Displaying results 1 - 17 of 17 (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: The purpose of this Hub was to deepen insight into an understudied and vulnerable subset of students with learning disabilities (LD), students with comorbid difficulty across reading comprehension (RC) and word problem solving (WPS) and whether text structure intervention in one domain transfers to the other domain.
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: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: This dataset includes the observations to determine the fidelity of implementation of the treatment conditions in the study.
Dataset
Part of Project: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: Nesting variables, treatment condition, demographics, pretest and posttest reading and math variables, text-structure knowledge for classmates of second-grade children with comorbid learning difficulty
Dataset
Part of Project: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: Nesting variables, treatment condition, demographics, pretest and posttest reading and math variables, text-structure knowledge for second-grade children with comorbid learning difficulty .
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: Vanderbilt University Learning Disabilities Innovation Hub: Word Problems, Language, & Comorbid Learning Disabilities
Description: This codebook applies to the three datasets associated with this study:
1-Transfer between Reading Comprehension and Problem Solving
2-Classmates - Transfer between Reading Comprehension and Problem Solving
3-Fidelity - Transfer between Reading Comprehension and Problem Solving
Document Type: Codebook
