TestGardener: A Program for Optimal Scoring and Graphical Analysis
The aim of this paper is to demonstrate how to use TestGardener to analyze testing data with various item types and explain some main displays. TestGardener is a software designed to aid the development, evaluation, and use of multiple choice examinations, psychological scales, questionnaires, and similar types of data. This software implements the optimal scoring of binary and multi-option items, and uses spline smoothing to obtain item characteristics curves (ICCs) that better fit the real data. Using TestGardner does not require any programming skill or formal statistical knowledge, which will make optimal scoring and item response theory more approachable for test analysts, test developers, researchers, and general public.
KeywordsItem response theory Graphical analysis software Optimal scoring Spline smoothing
This research was funded by the Swedish Research Council (grant. 2014-578).
- Laroche, M., Chankon, K., & Tomiuk, M. (1999). Irt-based item level analysis: an additional diagnostic tool for scale purification. In J. E. Arnould, L. M. Scott (Eds.) Advances in consumer research (Vol 26, pp. 141–149). Provo, UT: Association for Consumer Research.Google Scholar
- Liane, P. (1995). A comparison of item parameter estimates and ICCs produced with TESTGRAF and BILOG under different test lengths and sample sizes. The University of Ottawa, thesis.Google Scholar
- Nering, M. L., & Ostini, R. (2010). Handbook of polytomous item response theory models. New York: Taylor and Francis.Google Scholar
- Ramsay, J. O. (1995). TestGraf—a program for the graphical analysis of multiple choice test and questionnaire data [computer software]. Montreal: McGill University.Google Scholar
- Ramsay, J. O. & Wiberg, M. (2017b). Breaking through the sum score barrier. (pp. 151–158). Paper presented at the International Meeting of the Psychometric Society, Asheville: NC, July 11–15.Google Scholar
- Sachs, J., Law, Y., & Chan, C. K. (2003). A nonparametric item analysis of a selected item subset of the learning process questionnaire. British Journal of Educational Psychology 73(3), 395–423.Google Scholar
- Wiberg, M., Ramsay, J. O., & Li, J. (2018). Optimal scores as an alternative to sum scores. In: M. Wiberg, S. Culpepper, R. Janssen, J. González, D. Molenaar (eds) Quantitative Psychology. IMPS 2017. Springer Proceedings in Mathematics & Statistics, vol 233. Cham: Springer.Google Scholar