Multidimensional scoring evaluates each constructed-response answer from more than one rating dimension and/or trait such as lexicon, organization, and supporting ideas instead of only one holistic score, to help students distinguish between various dimensions of writing quality. In this work, we present a bilevel learning model for combining two…

Adaptive tests are more efficient than fixed-length tests through the use of item response theory; adaptive tests also present students questions that are tailored to their proficiency level. Although the adaptive algorithm is straightforward, developing a multidimensional computer adaptive test (MCAT) measure is complex. Evidence-centered design…

Changes to the design and development of our educational assessments are resulting in the unprecedented demand for a large and continuous supply of content-specific test items. One way to address this growing demand is with automatic item generation (AIG). AIG is the process of using item models to generate test items with the aid of computer…

Testing organization needs large numbers of high-quality items due to the proliferation of alternative test administration methods and modern test designs. But the current demand for items far exceeds the supply. Test items, as they are currently written, evoke a process that is both time-consuming and expensive because each item is written,…

Addresses the potential benefits of using sound in computerized assessments. Describes some current computer uses of the audio channel of communication and outlines a proposed audio computer-based testing framework. Provides some examples of operational and experimental audio tests and reviews some research cautions and recommendations. (SLD)

The utility of item response theory (IRT) models in computerized adaptive tests is considered. Measurement questions that have been answered using IRT, and those that might be overlooked because of IRT, are reviewed. Areas in which fuller use of IRT could improve adaptive testing practices are identified. (SLD)