Identifying Guessing in English Language Tests via Rasch Fit Statistics: An Exploratory Study

Abstract

This article explores the issue of identifying guessers – with a specific focus on multiple-choice tests. Guessing has long been considered a problem due to the fact that it compromises validity. A test taker scoring higher than they should through guessing does not provide a picture of their actual ability. After an initial description of issues associated with guessing, the article then outlines approaches which have been taken to either discourage test takers from guessing or which attempt statistically to handle the problem. From this, the article moves to a novel way of identifying potential guessers: from the post hoc use of Rasch fit statistics. Two datasets, each consisting of approximately 200 beginner level English language test takers were split into two. In each dataset, half the test takers’ answers were randomised – to approximate guessing. Results obtained via a Rasch analysis of the data was then passed to an analyst who used the Rasch fit statistics to identify possible guessers. On each dataset, 80% of guessers were identified.