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Xiao Liu; Zhiyong Zhang; Lijuan Wang – Grantee Submission, 2024
In psychology, researchers are often interested in testing hypotheses about mediation, such as testing the presence of a mediation effect of a treatment (e.g., intervention assignment) on an outcome via a mediator. An increasingly popular approach to testing hypotheses is the Bayesian testing approach with Bayes factors (BFs). Despite the growing…
Descriptors: Sample Size, Bayesian Statistics, Programming Languages, Simulation
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Madeline A. Schellman; Matthew J. Madison – Grantee Submission, 2024
Diagnostic classification models (DCMs) have grown in popularity as stakeholders increasingly desire actionable information related to students' skill competencies. Longitudinal DCMs offer a psychometric framework for providing estimates of students' proficiency status transitions over time. For both cross-sectional and longitudinal DCMs, it is…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
Laura K. Allen; Arthur C. Grasser; Danielle S. McNamara – Grantee Submission, 2023
Assessments of natural language can provide vast information about individuals' thoughts and cognitive process, but they often rely on time-intensive human scoring, deterring researchers from collecting these sources of data. Natural language processing (NLP) gives researchers the opportunity to implement automated textual analyses across a…
Descriptors: Psychological Studies, Natural Language Processing, Automation, Research Methodology
David Kaplan; Jianshen Chen; Weicong Lyu; Sinan Yavuz – Grantee Submission, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
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Wang, Chun; Xu, Gongjun; Zhang, Xue – Grantee Submission, 2019
When latent variables are used as outcomes in regression analysis, a common approach that is used to solve the ignored measurement error issue is to take a multilevel perspective on item response modeling (IRT). Although recent computational advancement allow efficient and accurate estimation of multilevel IRT models, we argue that a two-stage…
Descriptors: Error of Measurement, Item Response Theory, Regression (Statistics), Evaluation Methods
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Zhongdi Wu; Eric Larson; Makoto Sano; Doris Baker; Nathan Gage; Akihito Kamata – Grantee Submission, 2023
In this investigation we propose new machine learning methods for automated scoring models that predict the vocabulary acquisition in science and social studies of second grade English language learners, based upon free-form spoken responses. We evaluate performance on an existing dataset and use transfer learning from a large pre-trained language…
Descriptors: Prediction, Vocabulary Development, English (Second Language), Second Language Learning
Wolbers, Kimberly A.; Dostal, Hannah M.; Cihak, David; Holcomb, Leala – Grantee Submission, 2020
This study explores the impact of Strategic and Interactive Writing Instruction (SIWI) on six students' written language skills through the application of a multiple-baseline probe single case design with embedded condition. This was part of a larger Institute of Education Sciences (IES)-funded project focused on the development and feasibility of…
Descriptors: Deafness, Writing Instruction, Writing Skills, Syntax
Middleton, Joel A.; Scott, Marc A.; Diakow, Ronli; Hill, Jennifer L. – Grantee Submission, 2016
In the analysis of causal effects in non-experimental studies, conditioning on observable covariates is one way to try to reduce unobserved confounder bias. However, a developing literature has shown that conditioning on certain covariates may increase bias, and the mechanisms underlying this phenomenon have not been fully explored. We add to the…
Descriptors: Statistical Bias, Identification, Evaluation Methods, Measurement Techniques
Doroudi, Shayan; Aleven, Vincent; Brunskill, Emma – Grantee Submission, 2017
The gold standard for identifying more effective pedagogical approaches is to perform an experiment. Unfortunately, frequently a hypothesized alternate way of teaching does not yield an improved effect. Given the expense and logistics of each experiment, and the enormous space of potential ways to improve teaching, it would be highly preferable if…
Descriptors: Teaching Methods, Matrices, Evaluation Methods, Models
Santi, Kristi L.; Khalaf, Shiva; Bunta, Ferenc; Rojas, Raúl; Francis, David J. – Grantee Submission, 2019
This article examines the validity of IQ-achievement discrepancy and low-achievement as criteria for the identification of disabilities in Spanish-speaking ELs and the factors that moderate the validity of these approaches as bases for identification. While there has been a long history of examining the validity of different approaches to…
Descriptors: Intelligence Quotient, Spanish Speaking, English Language Learners, Disability Identification
Abrams, Lisa; Varier, Divya; Jackson, Lisa – Grantee Submission, 2016
The use of assessment data to inform instruction is an important component of a comprehensive standards-based assessment programme. Examining teachers' data use for instruction can reveal the extent to which instruction is aligned with established content standards and assessment. This paper describes results of a qualitative study of teachers'…
Descriptors: Alignment (Education), Elementary School Teachers, Evaluation Methods, Evaluation Utilization