What are the “Standards for Teacher Competence in Educational Assessment of Students”? In what domains do teachers have the greatest knowledge of measurement? Where are they least strong? Do teachers with measurement training show greater knowledge than teachers without such training?

Practitioners typically face situations in which examinees have not responded to all test items. This study investigated the effect on an examinee's ability estimate when an examinee is presented an item, has ample time to answer, but decides not to respond to the item. Three approaches to ability estimation (biweight estimation, expected a posteriori, and maximum likelihood estimation) were examined. A Monte Carlo study was performed and the effect of different levels of omissions on the simulee's ability estimates was determined. Results showed that the worst estimation occurred when omits were treated as incorrect. In contrast, substitution of 0.5 for omitted responses resulted in ability estimates that were almost as accurate as those using complete data. Implications for practitioners are discussed.

The No Child Left Behind Act of 2001 (NCLB) requires states to have developed content standards in Reading and Mathematics, and to employ some form of statewide assessment. For accurate inferences about student achievement and growth over time, these assessments must measure the knowledge and skills deemed valuable and described in these content standards. This article provides a description of models for evaluating the degree of alignment between assessments and content standards. Challenges to these models are described and discussed, and solutions are suggested. Two empirical alignment studies are summarized and implications of using different alignment models for aligning commercially available tests with content standards are also discussed.

Since 1971 there have been a number of studies in which a cut score has been set using a method proposed by Angoff (1971). In this method, each member of a panel of judges estimates for each test question the proportion correct for a specific target group of examinees. Prior and contemporary research suggests that this is a difficult task for judges. Angoff also proposed that judges simply indicate whether or not an examinee from the target group will be able to answer each question correctly (the yes/no method). We report on the results of two studies that compare a yes/no estimation with a proportion correct estimation. The two studies demonstrate that both methods produce essentially equal cut scores and that judges find the yes/no method more comfortable to use than the estimated proportion correct method.