A Collection of Educational Datasets for Research and Statistical Analysis

Curates a comprehensive and robust collection of 15 classic educational, economic, and social science datasets meticulously tailored for empirical research, project-based learning, and academic instruction in higher education. It streamlines exploratory data analysis, business intelligence modeling, regression techniques, and hypothesis testing by providing ready-to-use data structures sourced from prominent community packages (Kleiber and Zeileis (2008) < https://CRAN.R-project.org/package=AER>; Fox and Weisberg (2019) < https://CRAN.R-project.org/package=carData>).


License: GPL-3

eduResearchR

eduResearchR is an R package designed to facilitate access to a curated collection of 15 educational and social science datasets, ready for research and statistical analysis.

Description

This package provides a standardized structure for loading and exploring research data, enabling students and professionals to focus on quantitative analysis without the need for complex preprocessing.

Installation

You can install the development version of the package with the following command in R:

devtools::install_github("jlmarmanillo-jlms/eduResearchR", build_vignettes = TRUE)

Usage

Once installed, load the package and any available dataset:

library(eduResearchR)
data("STARplus")
head(STARplus)

Pedagogical vignette

To consult the detailed methodological guide of the package, run:

vignette("intro-eduResearchR", package = "eduResearchR")

Author

Jorge Luis Marmanillo Santana

M.Sc. in Educational Informatics

Dataset sources and descriptions

The 15 datasets included in eduResearchR have been curated and organized from standard R packages to facilitate educational research and applied statistical analysis:

  • apipop.rda: Academic Performance Index student and school-level dataset.
  • CASchools.rda: California Test Score Data for school districts.
  • classroom.rda: Classroom-level data on student achievement and instruction.
  • collegeDistance.rda: High School and Beyond dataset on higher education accessibility.
  • EducationLiteracy.rda: Cross-national indicators of educational literacy and attainment.
  • ExamScores.rda: Student examination scores and performance metrics.
  • FirstYearGPA.rda: First-year college GPA and academic predictor variables.
  • MathAchieve.rda: Mathematics achievement scores from high school students.
  • NELS.rda: National Education Longitudinal Study (NELS) of 1988 dataset on school effectiveness.
  • pisausa.rda: Program for International Student Assessment (PISA) data for the United States.
  • school.rda: Institutional indicators and structural school characteristics.
  • schoolProgram.rda: Evaluation data on school academic programs and interventions.
  • schools.rda: Census and demographic data across primary and secondary schools.
  • STARplus.rda: STAR project dataset on class size reduction and student achievement with non-experimental controls.
  • STUDENT.rda: Student-level demographic and academic performance records.

Reference manual

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install.packages("eduResearchR")

0.1.0 by Jorge Luis Marmanillo Santana, 9 days ago


https://github.com/jlmarmanillo-jlms/eduResearchR


Report a bug at https://github.com/jlmarmanillo-jlms/eduResearchR/issues


Browse source code at https://github.com/cran/eduResearchR


Authors: Jorge Luis Marmanillo Santana [aut, cre] (ORCID: , Christian Kleiber [ctb] (Author of the AER package; original source for CASchools and CollegeDistance.) , John Fox [ctb] (Author of the carData package; original source for EducationLiteracy , ExamScores , and FirstYearGPA.) , Douglas Bates [ctb] (Author of the MEMSS package; original source for MathAchieve.) , Thomas Lumley [ctb] (Author of the survey package; original source for apipop.) , Jeremy Finn [ctb] (Principal investigator; original source for STARplus (Project STAR).) , Andrew Raudenbush [ctb] (Researcher; original source for the classroom dataset.)


Documentation:   PDF Manual  


GPL-3 license


Suggests ggplot2, testthat, dplyr, knitr, rmarkdown


See at CRAN