R Markdown as a dynamic interface for teaching: Modules from math and biology classrooms.

Area of Science:

• Educational Technology
• Computational Science Education

Background:

• Interactive technologies are transforming academic teaching methods.
• R Markdown offers a versatile platform for creating dynamic educational content.

Purpose of the Study:

• To explore the utility of R Markdown for developing interactive classroom modules.
• To demonstrate R Markdown's effectiveness in teaching computational concepts and data analysis.

Main Methods:

• Utilizing R Markdown to combine R code, formatted text, and LaTeX for reports.
• Developing interactive modules for courses in Computational Modeling and Data Visualization.
• Integrating student coding and text response within R Markdown documents.

Main Results:

• R Markdown facilitated guided exploration of mathematical models (e.g., herd immunity).
• It effectively taught R programming fundamentals and data visualization techniques.
• Students learned to create reproducible data investigations using R Markdown.

Conclusions:

• R Markdown serves as a powerful, dynamic tool for enhancing teaching and learning in computational and data-intensive courses.
• Its flexibility supports both instructor-led modules and independent student assignments.
• R Markdown promotes active learning and the development of essential programming and data analysis skills.