Can test metadata help schools measure social-emotional learning?
Consortium for Policy Research in Education Knowledge Hub podcast
Social-emotional learning (SEL) competencies like self-efficacy and conscientiousness can be predictive of long-term academic achievement. But they can also be difficult to measure. In a new study led by NWEA’s James Soland, researchers investigated whether assessment metadata – the way students approach tests and surveys – can provide useful SEL data to schools and educators. Soland joins CPRE research specialist Tesla DuBois to discuss his findings, their implications, and the promise and limitations of student metadata in general.See More
Do students rapidly guess repeatedly over time? A longitudinal analysis of student test disengagement, background, and attitudes
This session from the 2020 National Council on Measurement in Education virtual conference presents new research findings on understanding and managing test-taking disengagement. (Presentation begins at 22:55).
Topics: School & test engagement
This study investigated effort‐moderated (E‐M) scoring, in which item responses classified as rapid guesses are identified and excluded from scoring, and its affect on score distortion from disengaged test taking.
This interactive tool provides context on the typical patterns of achievement and growth in mathematics and reading for private and Catholic schools who take MAP Growth assessments. It provides multiple ways to examine patterns for different groups of students, including by student gender, race/ethnic group, region, and state.
By: Michael Dahlin, Art Katsapis
This user’s guide for the MAP Growth Goal Explorer describes how to use this interactive tool, the benchmarks it uses to provide context on student growth goals, a framework for goal setting, instructions for how to download information from the tool, and answers to frequently asked questions.
The MAP Growth Goal Explorer is designed to support and simplify the goal-setting process by showing a range of possible fall-to-spring growth goals against the backdrop of important academic benchmarks.
Do response styles affect estimates of growth on social-emotional constructs? Evidence from four years of longitudinal survey scores
This study explored how response style affects estimates of growth.
This book presents varied applications of artificial intelligence (AI) in test development, including research and successful examples of using AI technology in automated item generation, automated test assembly, automated scoring, and computerized adaptive testing.
By: Steven Wise