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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: In an attempt to bridge the opportunity gap that exists prior to schooling, understanding the specific activities, resources, and interactions that take place in the home that encourage higher academic achievement has become a primary concern in the field.
Project
Description: We will explore the effects of a self-monitoring self-care intervention on the resilience and self-efficacy of pre-service teachers' (PSTs). PSTs enrolled in an education preparation program will be randomly assigned to a control or treatment group. Both groups will participate in a a resilience and stress reduction training.
Project
Description: The purpose of this pilot study is to explore the effects of podcast creation on empowerment of pre-service teachers (PSTs). Undergraduate students enrolled in an educator preparation program will create an original podcast episode examining one issue in education.
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: Early Home Learning Environment
Description: These data are parent reports of survey questions about their beliefs and their children's home learning environments. Data are cross-sectional and include responses from parents with children ranging from 0 - 13 years of age.
Dataset
Part of Project: Self-Monitoring Self-Care
Description: These data provide pre and posttest results from the SMSC study.
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: Early Home Learning Environment
Description: This is the codebook accompanying the full EHLE data set. It includes descriptions of variables and data collection processes.
Document Type: Codebook
Document
Part of Project: Self-Monitoring Self-Care
Description: This file provides the codebook for the SMSC dataset.
Document Type: Codebook
