NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Wu, Haiyan; Liang, Xinya; Yürekli, Hülya; Becker, Betsy Jane; Paek, Insu; Binici, Salih – Journal of Psychoeducational Assessment, 2020
The demand for diagnostic feedback has triggered extensive research on cognitive diagnostic models (CDMs), such as the deterministic input, noisy output "and" gate (DINA) model. This study explored two Q-matrix specifications with the DINA model in a statewide large-scale mathematics assessment. The first Q-matrix was developed based on…
Descriptors: Mathematics Tests, Cognitive Measurement, Models, Test Items
Shin, Chingwei David; Chien, Yuehmei; Way, Walter Denny – Pearson, 2012
Content balancing is one of the most important components in the computerized adaptive testing (CAT) especially in the K to 12 large scale tests that complex constraint structure is required to cover a broad spectrum of content. The purpose of this study is to compare the weighted penalty model (WPM) and the weighted deviation method (WDM) under…
Descriptors: Computer Assisted Testing, Elementary Secondary Education, Test Content, Models
Kobrin, Jennifer L.; Kim, Rachel; Sackett, Paul – College Board, 2011
There is much debate on the merits and pitfalls of standardized tests for college admission, with questions regarding the format (multiple-choice versus constructed response), cognitive complexity, and content of these assessments (achievement versus aptitude) at the forefront of the discussion. This study addressed these questions by…
Descriptors: College Entrance Examinations, Mathematics Tests, Test Items, Predictive Validity
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Graf, Edith Aurora; Peterson, Stephen; Steffen, Manfred; Lawless, René – ETS Research Report Series, 2005
We describe the item modeling development and evaluation process as applied to a quantitative assessment with high-stakes outcomes. In addition to expediting the item-creation process, a model-based approach may reduce pretesting costs, if the difficulty and discrimination of model-generated items may be predicted to a predefined level of…
Descriptors: Psychometrics, Accuracy, Item Analysis, High Stakes Tests