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Feng, Tianying; Chung, Gregory K. W. K. – Grantee Submission, 2022
A critical issue in using fine-grained gameplay data to measure learning processes is the development of indicators and the algorithms used to derive such indicators. Successful development--that is, developing traceable, interpretable, and sensitive-to-learning indicators--requires understanding the underlying theory, how the theory is…
Descriptors: Games, Data Collection, Learning Processes, Measurement
Man Chen; James E. Pustejovksy; David A. Klingbeil; Ethan R. Van Norman – Grantee Submission, 2023
Single-case designs (SCDs) are a class of research methods for evaluating the effects of academic and behavioral interventions in educational and clinical settings. Although visual analysis is typically the first and main method for primary analysis of data from SCDs, quantitative methods are useful for synthesizing results and drawing systematic…
Descriptors: Effect Size, Meta Analysis, Intervention, Data Collection
Nazanin Nezami; Parian Haghighat; Denisa Gándara; Hadis Anahideh – Grantee Submission, 2024
The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…
Descriptors: Evaluation Methods, College Students, Success, Predictor Variables
Vonna L. Hemmler; Allison W. Kenney; Susan Dulong Langley; Carolyn M. Callahan; E. Jean Gubbins; Shannon Holder – Grantee Submission, 2022
Though qualitative research has become more prevalent in practice over the last 30 years, there is still considerable uncertainty among researchers regarding how to ensure inter-rater consistency when teams are tasked with coding qualitative data. In this article, we offer an explanation of a methodology our qualitative team used to achieve…
Descriptors: Interrater Reliability, Coding, Guides, Data Collection
Bonifay, Wes – Grantee Submission, 2022
Traditional statistical model evaluation typically relies on goodness-of-fit testing and quantifying model complexity by counting parameters. Both of these practices may result in overfitting and have thereby contributed to the generalizability crisis. The information-theoretic principle of minimum description length addresses both of these…
Descriptors: Statistical Analysis, Models, Goodness of Fit, Evaluation Methods
Lauren Berkovits; Jan Blacher; Abbey Eisenhower; Stuart Daniel – Grantee Submission, 2023
Purpose: Comparative data of autism-sensitive standardized measures of emotion regulation and lability, describing percentage change over time for populations of young autistic children, are currently publicly unavailable. We propose publication of such data as a support for future therapeutic intervention studies. Methods: We generate and present…
Descriptors: Emotional Response, Check Lists, Autism Spectrum Disorders, Comparative Analysis
Samantha Fu; Charles Davis; Jesse Rothstein; Aparna Ramesh; Evan White – Grantee Submission, 2022
Linking data together can be a powerful way for governments and researchers alike to tackle vexing public policy research problems. However, for researchers, finding ways to link data directly between two departments can often be more challenging than even obtaining the data in the first place. Even when a researcher develops the necessary…
Descriptors: Data Use, Research Methodology, Researchers, Privacy
Emma R. Dear; Bryce D. McLeod; Nicole M. Peterson; Kevin S. Sutherland; Michael D. Broda; Alex R. Dopp; Aaron R. Lyon – Grantee Submission, 2024
Introduction: Due to usability, feasibility, and acceptability concerns, observational treatment fidelity measures are often challenging to deploy in schools. Teacher self-report fidelity measures with specific design features might address some of these barriers. This case study outlines a community-engaged, iterative process to adapt the…
Descriptors: Measures (Individuals), Data Collection, Observation, Learning Analytics
Grantee Submission, 2022
Systems for learning and producing knowledge, such as career and technical education (CTE), often reproduce inequities unless an equity-focused lens is used when designing, implementing, and evaluating programs. This framework presents guidance for conducting CTE research with an intentional focus on equity. Developed by the CTE Research Network's…
Descriptors: Equal Education, Vocational Education, Educational Research, Program Administration
McLeod, Bryce D.; Jensen-Doss, Amanda; Lyon, Aaron R.; Douglas, Susan; Beidas, Rinad S. – Grantee Submission, 2022
Mental health organizations that serve youth are under pressure to adopt measurement-based care (MBC), defined as the continuous collection of client-report data used to support clinical decision making as part of standard care. However, few frameworks exist to help leadership ascertain how to select an MBC approach for a clinical setting. This…
Descriptors: Mental Health Programs, Measurement, Evidence Based Practice, Youth
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
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
Razvan Paroiu; Stefan Ruseti; Mihai Dascalu; Stefan Trausan-Matu; Danielle S. McNamara – Grantee Submission, 2023
The exponential growth of scientific publications increases the effort required to identify relevant articles. Moreover, the scale of studies is a frequent barrier to research as the majority of studies are low or medium-scaled and do not generalize well while lacking statistical power. As such, we introduce an automated method that supports the…
Descriptors: Science Education, Educational Research, Scientific and Technical Information, Journal Articles
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
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