Displaying results 1 - 12 of 12 (Go to Advanced Search)
Project
Description: Mathematical thinking is in high demand in the global market, but approximately six percent of school-age children across the globe experience math difficulties (Shalev, et al., 2000).
Project
Description: The purpose of this scoping review to provide a rigorous – and accessible – overview of the research base for universal behavior screening instruments to facilitate educators’ decision-making process when selecting a systematic screening tool for the students they serve and identify areas of further refinement for the research community.
Project
Description: The analysis of narratives often accompanies comprehensive language assessments of students. While analyzing narratives can be time-consuming and labor-intensive, recent advances in large language models (LLMs) indicate that it may be possible to automate this process.
Dataset
Part of Project: The Home Math Environment and Children's Math Achievment: A Meta-Analysis
Description: The data are in long form, with some studies having multiple lines and includes a sample of children ranging from 3.54 to 13.75 years old. The main effect size is the r, correlation coefficient, and the accompanying sample size is also included.
Dataset
Part of Project: Mapping the Research Base for Universal Behavior Screeners
Description: This database includes a of summary findings from 180 articles examining psychometric properties behavior screening tools administered universally which are summarized in the article "Mapping the Research Base for Universal Behavior Screeners".
Dataset
Part of Project: Automated Narrative Scoring Using Large Language Models
Description: Narrative language samples elicited using the ALPS Oral Narrative Retell and Oral Narrative Generation tasks from diverse K-3 students. The test data set was drawn randomly from the larger corpus of narrative language samples.
Dataset
Part of Project: Automated Narrative Scoring Using Large Language Models
Description: Narrative language samples elicited using the ALPS Oral Narrative Retell and Oral Narrative Generation tasks from diverse K-3 students. The training data set was drawn randomly from the larger corpus of narrative language samples.
Dataset
Part of Project: Automated Narrative Scoring Using Large Language Models
Description: Narrative language samples elicited using the ALPS Oral Narrative Retell and Oral Narrative Generation tasks from diverse K-3 students. The tworaters data set was drawn randomly from the larger corpus of narrative language samples. These samples were scored by two raters for reliability purposes.
Code
Home Math Environment and Children's Math Achievement Meta-Analysis R code using the Metafor package
Part of Project: The Home Math Environment and Children's Math Achievment: A Meta-Analysis
Description: This code was written in R version 3.5.3 using the metafor package (Viechtbauer, 2010). First the dataset is called in, then the variables are converted to the correct formats for analysis, then the escalc() function is used to calculate an overall Fisher's Z effect size, which is then converted to an R correlation coefficient.
Code Type: Analysis
Document
Part of Project: Mapping the Research Base for Universal Behavior Screeners
Description: This is a pre-print of the manuscript as it was submitted for publication.
Document Type: Preprint
Document
Part of Project: Mapping the Research Base for Universal Behavior Screeners
Description: This is the final pre-print for the project Mapping the Research Base for Universal Behavior Screening.
Document Type: Preprint
Document
Part of Project: Mapping the Research Base for Universal Behavior Screeners
Description: This is the final pre-print for the project Mapping the Research Base for Universal Behavior Screening as of 02/05/2025.
Document Type: Preprint
