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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: This project focused on the idea of data-based decision-making (DBDM) at the classroom level, focusing on how teachers use assessment data to adapt their instruction to students’ individual needs. The present project investigated this idea directly and evaluated the effectiveness of teacher support on the different steps of this process.
Project
Description: Raw data files on test statistics of students in our SBL class of 2022.
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: Data-based decision-making in schools: Examining the process and effects of teacher support
Description: This dataset contains the relevant data related to the project "Data-based decision-making in schools: Examining the process and effects of teacher support", that were used in the associated manuscript available at https://doi.org/10.1037/edu0000530. Data and associated codebook/materials are all available at the external dataset link.
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: Simulation Based Learning (SBL): an engineering course on Chao Phraya River’s salinity forecasting by Mathematical Modeling
Description: This document is a paper submitted to a Hindawi journal of education.
Document Type: Journal Contribution
