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Shaw, Mairead; Flake, Jessica K. – Educational Measurement: Issues and Practice, 2023
Clustered data structures are common in many areas of educational and psychological research (e.g., students clustered in schools, patients clustered by clinician). In the course of conducting research, questions are often administered to obtain scores reflecting latent constructs. Multilevel measurement models (MLMMs) allow for modeling…
Descriptors: Hierarchical Linear Modeling, Research Methodology, Data Analysis, Structural Equation Models
Marjorie Cohen; Steve Klein; Cherise Moore – Career and Technical Education Research Network, 2020
As the education and workforce development community looks more and more to CTE to help ensure students are both college and career ready, understanding and using CTE data and research becomes increasingly important. This is the first in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE)…
Descriptors: Vocational Education, Units of Study, Data Use, Training Objectives
Annie E. Casey Foundation, 2023
"Fostering Youth Transitions 2023: State and National Data to Drive Foster Care Advocacy" is a unique compilation of data designed to inform federal and state policy efforts aimed at making a difference for young people in foster care. This overview brief and detailed profiles of the latest available data from all 50 states, along with…
Descriptors: Foster Care, Advocacy, Youth, State Policy
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Swist, Teresa; Humphry, Justine; Gulson, Kalervo N. – Learning, Media and Technology, 2023
There is a broad impetus across policy and institutional domains to expand public engagement and involvement with emerging technology research and innovation. Yet innovative theory, methods, and practices to critically explore algorithmic system controversies and democratic possibilities are still in nascent form. In this paper, we bring together…
Descriptors: Algorithms, Data Analysis, Democracy, Design
Sosa, Giovanni – RP Group, 2022
The first step to addressing equity gaps is to identify them. How can community colleges determine, with some degree of certainty, whether one or more student groups on a campus is in need of assistance in order to succeed? This paper tackles this question by delving into the three methods typically used to identify equity gaps, comparing and…
Descriptors: Equal Education, Community College Students, Disproportionate Representation, Data Analysis
Marjorie Cohen; Steve Klein; Cherise Moore – Career and Technical Education Research Network, 2020
By partnering with researchers, state CTE administrators have the opportunity to better understand CTE programming and practices across their states. This is the fourth in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE) Research Network Lead. Designed for CTE practitioners and state…
Descriptors: Vocational Education, Educational Research, Research Utilization, Data Use
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Liou, Gloria; Bonner, Cavan V.; Tay, Louis – International Journal of Testing, 2022
With the advent of big data and advances in technology, psychological assessments have become increasingly sophisticated and complex. Nevertheless, traditional psychometric issues concerning the validity, reliability, and measurement bias of such assessments remain fundamental in determining whether score inferences of human attributes are…
Descriptors: Psychometrics, Computer Assisted Testing, Adaptive Testing, Data
Kulkarni, Tara; Weeks, Mollie R.; Sullivan, Amanda L. – Communique, 2020
As frequent consumers and disseminators of research, school psychologists have an ethical obligation to critically evaluate the findings of studies (National Association of School Psychologists, 2010); however, this can feel burdensome when studies are behind paywalls and require hours to properly scrutinize. Particularly when studies utilizing…
Descriptors: Data Analysis, School Psychology, Criticism, Psychological Studies
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Pazzaglia, Angela M.; Stafford, Erin T.; Rodriguez, Sheila M. – Regional Educational Laboratory Northeast & Islands, 2016
This guide describes a five-step collaborative process that educators can use with other educators, researchers, and content experts to write or adapt questions and develop surveys for education contexts. This process allows educators to leverage the expertise of individuals within and outside of their organization to ensure a high-quality survey…
Descriptors: Surveys, Data Analysis, Response Rates (Questionnaires), Statistics
Steve Klein; Cherise Moore – Career and Technical Education Research Network, 2021
This is the sixth in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE) Research Network Lead. Designed for CTE practitioners and state agency staff, these modules are designed to strengthen the capacity to access, understand, and use CTE data and research as well as conduct one's own…
Descriptors: Vocational Education, Educational Research, Research Utilization, Data Use
Steve Klein; Cherise Moore – Career and Technical Education Research Network, 2021
With research as a guide, designing CTE programs that promote equity and help close the opportunity gap is achievable. This is the fifth in a series of six practitioner training modules developed as part of the Career & Technical Education (CTE) Research Network Lead. Designed for CTE practitioners and state agency staff, these modules are…
Descriptors: Vocational Education, Educational Research, Research Methodology, Research Utilization
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Bruhn, Allison L.; McDaniel, Sara C.; Rila, Ashley; Estrapala, Sara – Beyond Behavior, 2018
Students who are at risk for or show low-intensity behavioral problems may need targeted, Tier 2 interventions. Often, Tier 2 problem-solving teams are charged with monitoring student responsiveness to intervention. This process may be difficult for those who are not trained in data collection and analysis procedures. To aid practitioners in these…
Descriptors: Progress Monitoring, Behavior Problems, Student Behavior, At Risk Students
Truckenmiller, Adrea J.; Yohannan, Justina; Cho, Eunsoo – Communique, 2020
When students struggle with reading, school-based teams seek more information about why those students are struggling in order to provide instruction that will meet the students' needs. This process occurs for students needing Tier 2 or 3 instruction and students with disabilities who have reading goals. Reading specialists, special education…
Descriptors: Reading Tests, Data Use, Educational Planning, Reading Difficulties
Flanagan, Agnes; Cormier, Damien C. – Communique, 2019
One of the areas subsumed under the data-based decision making and accountability practice identified in the National Association of School Psychologists' (NASP) "Model for Integrated School Psychological Services" is to collect information on psychological and educational variables to make decisions at a number of levels of service…
Descriptors: Test Bias, School Psychologists, Measurement, Data Collection
National Student Clearinghouse, 2022
This tenth annual High School Benchmarks Report provides updated data on high school graduates' college access, persistence, and completion outcomes. This report was designed with several features particularly tailored to secondary education practitioners and policymakers. First, results presented in this report update last years' findings on high…
Descriptors: High School Graduates, Access to Education, College Attendance, Academic Persistence
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