlarının üç farklı eşitleme yöntemine göre karşılaştırılması. (Unpublished doctoral thesis). Hacettepe University, Ankara. [Google Scholar]
Tanguma, J. (2000). Equating test scores using linear method. Paper presented at the Annual Meeting of the Southwest Educational Research Association, Dallas. [Google Scholar]
Telli, A. (1993). Şans başarısının madde türlerindeki madde ve test istatistiklerine etkisi. (Unpublished mater’s thesis). Hacettepe University, Ankara. [Google Scholar]
Thorndike, R.L. (1982). Aplied Psychometrics. Houghton Mifflin Company, Boston. [Google Scholar]
Tsai, T.H. (1997). Estimating minumum sample sizes in random groups equating. Poster presented at the Annual Meeting of the National Council on measurement in Education, Chicago. [Google Scholar]
Turgut, F. (1971). Şans Başarısının Test Puvanlarına Etkisi, ODTÜ Yayınları, Ankara. [Google Scholar]
Woldbeck, T. (1998). Basic concepts in modern methods of test equating. Paper presented at the Annual Meeting of the Southwest Psychological Association, New Orleans. [Google Scholar]
Zeng, L.(1991). Standard errors of linear equating for the single group design. ACT Research Report Series (4). [Google Scholar]
Zimmerman D. W., & Williams R. H. (2003). A new look at the influence of guessing on the reliability of multiple-choice tests. Applied Psychological Measurement, 27, 357-371. https://doi.org/10.1177/0146621603254799. [Google Scholar] [Crossref]

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