If you’re looking for software tools that involve coding for creating and presenting academic content, here are some relevant options:

Jupyter Notebooks: Particularly popular in data science and computational research, Jupyter Notebooks allow you to write and execute code in various programming languages (Python, R, Julia, etc.) interspersed with explanatory text, equations, and visualizations. It’s commonly used for presenting research that involves code-based analysis or simulations.

R Markdown: R Markdown integrates R code with markdown syntax to generate dynamic reports, presentations (using frameworks like ioslides, revealjs), and dashboards. It’s widely used in statistical analysis, data visualization, and reproducible research.

Markdown + Code Editors (e.g., Visual Studio Code): Markdown paired with code editors like Visual Studio Code allows you to create presentations using markdown syntax and embed code snippets for live execution and demonstration purposes.

GitHub Pages: You can use GitHub Pages in combination with Markdown, HTML, and JavaScript to create interactive and visually appealing presentations directly from your GitHub repositories. This approach is useful for sharing and presenting projects that are hosted on GitHub.

R Shiny: R Shiny is a web application framework for R that allows you to create interactive web applications and dashboards. It can be used for presenting research results that involve interactive data visualization or simulations.

Python Libraries (e.g., Matplotlib, Seaborn, Plotly): For presentations involving Python-based analysis and visualization, libraries like Matplotlib, Seaborn, and Plotly can generate plots and visualizations directly within presentation frameworks like Jupyter Notebooks or Markdown.

Latex + Beamer: For a more traditional approach, LaTeX with Beamer class allows you to create academic presentations with precise control over formatting, equations, and figures, which can be particularly useful for technical and mathematical content.