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Miranda Kucera; K. Kawena Begay – Communique, 2025
While the field advocates for a diversified and comprehensive professional role (National Association of School Psychologists, 2020), school psychologists have long spent most of their time in assessment-related activities (Farmer et al., 2021), averaging about eight cognitive evaluations monthly (Benson et al., 2020). Assessment practices have…
Descriptors: Equal Education, Student Evaluation, Evaluation Methods, Standardized Tests
Miranda Kucera; K. Kawena Begay – Communique, 2025
In Part 1 of this series, the authors briefly reviewed some challenges inherent in using standardized tools with students who are not well represented in norming data. To help readers clearly conceptualize the framework steps, the authors present two case studies that showcase how a nonstandardized approach to assessment can be individualized to…
Descriptors: Equal Education, Student Evaluation, Evaluation Methods, Standardized Tests
Bernstein, Sima; Barnett, W. Steven; Ackerman, Debra J. – National Institute for Early Education Research, 2019
Because pre-academic and social-emotional capabilities at kindergarten entry predict later academic and social success, there has been great concern with the level of "readiness" at kindergarten entry. Many states require a kindergarten readiness assessment (KRA). However, how readiness is defined, who or what entity is doing the…
Descriptors: School Readiness, Kindergarten, Definitions, Student Characteristics
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Sandlin, Michele – College and University, 2019
This feature focuses on the five areas an institution needs to know before implementing holistic measures. These include: what does a holistic review entail, how to be legally complaint, Sedlacek's noncognitive variables, applying student success measures, and the vital importance of training.
Descriptors: Predictor Variables, Success, Holistic Approach, Compliance (Legal)
Klein-Collins, Rebecca; Taylor, Jason; Bishop, Carianne; Bransberger, Peace; Lane, Patrick; Leibrandt, Sarah – Council for Adult and Experiential Learning, 2020
This report describes the adult student's experience with prior learning assessment (PLA) using student record data from 72 degree-granting postsecondary institutions in the United States, primarily focusing on the data from 69 of those institutions based on the more detailed data provided by those institutions to the study. Researchers from the…
Descriptors: Prior Learning, Student Evaluation, Adult Students, Student Records
Klein-Collins, Rebecca; Taylor, Jason; Bishop, Carianne; Bransberger, Peace; Lane, Patrick; Leibrandt, Sarah – Council for Adult and Experiential Learning, 2020
This report describes the adult student's experience with prior learning assessment (PLA) using student record data from 72 degree-granting postsecondary institutions in the United States, primarily focusing on the data from 69 of those institutions based on the more detailed data provided by those institutions to the study. Researchers from the…
Descriptors: Prior Learning, Student Evaluation, Adult Students, Student Records
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Coleman, Chad; Baker, Ryan S.; Stephenson, Shonte – International Educational Data Mining Society, 2019
Determining which students are at risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of research and practice in both K-12 and higher education. The detectors produced from this type of predictive modeling research are increasingly used in early warning…
Descriptors: Prediction, At Risk Students, Predictor Variables, Elementary Secondary Education
Sugarman, Julie – Migration Policy Institute, 2018
In recent years, education data have become both more easily accessible and more important than ever to decisions about K-12 policies and practice. Under the "Every Student Succeeds Act" (ESSA), states are required to publish data on how students, including English Learners (ELs), are performing in areas such as reading, math, and…
Descriptors: English Language Learners, Data Collection, Data Analysis, Student Characteristics
Edwards, Virginia B., Ed. – Education Week, 2014
Educators and experts alike have come to a growing realization that academic factors alone do not tell the whole story of what it means to successfully navigate the educational system through high school and into higher education or the workplace. This national report from "Education Week" investigates the role that student engagement…
Descriptors: Learner Engagement, Student Motivation, Student Participation, Success
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Irwin, Clare W.; O'Dwyer, Laura; Cook, Kyle DeMeo – Regional Educational Laboratory Northeast & Islands, 2014
The Early Childhood Educator Survey and the Early Childhood Administrator Survey allow users to collect consistent data on the use of child assessments and learning standards in early childhood learning settings. Each survey includes modules on educator/administrator background information, assessment use, and learning standards implementation.…
Descriptors: Administrators, Surveys, Teacher Characteristics, Administrator Characteristics
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Zweig, Jacqueline; Irwin, Clare W.; Kook, Janna Fuccillo; Cox, Josh – Regional Educational Laboratory Northeast & Islands, 2015
The purpose of this study is to describe what data preschools in a mid-sized city in the Northeast collect, how they use that data, and the challenges they face. The study focuses on three types of data: early learning outcomes, dosage (i.e., the amount of exposure to early childhood education), and classroom quality. The report further…
Descriptors: Preschool Education, Data Collection, Early Childhood Education, Educational Quality
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Zweig, Jacqueline; Irwin, Clare W.; Kook, Janna Fuccillo; Cox, Josh – Regional Educational Laboratory Northeast & Islands, 2015
This "Stated Briefly" report is a companion piece that summarizes the results of another report of the same name. This study explores how seven early childhood education programs in a mid-sized city in the Northeast region are collecting and using data, how they would like to use data, how they could use the data that they have, and the…
Descriptors: Preschool Education, Data Collection, Early Childhood Education, Educational Quality
Thompson, Travis – Brookes Publishing Company, 2011
Discrete trial instruction or naturalistic, incidental teaching: How do you choose which approach to use with young children with autism? Now there's no need to "pick a side"--this groundbreaking book helps professionals skillfully blend the best of both behavioral approaches to respond to "each child's individual needs". Developed by one of the…
Descriptors: Student Characteristics, Intervention, Autism, Young Children
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Hopstock, Paul J.; Pelczar, Marisa P. – National Center for Education Statistics, 2011
This technical report and user's guide is designed to provide researchers with an overview of the design and implementation of the 2009 Program for International Student Assessment (PISA), as well as with information on how to access the PISA 2009 data. This information is meant to supplement that presented in Organization for Economic Cooperation…
Descriptors: Parent Materials, Academic Achievement, Measures (Individuals), Program Effectiveness
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Swing, Randy L. – Assessment Update, 2004
Summative measures of learning collected at the conclusion of an associate or bachelor's degree program are insufficient to help educators and students maximize learning and personal development across the college years. Managing the desired outcomes of college requires an understanding of when learning and growth occur during the educational…
Descriptors: College Freshmen, Program Effectiveness, Researchers, Student Evaluation
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