Caroline Wang

Caroline_wang
Caroline Wang
Research Scientist,
Education Analytics

Caroline Wang is a research scientist at Education Analytics, a nonprofit organization based in Madison, Wisconsin, that conducts statistical research to solve complex, pressing problems facing public education in the United States. Wang received her PhD in educational research, measurement, and evaluation from Boston College.

updated 2021

 

Contributing topics
Supporting students’ social-emotional, mental & physical health
Understanding, measuring & improving student outcomes
Contributing initiatives
CORE-PACE Research Partnership
COVID-19 Recovery
Caroline Wang in the Media
: Evidence-Based Practices for Assessing Students' Social and Emotional Well-Being
: 4 New Evidence Briefs to Help Students During and After the COVID-19 Pandemic
: Measuring Students’ Social-Emotional Learning Among California’s CORE Districts: An IRT Modeling Approach
Publications by Caroline Wang
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Student Well-Being and Learning Conditions During the Pandemic
Evidence from the CORE Districts
Since spring 2020, the COVID-19 pandemic has been abruptly interrupting regular instruction in almost all schools in the U.S. One year later, policymakers, district administrators, and educators are still balancing the benefits and risks of…
EdResearch for Recovery Brief
Evidence-Based Practices for Assessing Students’ Social and Emotional Well-Being
This brief is one in a series aimed at providing K–12 education decision makers and advocates with an evidence base to ground discussions about how to best serve students during and following the novel coronavirus pandemic. Learn more about the…
An IRT Mixture Model for Rating Scale Confusion Associated with Negatively Worded Items in Measures of Social-Emotional Learning
An IRT Mixture Model for Rating Scale Confusion Associated with Negatively Worded Items in Measures of Social-Emotional Learning
This article illustrates the application of mixture IRT models to evaluate respondent confusion due to the negative wording of certain items on a social-emotional learning (SEL) assessment. Using actual student self-report ratings on four social-…
An IRT Mixture Model for Rating Scale Confusion Associated with Negatively Worded Items in Measures of Social-Emotional Learning
This paper illustrates the application of mixture IRT models to evaluate the possibility of respondent confusion due to the negative wording of certain items on a social-emotional learning (SEL) assessment. Using actual student self-report ratings…