Make it matter for students by connecting computer science to other fields, such as medicine, the humanities, and media. By showing how computer science concepts and skills are used in other fields, you can engage students who may not have considered computer science as a major or career.

Some suggestions

Use interdisciplinary problems. Assign homeworks, labs, and projects that have students apply what they are learning to interesting problems in other fields. The EngageCSEdu collection has lots of examples!

Draw on the expertise of colleagues from other fields. Worried that you can’t make the interdisciplinary connections yourself? Ask around for colleagues who do computational work in their fields. Then have them come talk to your students or collaborate with them on some assignments.

Introduce students to cross-disciplinary computing fields. Highlight the contributions made by other disciplines to new interdisciplinary fields in computing. These are often referred to as 'x-informatics' (e.g., bioinformatics) and 'computational y' (e.g., computational linguistics).

Examples from the collection

Lab 6 - Impressionism and Implicit Functions (Looping 2D Space)

This is the sixth lab in a course on computational art (CS1) using Processing (https://processing.org/overview/). In this lab, students write a program that creates an image using an implicit representation of geometry that is drawn using shapes to emulate paint strokes.

In this lab, students will:

Engagement Excellence

Computational Creativity Exercise (CCE): Storytelling

In this assignment students work as a team to develop chapters of a story where the first and last sentence of the chapter is prescribed. Students first work independently developing their own chapter and then work collaboratively to identify and resolve logical inconsistencies in the chapters in order to produce a final coherent story.  This exercise will allow students to practice problem decomposition, abstraction, and evaluation, and also debugging and testing.

Engagement Excellence

Problem Set 7: Simulating The Spread of Disease and Virus Population

In this assignment, students design and implement a stochastic simulation of patient and virus population dynamics. Using Python and pylab, students must reach conclusions about treatment regimens based on the simulation results by implementing classes that model the virus population and running an analysis on a 'no-drug treatment' simulation.

Engagement Excellence

Resources