Displaying results 1 - 8 of 8 (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: 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.
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
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: 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: Self-Monitoring Self-Care
Description: This file provides the codebook for the SMSC dataset.
Document Type: Codebook
