Displaying results 1 - 19 of 19 (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: Project Goals:
The first goal will fill a CUREs gap by creating self-supporting and sustainable protein-centric
CUREs. The second goal will use this protein-centric CUREs community to examine two critical
aspects of a CURE: 1) the impact of the length of CUREs (course long CUREs (cCUREs) or shorter, modular
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.
Project
Description: Word knowledge is critical for speaking, reading and writing, yet a substantial proportion of children with language impairment demonstrate poor word learning and consequently poor vocabulary. Because vocabulary has a causal relationship with reading comprehension, this presents a significant national health concern.
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.
Dataset
Part of Project: Profiles of Working Memory and Word Learning for Educational Research (POWWER)
Description: This dataset incudes data from 248 second graders (7- to 8-year-olds) with typical development from three states. One hundred sixty-seven were monolingual English-speaking and 81 were dual Spanish- and English-speaking.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: This is the pre and post test TOSLS data for the undergraduate students in this project.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: This contains institutional data gathered from some of the participating institutions including GPA, retention, and graduation data.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: This includes the variables from the STEM Career Interest Scale.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: This is the student data from the LCAS taken at the end of the semester.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: The faculty reported the CURE elements that were incorporated into their course after the semester was finished.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: This is the results of the faculty CURE survey given after the faculty taught the course.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: EDAT data from undergraduate students participating in a protein-centric CURE.
Dataset
Part of Project: Malate Dehydrogenase CURE Community
Description: Data are from ~1,500 undergraduate students participating in a protein-centric CURE across 19 institutions. This is the data from Lopatto's CURE survey.
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
Document
Part of Project: A Longitudinal Assessment of Late Talking Toddlers
Description: This file contains information on how to calculate the used D-scores from the raw data provided. Additionally, the contained dataset is in long-format, which may cause difficulties for performing certain operations/analyses on the data.
Document Type: Other
