Discovering Computer Science: Interdisciplinary Problems, Principles, and Python Programming is a problem-driven introduction to computer science that foregrounds interesting applications, providing context and connections to students' prior knowledge and interests. This approach both facilitates student learning and encourages them to discover the scope of the subject beyond simply learning coding.

Organized around carefully chosen and sequenced applications from the sciences and digital humanities, the text eases students into computational thinking, using a spiral approach to teach Python programming that orients them to problem solving first and encourages using pseudocode and trace tables early in the process. Fundamental computer science principles, such as abstraction, efficiency, testing, and algorithmic techniques, are incorporated throughout to build good programming habits from the start of a student's learning. Integrated hands-on examples and reflection questions encourage students to actively engage with the material. Over 750 curated end-of-section exercises are designed to provide further practice, and some more complex ones may form the basis of longer-term assignments. Wherever possible, the exercises are drawn from real interdisciplinary problems.

The book is ideal as a first course for computer science majors, a more targeted disciplinary computing course or, at a slower pace, any introductory computer science course for a general audience.

All of the reflection questions and exercises have been implemented in PrairieLearn, and are available to adopters. The accompanying website - discoveringcs.net - provides programs and data files referenced in the text, additional optional content, and links for further exploration.