Developing Computerized Versions of Paper-and-Pencil Tests: Mode Effects for Passage-Based Tests

As testing moves from paper-and-pencil administration toward computerized administration, how to present tests on a computer screen becomes an important concern. Of particular concern are tests that contain necessary information that cannot be displayed on screen all at once for an item. Ideally, the method of presentation should not interfere with examinee performance on the test. Examinees should perform similarly on an item regardless of the mode of administration. This paper discusses the development of a computer interface for passage-based, multiple-choice tests. Findings are presented from two studies that compared performance across computer and paper administrations of several fixed-form tests. The effect of computer interface changes made between the two studies is discussed. The results of both studies showed some performance differences across modes. Evaluations of individual items suggested a variety of factors that could have contributed to mode effects. Although the observed mode effects were in general small, overall the findings suggest that it would be beneficial to develop an understanding of factors that can influence examinee behavior and to design a computer interface accordingly, to ensure that examinees are responding to test content rather than features inherent in presenting the test on computer

The Effect of Using Item Parameters Calibrated from Paper Administrations in Computer Adaptive Test Administrations

Computer administered tests are becoming increasingly prevalent as computer technology becomes more readily available on a large scale. For testing programs that utilize both computer and paper administrations, mode effects are problematic in that they can result in examinee scores that are artificially inflated or deflated. As such, researchers have engaged in extensive studies of whether scores differ across paper and computer presentations of the same tests. The research generally seems to indicate that the more complicated it is to present or take a test on computer, the greater the possibility of mode effects. In a computer adaptive test, mode effects may be a particular concern if items are calibrated using item responses obtained from one administration mode (i.e., paper), and those parameters are then used operationally in a different administration mode (i.e., computer). This paper studies the suitability of using parameters calibrated from a paper administration for item selection and scoring in a computer adaptive administration, for two tests with lengthy passages that required navigation in the computer administration. The results showed that the use of paper calibrated parameters versus computer calibrated parameters in computer adaptive administrations had small to moderate effects on the reliability of examinee scores, at fairly short test lengths. This effect was generally diminished for longer test lengths. However, the results suggest that in some cases, some loss in reliability might be inevitable if paper-calibrated parameters are used in computer adaptive administrations

Item response theory for scores on tests including polytomous items with ordered responses

Item response theory (IRT) provides procedures for scoring tests including any combination of rated constructed-response and keyed multiple-choice items, in that each response pattern is associated with some modal or expected a posteriori estimate of trait level. However, various considerations that frequently arise in large-scale testing make response-pattern scoring an undesirable solution. Methods are described based on IRT that provide scaled scores, or estimates of trait level, for each summed score for rated responses, or for combinations of rated responses and multiple-choice items. These methods may be used to combine the useful scale properties of IR’r-based scores with the practical virtues of a scale based on a summed score for each examinee. Index terms: graded response model, item response theory, ordered responses, polytomous models, scaled scores