Version: v1.3.2 • License: MIT • Zenodo Archive: 10.5281/zenodo.17010174

CourseDemandR

CourseDemandR is a data-driven tool that supports General Education curriculum Planning through statistical modeling and scenario planning

Version 1.3.2 – Release Notes

• Correlation Heatmap Tooltips

  • Added hover tooltips to the GE Area correlation heatmap showing the pairwise GE areas and Pearson correlation value.
  • Sample size (number of terms) now appears in the heatmap title for interpretability.

• Interactive Cross-Tab Filtering

  • Clicking on a point in the Section Count vs. Fill Rate by Course plot now filters the Overview tab by Subject.
  • Enables dashboard-style drilldowns.

Notes

This version builds on v1.3.1 by adding interactive tooltips and cross-tab filtering. It does not alter the app’s required input structure.

Local Deployment of CourseDemandR

This section provides step-by-step instructions for running CourseDemandR locally using R and RStudio.

Preliminaries

Ensure the following are installed on your machine:

• R (version 4.4.2 or higher): Download R
• RStudio (IDE for running Shiny apps): Download RStudio

Step 1: Get the App Files

Option 1: Download as ZIP

1. Visit the GitHub repository: https://github.com/emontoya2/CourseDemandR
2. Click on the green "Code" button and choose "Download ZIP"
3. Unzip the downloaded folder to a local directory on your computer

Option 2: Clone via Git (for those familiar with Git)

git clone https://github.com/emontoya2/CourseDemandR.git

Step 2: Open the App in RStudio

1. Launch RStudio
2. Navigate to the folder containing the app files
3. Open the app.R file or the .Rproj file (if available)

Step 3: Install Required R Packages

In the RStudio Console, run the following command to install dependencies:

install.packages(c("shiny", "shinyjs", "shinyBS", "tidyverse", "DT", "broom", "ggrepel", "reshape2", "plotly"))

Additional packages may be installed dynamically on first run.

Step 4: Launch the Application

1. With app.R open in RStudio, click the "Run App" button in the top right
2. Or run this in the Console:

shiny::runApp()

This will launch the app in your default web browser.

Optional: Run Online (No Installation Required)

You may also access the hosted version at:

https://emontoya2.shinyapps.io/coursedemandr/

Reproducible Environment

Full R session details are recorded in docs/sessionInfo.txt.

Data Requirements

The application expects a structured CSV file with aggregate GE course enrollment data. Required columns include:

• College, Course, Catalog, Term
• Avg_enrl, crs_section_cnt, "Avg_capenrl
• GEcapsize, Req_1, Req_2

A sample dataset is included with this release for demonstration.

Note: On launch or upload, the app now runs validate_data.R to verify your CSV matches the expected schema (required columns, no NAs, numeric ≥ 0). Any violations will be logged in validation_log.txt.

Citation

Montoya, E. L. (2025). CourseDemandR: A statistical analysis and scenario-based planning tool for general education curriculum planning. SoftwareX, 32, 102412.