Data visualization
Exploring the educational impacts of COVID-19
2023
By: Greg King
Description
This visualization was developed to provide state-level insights into how students performed on MAP Growth in the 2020ā2021 school year. Assessments are one indicator, among many, of the student impact from COVID-19. Our goal with this tool is to create visible data that informs academic recovery efforts that will be necessary in the 2022 school year and beyond.
See MoreAssociated Research
Related Topics
The potential of adaptive assessment
In this article, the authors explain how CAT provides a more precise, accurate picture of the achievement levels of both low-achieving and high-achieving students by adjusting questions as the testing goes along. The immediate, informative test results enable teachers to differentiate instruction to meet individual students’ current academic needs.
By: Edward Freeman
Topics: Innovations in reporting & assessment, Measurement & scaling, Student growth & accountability policies
The utility of adaptive testing in addressing the problem of unmotivated examinees
This integrative review examines the motivational benefits of computerized adaptive tests (CATs), and demonstrates that they can have important advantages over conventional tests in both identifying instances when examinees are exhibiting low effort, and effectively addressing the validity threat posed by unmotivated examinees.
By: Steven Wise
Topics: Measurement & scaling, Innovations in reporting & assessment, School & test engagement
Effort analysis: Individual score validation of achievement test data
Whenever the purpose of measurement is to inform an inference about a studentās achievement level, it is important that we be able to trust that the studentās test score accurately reflects what that student knows and can do. Such trust requires the assumption that a studentās test event is not unduly influenced by construct-irrelevant factors that could distort his score. This article examines one such factorātest-taking motivationāthat tends to induce a person-specific, systematic negative bias on test scores.
By: Steven Wise
Topics: Measurement & scaling, Innovations in reporting & assessment, School & test engagement
Response time as an indicator of test taker speed: assumptions meet reality
The growing presence of computer-based testing has brought with it the capability to routinely capture the time that test takers spend on individual test items. This, in turn, has led to an increased interest in potential applications of response time in measuring intellectual ability and achievement. Goldhammer (this issue) provides a very useful overview of much of the research in this area, and he provides a thoughtful analysis of the speed-ability trade-off and its impact on measurement.
By: Steven Wise
Topics: Measurement & scaling, Innovations in reporting & assessment, School & test engagement
Modeling student test-taking motivation in the context of an adaptive achievement test
This study examined the utility of response timeābased analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapidāguessing 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.
Topics: Innovations in reporting & assessment, Measurement & scaling, School & test engagement
Are all biases bad? Collaborative grounded theory in developmental evaluation of education policy
By: Ross Anderson, Meg Guerreiro, Jo Smith
Mapping the road to college with the College Explorer tool
NWEA recently launched a new tool called College Explorer that enables middle school and early high school-age students to use their Measures of Academic Progress Ā® (MAPĀ®) scores to see which colleges and universities theyāre on track to enter long before they embark on the college application process.
By: Greg King
Topics: Innovations in reporting & assessment, College & career readiness, High school