Assumptions lead to claims about the types of inferences and uses that an assessment system is intended to support. Strong assumptions require strong evidence. This axiom holds true for educational measurement and most other scientific endeavors. The current interest in through year assessments appears to be based on very strong assumptions about the multiple purposes through year assessments may serve. Is there evidence to support these assumptions?

This is the second in a series of three posts on planning for the examination of the validity of scores collected through remote test administration. In the first post, Michelle Boyer and Leslie Keng laid out the reasons why states should be concerned about the effect of remote testing on the comparability of score meaning. In the third post in this series, we will discuss specific challenges to score interpretations for remotely-administered tests.  

This is the first in a series of three posts on planning for the examination of the validity of scores collected through remote test administration. Next up is a discussion of a framework for the types of analyses that will be useful for understanding the degree to which scores are comparable between remotely tested students and students tested in the classroom, what might be done to adjust them if they are not, and the conditions under which data can be collected to support those analyses.

This is the second in a series of posts by our 2020 summer interns and their mentors based on their project and the assessment and accountability issues they addressed this summer. Sandy Student, from the University of Colorado Boulder, and Brian Gong get things started with a two-part series describing their work analyzing the validity arguments for states’ large-scale Next Generation Science Standards (NGSS) assessments.

Once again this year, we are pleased to share posts on CenterLine by our summer interns and their mentors. These posts are based on the project they undertook and the assessment and accountability issues they addressed this summer.

Although so much about the future seems uncertain, we are excited this month to bring a little normalcy into our world by addressing key questions and challenges in educational assessment and accountability through our 2020 summer internship program. This summer, the Center welcomes four advanced doctoral students who will work with the Center’s professionals on projects that will have direct implications for state and national educational policy. Each intern will work with a Center mentor on one major project throughout the summer.

This is the final installment in a three-part series on the future of large-scale state assessment and accountability. Of course, it is impossible to know the future, but forecasts for educational assessment can be informed by examining what has shaped state assessment and accountability in the past. 

This is the second in a three-part series on the future of large-scale state assessment and accountability. Of course, it is impossible to know the future, but forecasts for educational assessment can be informed by examining what has shaped state assessment and accountability in the past.

Testing experts know a lot about how to conduct scoring of students’ written responses to assessment items. Raters are trained under strict protocols to follow scoring rules accurately and consistently. To verify that raters did their job well, we use a few basic score quality measures that center on how well two or more raters agree. These measures of agreement are called inter-rater reliability (IRR) statistics, and they are widely used, perhaps in part because they are easy to understand and apply.