Affiliation:
1. KASTAMONU ÜNİVERSİTESİ
2. PAMUKKALE ÜNİVERSİTESİ
Abstract
The dimensionality is one of the most investigated concepts in the psychological assessment, and there are many ways to determine the dimensionality of a measured construct. The Automated Item Selection Procedure (AISP) and the DETECT are non-parametric methods aiming to determine the factorial structure of a data set. In the current study, dimensionality results provided by the two methods were compared based on the original factorial structure defined by the scale developers. For the comparison of the two methods, the data was obtained by implementing a scale measuring academic dishonesty levels of bachelor students. The scale was conducted on junior students studying at a public and a private university. The dataset was analyzed by using the AISP and DETECT analyses. The “mokken” and “sirt” packages on the R program were utilized for the AISP and DETECT analyses, respectively. The similarities and differences between the findings provided by the methods were analyzed depending on the original factor structure of the scale verified by the scale developers.
Publisher
International Journal of Assessment Tools in Education
Reference56 articles.
1. Ackerman, T.A., Gierl, M.A., & Walker, C.M. (2003). Using multidimensional item response theory to evaluate educational and psychological tests. Educational Measurement: Issues and Practice, 22(1), 37-53. https://doi.org/10.1111/j.1745-3992.2003.tb00136.x
2. Antino, M., Alvarado, J.M., Asún, R.A., & Bliese, P. (2020). Rethinking the exploration of dichotomous data: Mokken scale analysis versus factorial analysis. Sociological Methods Research, 49(4), 839-867. https://doi.org/10.1177/0049124118769090
3. Cavalini, P.M. (1992). It’s an ill wind that brings no good. Studies on odour annoyance and the dispersion of odorant concentrations from industries [Unpublished doctoral dissertation]. University of Groningen, The Netherlands.
4. Crocker, L., & Algina, J. (1986). Introduction to classical and modern test theory. Cengage Learning.
5. Finch, H. (2010). Item parameter estimation for the MIRT model bias and precision of confirmatory factor analysis based models. Applied Psychological Measurement 34(1), 10 26. https://doi.org/10.1177/0146621609336112