Guided Inquiry and Scientific Competencies in Eighth-Grade Biology: Aggregated Data and R Code
Description
This repository contains the anonymized aggregated datasets and analytical materials associated with the study “Developing Scientific Competencies Through Guided Inquiry in Eighth-Grade Biology: A Pre-Experimental Study in Colombia.” The study examined an eight-week guided inquiry intervention involving 54 eighth-grade students at a private secondary school in Pereira, Colombia. The repository includes the English-language aggregated dataset, a data dictionary, the R script used to reproduce the descriptive analyses, reported in the manuscript. The available files contain aggregated response-level data only. No student-level identifiers or direct personal information are included.
Files
Steps to reproduce
Steps to reproduce 1. Download and extract the file guided_inquiry_scientific_competencies_colombia.zip. 2. Keep the original directory structure unchanged. The main files required for reproduction are: - IBL_scientific_competencies_aggregated_en.xlsx - analysis_script.R - DATA_DICTIONARY.md 3. Install a recent version of R (R 4.x is recommended). RStudio may be used as an optional graphical interface. 4. Open R or RStudio and set the working directory to the root folder of the extracted repository: guided_inquiry_scientific_competencies_colombia 5. Install any missing R packages before running the analysis. The main packages used by the script are: readxl, dplyr, tidyr, ggplot2, stringr, purrr, janitor, broom, openxlsx, knitr, kableExtra, and scales. Missing packages can be installed with: install.packages(c( "readxl", "dplyr", "tidyr", "ggplot2", "stringr", "purrr", "janitor", "broom", "openxlsx", "knitr", "kableExtra", "scales" )) 6. Run the complete analysis from R with: source("code/analysis_script.R") Alternatively, run the script from a terminal opened in the repository root directory: Rscript code/analysis_script.R 7. The script reads the English-language aggregated workbook: IBL_scientific_competencies_aggregated_en.xlsx It cleans and reshapes the archived data, calculates the descriptive pretest-posttest distributions, percentage-point changes, weekly high-performance percentages, descriptive linear trends, instructional phase summaries, class-section sensitivity checks, and perception questionnaire summaries. 8. Reproduced tables are saved in: outputs/tables/ Reproduced figures are saved in: outputs/figures/ Figures are exported in vector PDF and high-resolution PNG formats. The output folders are created automatically if they do not already exist. Important analytical note: The repository contains anonymized aggregated response-level data rather than student-level longitudinal records. Consequently, the script reproduces the descriptive analyses reported in the article but does not conduct paired student-level tests, individual growth analyses, reliability estimates based on participant-level response matrices, or multilevel models.