Publication Date
| In 2026 | 0 |
| Since 2025 | 0 |
| Since 2022 (last 5 years) | 0 |
| Since 2017 (last 10 years) | 2 |
| Since 2007 (last 20 years) | 4 |
Descriptor
| Monte Carlo Methods | 4 |
| Error of Measurement | 2 |
| Reading Tests | 2 |
| Research Design | 2 |
| Scores | 2 |
| Statistical Bias | 2 |
| Academic Achievement | 1 |
| Accuracy | 1 |
| Algebra | 1 |
| Attrition (Research Studies) | 1 |
| Classification | 1 |
| More ▼ | |
Author
| Agodini, Roberto | 1 |
| Beretvas, S. Natasha | 1 |
| Campuzano, Larissa | 1 |
| David J. Weiss | 1 |
| Deke, John | 1 |
| Dynarski, Mark | 1 |
| Ferron, John M. | 1 |
| Gina Biancarosa | 1 |
| Joseph N. DeWeese | 1 |
| Kautz, Tim | 1 |
| Mark L. Davison | 1 |
| More ▼ | |
Publication Type
| Numerical/Quantitative Data | 4 |
| Reports - Research | 3 |
| Journal Articles | 1 |
| Reports - Descriptive | 1 |
Education Level
| Elementary Education | 1 |
| Grade 1 | 1 |
| Grade 4 | 1 |
| Grade 6 | 1 |
Audience
Location
Laws, Policies, & Programs
| No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
| California Achievement Tests | 1 |
| Iowa Tests of Basic Skills | 1 |
| Otis Lennon School Ability… | 1 |
| Stanford Achievement Tests | 1 |
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 1 |
| Meets WWC Standards with or without Reservations | 1 |
Mark L. Davison; David J. Weiss; Ozge Ersan; Joseph N. DeWeese; Gina Biancarosa; Patrick C. Kennedy – Grantee Submission, 2021
MOCCA is an online assessment of inferential reading comprehension for students in 3rd through 6th grades. It can be used to identify good readers and, for struggling readers, identify those who overly rely on either a Paraphrasing process or an Elaborating process when their comprehension is incorrect. Here a propensity to over-rely on…
Descriptors: Reading Tests, Computer Assisted Testing, Reading Comprehension, Elementary School Students
Moeyaert, Mariola; Ugille, Maaike; Ferron, John M.; Beretvas, S. Natasha; Van den Noortgate, Wim – Journal of Experimental Education, 2016
The impact of misspecifying covariance matrices at the second and third levels of the three-level model is evaluated. Results indicate that ignoring existing covariance has no effect on the treatment effect estimate. In addition, the between-case variance estimates are unbiased when covariance is either modeled or ignored. If the research interest…
Descriptors: Hierarchical Linear Modeling, Monte Carlo Methods, Computation, Statistical Bias
Deke, John; Wei, Thomas; Kautz, Tim – National Center for Education Evaluation and Regional Assistance, 2017
Evaluators of education interventions are increasingly designing studies to detect impacts much smaller than the 0.20 standard deviations that Cohen (1988) characterized as "small." While the need to detect smaller impacts is based on compelling arguments that such impacts are substantively meaningful, the drive to detect smaller impacts…
Descriptors: Intervention, Educational Research, Research Problems, Statistical Bias
Campuzano, Larissa; Dynarski, Mark; Agodini, Roberto; Rall, Kristina – National Center for Education Evaluation and Regional Assistance, 2009
In the No Child Left Behind Act (NCLB), Congress called for the U.S. Department of Education (ED) to conduct a rigorous study of the conditions and practices under which educational technology is effective in increasing student academic achievement. A 2007 report presenting study findings for the 2004-2005 school year, indicated that, after one…
Descriptors: Teacher Characteristics, Federal Legislation, Academic Achievement, Computer Software

Peer reviewed
Direct link
