Introduction: Data science in education—you’re invited to the party

This chapter welcomes readers and gives an overview of the book, its themes, and its structure. It walks through what it means to learn about data science in education and the complex nature of education systems. The chapter describes how we clarify the data scientist role through a series of walkthroughs that introduce foundational skills for those new to learning R, run analysis on student perceptions of learning and student performance data, and describe how to use aggregate data. This introduction presents an overview of the key concepts discussed in the subsequent chapters of this book. The book welcomes readers and gives an overview of the book, its themes, and its structure. It walks through what it means to learn about data science in education and the complex nature of education systems. The book begins by offering a primer for data science in education, including a discussion of unique challenges and foundational skills in the programming language R. Education consultants study how students perform on course work and even how they feel about class materials. In many education settings, school administrators and their staff may have never had someone around who deeply understands education, knows how to write code, and uses statistical techniques all at once, as data science in education could be defined.