Optimal test design involves the application of an item selection heuristic to construct a test to fit the target information function in order that the standard error of the test can be controlled at different regions of the ability continuum. The real data simulation study assessed the efficiency of binary programming in optimal item selection by comparing the degree in which the obtained test information was approximated to different target information functions with a manual heuristic. The effects of imposing a content balancing constraint was studied in conventional, two-stage and adaptive tests designed using the automated procedure. Results showed that the automated procedure improved upon the manual procedure significantly when a uniform target information function was used. However, when a peaked target information function was used, the improvement over the manual procedure was marginal. Both procedures were affected by the distribution of the item parameters in the item pool. The degree in which the examinee empirical scores were recovered was lower when a content balancing constraint was imposed in the conventional test designs. The effect of uneven item parameter distribution in the item pool was shown by the poorer recovery of the empirical scores at the higher regions of the ability continuum. Two-stage tests were shown to limit the effects of content balancing. Content balanced adaptive tests using optimal item selection was shown to be efficient in empirical score recovery, especially in maintaining equiprecision in measurement over a wide ability range despite the imposition of content balancing constraint in the test design. The study had implications for implementing automated test designs in the school systems supported by hardware and expertise in measurement theory and addresses the issue of content balancing using optimal test designs within an adaptive testing framework.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-8561 |
| Date | 01 January 1993 |
| Creators | Lam, Tit Loong |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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