Large amounts of missing data could distort item parameter estimation and lead to biased ability estimates in educational assessments. Therefore, missing responses should be handled properly before estimating any parameters. In this study, two Monte Carlo simulation studies were conducted to compare the performance of four methods in handling…

This study was designed to initiate the process of building professional development learning communities for pre-service math teachers through revealing those teachers' conceptions/beliefs of students' learning and their own learning in China. It examines Chinese pre-service math teachers' conceptions of student learning and their related…

A simulation study was conducted to explore the performance of the linear logistic test model (LLTM) when the relationships between items and cognitive components were misspecified. Factors manipulated included percent of misspecification (0%, 1%, 5%, 10%, and 15%), form of misspecification (under-specification, balanced misspecification, and…

Differential item functioning (DIF) of items has become an important issue in test fairness and equity in large-scale assessments. DIF occurs when subgroups of test takers have equal trait levels but differ in their probabilities of a correct response. DIF items may threaten the validity of test scores for subgroups and can mislead researchers…