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Wilhelmina Van Dijk; Cynthia U. Norris; Stephanie Al Otaiba; Christopher Schatschneider; Sara A. Hart – Grantee Submission, 2022
This manuscript provides information on datasets pertaining to Project KIDS. Datasets include behavioral and achievement data for over 4,000 students between five and twelve years old participating in nine randomized control trials of reading instruction and intervention between 2005-2011, and information on home environments of a subset of 442…
Descriptors: Data, Reading Instruction, Intervention, Family Environment
Hollands, Fiona M.; Pratt-Williams, Jaunelle; Shand, Robert – Grantee Submission, 2021
The purpose of these guidelines is to support the execution of cost analysis and cost-effectiveness analysis of educational programs. The steps involved in conducting a cost analysis are presented in four stages with explicit examples used throughout: designing your cost analysis, collecting cost data using the ingredients method, analyzing cost…
Descriptors: Cost Effectiveness, Educational Finance, Standards, Guidelines
Daugherty, Lindsay – Grantee Submission, 2020
"Stackable credential programs" are designed to make it easier for students to earn multiple postsecondary certificates or degrees in a field as they advance in their careers. To examine the stacking of credentials in Ohio and inform ongoing efforts to scale stackable credential programs, the Ohio Department of Higher Education and the…
Descriptors: Data Use, Educational Improvement, Postsecondary Education, Credentials
Magooda, Ahmed; Litman, Diane – Grantee Submission, 2021
This paper explores three simple data manipulation techniques (synthesis, augmentation, curriculum) for improving abstractive summarization models without the need for any additional data. We introduce a method of data synthesis with paraphrasing, a data augmentation technique with sample mixing, and curriculum learning with two new difficulty…
Descriptors: Data Analysis, Synthesis, Documentation, Models
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
Dan Soriano; Eli Ben-Michael; Peter Bickel; Avi Feller; Samuel D. Pimentel – Grantee Submission, 2023
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for balancing weights estimators, an increasingly popular approach that solves an optimization problem to…
Descriptors: Statistical Analysis, Computation, Mathematical Formulas, Monte Carlo Methods
Apryl L. Poch; Abigail A. Allen; Pyung-Gang Jung; Erica S. Lembke; Kristen L. McMaster – Grantee Submission, 2022
Writing is a critical academic and life skill, but many school-age children struggle with the complexity of written expression. Given the importance of writing, there is a clear need for a systematic approach to identifying and supporting struggling writers, including writers with learning and emotional disabilities. One such approach is known as…
Descriptors: Data Use, Decision Making, Writing Instruction, Writing Difficulties
Debshila Basu Mallick; Brittany C. Bradford; Richard G. Baraniuk – Grantee Submission, 2023
OpenStax Kinetic is an innovative research infrastructure that aims to transform education and learning research in the digital age. With its access to large sample sizes, authentic learning environments, experimental control, scalability, security and privacy protection, Kinetic provides an unparalleled opportunity for researchers to study the…
Descriptors: Educational Research, Research Methodology, Electronic Learning, Adult Learning
McLeod, Bryce D.; Cook, Clayton R.; Sutherland, Kevin S.; Lyon, Aaron R.; Dopp, Alex; Broda, Michael; Beidas, Rinad S. – Grantee Submission, 2021
Numerous evidence-based programs (EBPs) exist for delivery in schools to promote youth mental health outcomes. However, school systems often lack the internal infrastructure to support the effective implementation and sustainment of EBPs when external supports are withdrawn, resulting in notable attenuation in the benefits in youth clinical…
Descriptors: Evidence Based Practice, Mental Health Programs, School Health Services, Program Implementation
Craig K. Enders – Grantee Submission, 2023
The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…
Descriptors: Data, Research, Theories, Regression (Statistics)
Zhang, Zhiyong; Liu, Haiyan – Grantee Submission, 2018
Latent change score models (LCSMs) proposed by McArdle (McArdle, 2000, 2009; McArdle & Nesselroade, 1994) offer a powerful tool for longitudinal data analysis. They are becoming increasingly popular in social and behavioral research (e.g., Gerstorf et al., 2007; Ghisletta & Lindenberger, 2005; King et al., 2006; Raz et al., 2008). Although…
Descriptors: Sample Size, Monte Carlo Methods, Data Analysis, Models
Fesler, Lily; Dee, Thomas; Baker, Rachel; Evans, Brent – Grantee Submission, 2019
Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this article, we review the recent automated text methods relevant to educational…
Descriptors: Educational Research, Content Analysis, Research Methodology, Data Analysis
McGrath Kato, Mimi; Flannery, Brigid; Triplett, Danielle; Saeturn, Sun – Grantee Submission, 2018
Freshman year has been identified as a very important year in high school. It has been shown more than any other year to determine whether a student will complete high school or drop out. Schools who examine grade-level data on a regular basis often find that freshmen students receive the most office discipline referrals and most failing grades,…
Descriptors: Grade 9, High School Freshmen, Student Needs, Prevention
Arenson, Ethan A.; Karabatsos, George – Grantee Submission, 2017
Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…
Descriptors: Bayesian Statistics, Item Response Theory, Nonparametric Statistics, Models

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