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11.
This study investigated the performance of four widely used data-collection designs in detecting test-mode effects (i.e., computer-based versus paper-based testing). The experimental conditions included four data-collection designs, two test-administration modes, and the availability of an anchor assessment. The test-level and item-level results were analyzed with inferential statistics and multidimensional scaling, respectively. The test-level results supported the superiority of the single-group counterbalanced design and the random-groups design over the single-group design without counterbalancing and the anchor test design in the recovery of the actual test-mode effects. Analysis at the item level revealed the presence of a two-dimensional solution, with the data-collection design contributing significant variability over and beyond the test mode. 相似文献
12.
In low-stakes assessments, some students may not reach the end of the test and leave some items unanswered due to various reasons (e.g., lack of test-taking motivation, poor time management, and test speededness). Not-reached items are often treated as incorrect or not-administered in the scoring process. However, when the proportion of not-reached items is high, these traditional approaches may yield biased scores and thereby threatening the validity of test results. In this study, we propose a polytomous scoring approach for handling not-reached items and compare its performance with those of the traditional scoring approaches. Real data from a low-stakes math assessment administered to second and third graders were used. The assessment consisted of 40 short-answer items focusing on addition and subtraction. The students were instructed to answer as many items as possible within 5 minutes. Using the traditional scoring approaches, students’ responses for not-reached items were treated as either not-administered or incorrect in the scoring process. With the proposed scoring approach, students’ nonmissing responses were scored polytomously based on how accurately and rapidly they responded to the items to reduce the impact of not-reached items on ability estimation. The traditional and polytomous scoring approaches were compared based on several evaluation criteria, such as model fit indices, test information function, and bias. The results indicated that the polytomous scoring approaches outperformed the traditional approaches. The complete case simulation corroborated our empirical findings that the scoring approach in which nonmissing items were scored polytomously and not-reached items were considered not-administered performed the best. Implications of the polytomous scoring approach for low-stakes assessments were discussed. 相似文献