Positive student achievement and growth results for students in New York suggest that improvements to the teacher evaluation process that emphasize the importance of strong evaluation procedures, the systematic collection of evidence of teacher performance, and the use of data to inform the process, have promise for improving educator effectiveness far more than a narrower punitive approach.

This study examined the utility of response time‐based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid‐guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent unmotivated test taking behavior.

In this podcast, Nate Jensen discusses the value of assessments aligned to the Common Core State Standards and the misconceptions that accompanied the implementation of new assessments in some states.

This article describes the decisions made in the development of CATs that influence and might threaten content alignment. It outlines a process for evaluating alignment that is sensitive to these threats and gives an empirical example of the process.

Predictive analytics in education can offer a benefit as long as educators heed the differences between how the tools are used in industry and how they should be used differently in schooling. Perhaps most important, teachers already know a great deal about their students — far more than an investor knows about a stock or a baseball scout about an up-and-coming pitcher.

The nearly 10 million English Language Learners (ELLs) represent the fastest-growing segment of the US’s public school student population. While research continually finds that ELL parents, generally speaking, place a high value on their children’s education, many immigrant, refugee, and ELL parents experience their relationships with their children’s schools very differently from mainstream English-speaking families.

Modeling student growth has been a federal policy requirement under No Child Left Behind (NCLB). In addition to tracking student growth, the latest Race To The Top (RTTP) federal education policy stipulates the evaluation of teacher effectiveness from the perspective of added value that teachers contribute to student learning and growth. Student growth modeling and teacher value-added modeling are complex.