Modeling Partial Knowledge on Multiple‐Choice Items Using Elimination Testing. Issue 2 (3rd June 2019)

• Record Type: Journal Article
• Authors: Wu, Qian; De Laet, Tinne; Janssen, Rianne
• Is Part Of: Journal of educational measurement. Volume 56:Issue 2(2019)
• Page Start: 391
• Page End: 414
• Publication Date: 2019-06-03
• Subjects: multiple‐choice items -- elimination testing -- partial credit model -- scoring group analysis -- IRT; Educational tests and measurements -- Periodicals; 371.2605
• DOI: 10.1111/jedm.12213
• Languages: English
• ISSNs: 0022-0655

Abstract

Abstract: Single‐best answers to multiple‐choice items are commonly dichotomized into correct and incorrect responses, and modeled using either a dichotomous item response theory (IRT) model or a polytomous one if differences among all response options are to be retained. The current study presents an alternative IRT‐based modeling approach to multiple‐choice items administered with the procedure of elimination testing, which asks test‐takers to eliminate all the response options they consider to be incorrect. The partial credit model is derived for the obtained responses. By extracting more information pertaining to test‐takers' partial knowledge on the items, the proposed approach has the advantage of providing more accurate estimation of the latent ability. In addition, it may shed some light on the possible answering processes of test‐takers on the items. As an illustration, the proposed approach is applied to a classroom examination of an undergraduate course in engineering science.