cloze test

Cloze tests are gap-filling tests designed to measure overall language ability and reading comprehension in a second language. Due to their ease of construction and scoring, cloze tests are widely used in the context of second and foreign language testing. Previous research over the past decades has shown the reliability and validity of cloze tests in different contexts. However, due to the interdependent structure of cloze test items, item response theory models have not been applied to analyze cloze tests. In this research, we apply a method to circumvent the problem of local dependence for analyzing cloze tests with the Rasch model. Using this method, we applied the Rasch model to a cloze test composed of eight passages each containing 8-15 gaps. Findings showed that the Rasch model fits the data and thus it is possible to scale persons and cloze passages on an interval unidimensional scale. The test had a high reliability and was well-targeted to the examinees. Implications of the study are discussed.

Local item dependence (LID) refers to the situation where responses to items in a test or questionnaire are influenced by responses to other items in the test. This could be due to shared prompts, item content similarity, and deficiencies in item construction. LID due to a shared prompt is highly probable in cloze tests where items are nested within a passage. The purpose of this research is to examine the occurrence and magnitude of LID in a cloze test. A cloze test was analyzed with the Rasch model and locally dependent items were identified with the residual correlations. Findings showed that three pairs of items were locally dependent. When these items were removed from the analysis, test reliability dropped but item fit and unidimensionality improved. Removing the three locally dependent items did not affect person ability mean and standard deviation, though. The findings are discussed in terms of LID detection and modeling in the context of cloze test and language testing.

Cloze tests are commonly used in language testing as a quick measure of overall language ability or reading comprehension. A problem for the analysis of cloze tests with item response theory models is that cloze test items are locally dependent. This leads to the violation of the conditional or local independence assumption of IRT models. In this study, a new modeling strategy is suggested to circumvent the problem of local item dependence in cloze tests. This strategy involves identifying locally dependent items in the first step and combining them into polytomous items in the second step. Finally, partial credit model is applied to the combination of dichotomous and polytomous items. Our findings showed that the new strategy results in a better model-data fit than the dichotomous model where dependence is ignored but with a lower reliability. Results also indicated that the person and item parameters from the two models highly correlate. The findings are discussed in light of the literature on managing local dependence in educational tests.