Purpose of the present study is to investigate distribution of aberrant response patterns across gender, school type, and graduation status (at last grade of high school, recently graduated, etc.) using person-response curves (PRC).

In multiple-choice tests, unexpected behaviors of examinees are considered to be a threat for validity. These behaviors of responses – also called aberrant responses – may stem from cheating, guessing, fatigue or careless, etc. of examinees. For example, if a low-ability examinee answers the hardest items in a test correctly, this can be used a trigger for suspicion of guessing or cheating. Another examinee may give wrong answers to the easiest items in a test and this may indicate a careless person.

One of the methods to investigate individual aberrancy is called person-response curve and proposed by Trabin and Weiss (1983). PRC is an Item Response Theory (IRT) based methodology and relates probability to answer correctly to a group of items with item difficulty. In this approach, discrepancy between observed and expected PRCs is investigated by using a chi-square statistic. Observed curves can be obtained by calculating proportions of correct answer in each strata. To construct expected PRC, items are ordered according to their difficulty levels and groups of items called “strata” are formed. Expected PRC provides a norm to make comparisons with observed curve. Then a statistical test was used to detect discrepancy between observed and expected PRCs. Though there are many indices that are used to detect aberrant response patterns, principle advantage of PRCs is that they provide a visual way to interpret aberrancy.

Comparative investigation of aberrant response patterns across subgroups may yield significant information about differences on examinees’ individual behaviors in testing environments.

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