Displaying results 1 - 9 of 9 (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: By leveraging technology, new knowledge will be gained on the linkage between teacher stress, teacher talk, teacher-student relationships, and pre-academic and social-emotional outcomes in Black and Latine students, paving the way for more efficacious interventions to reduce teacher stress.
Project
Description: Purpose: The special needs of young children (birth to 36 months) are not unidimensional. Early interventionists are challenged in developing interventions that fully address the needs of young children with developmental delays in multiple domains.
Project
Description: This study examined longitudinal outcomes of late-talking toddlers. Specifically, we included toddlers who participated in the Vocabulary Acquisition and Usage for Late Talkers (VAULT) treatment protocol.
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: A Longitudinal Assessment of Late Talking Toddlers
Description: This dataset contains the data from the overarching project that was collected via the Vocabulary Acquisition and Usage for Late Talkers (VAULT) protocol. This data is longitudinal in nature, containing data for baseline, pretest, at treatment, post treatment, and a delayed follow-up for 68 students.
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: A Longitudinal Assessment of Late Talking Toddlers
Description: This codebook contains the information needed to understand the variable naming conventions and structure for the VAULT dataset from the larger Longitudinal Assessment of Late Talking Toddlers project. Information is available for all timepoints.
Document Type: Codebook
Document
Part of Project: A Longitudinal Assessment of Late Talking Toddlers
Description: This document serves as an adjunct for understanding the nature of the VAULT data and its accompanying codebook. Specific information and citations are provided for the individual measures used. Additionally, the timeline/protocol used within the project is detailed in this document.
Document Type: Other
