Getting Started

If you are coming to computational educational research from a social science background, the technical setup can feel like the hardest part. This section is designed to lower that barrier and help you build a practical foundation before moving into method-heavy chapters.

Think of this section as the minimum viable toolkit for the rest of the book. The goal is not to teach everything about R or Positron, but to give you enough structure to reproduce examples, adapt workflows, and work confidently with your own data.

The three chapters in this section establish that foundation:

• Positron and RStudio introduces your working environment, project organization, and workflow habits that support reproducibility.
• R covers core file types, execution patterns, and practical help-seeking strategies for common coding roadblocks.
• Tidyverse builds the day-to-day data workflow vocabulary for reading, cleaning, transforming, and visualizing data in R.

By the end of this section, you should have a functioning analysis environment and a clear workflow for moving from data to interpretable output.

How the Full Book Connects

This book follows a four-part progression:

• Getting Started builds the technical and workflow baseline.
• Computational Methods applies text, network, and numeric approaches to core research tasks.
• LLM Methods introduces cloud/local LLM workflows and AI-assisted analysis with explicit attention to responsible use.
• Communication focuses on sharing computational research transparently and reproducibly.

Across all sections, we prioritize the same principles: methodological clarity, reproducibility, and responsible interpretation of results.