Avoiding stereotypes helps foster an inclusive student community. Stereotypes are fixed, overgeneralized beliefs about a group of people. They can make individuals feel unwelcome and unfairly judged. By avoiding stereotypes in both verbal and written communication faculty can help all students feel welcome and seen as individuals. Faculty should also discourage students from using stereotypes in their communication, including in their assignments and during class discussions.

Some suggestions

Choose your examples wisely. Examples can inadvertently reinforce stereotypes so try using ones that are not stereotypically associated with one group, e.g., cell phones, the color green.

Set expectations for professional behavior. This includes, but is not limited to, the expectation that students will not use derogatory or potentially insensitive language with each other, and that they will refrain from using it in their assignments, e.g., “The picture should not include hateful, offensive, or otherwise inappropriate images.”.

Attend to the physical and digital environments. Labs, classrooms, and social spaces can reinforce stereotypes about who the “typical” computer science student is. So can webpages. Check out your program’s physical spaces and websites to see what messages they may be sending.

Even “positive” stereotypes can hurt. Be careful making even seemingly positive comments that rely on stereotypes (e.g., “women are so good with. . .”). They can create division and trigger stereotype threat.

Examples from the collection


Embedded Ethics: Pandemic Exposure Notification Systems and Giving Ethical Justifications

In this follow-up to "Embedded Ethics: Pandemic Contact Tracing and Ethical Trade-Offs" [6], students revisit a trade- off they faced in that first module. There, students brainstormed about the rich data one might collect to build a powerful app for contact tracing, discovered that this may facilitate violations of privacy, considered the harms that can come from this, and recognized the trade-off between protecting privacy and gathering data to support the fight against the spread of a disease such as COVID-19.

CS2 Graphical Photo Library Project

This project steps learners through a series of assignments that culminate into a photo viewer/archive tool. The assignments are designed to emulate a software development "sprint" in the Agile development process parlance. Each sprint consists of an assignment that builds off the code of the previous assignment, and is by itself a valuable piece of the overall end product.

Our aim is to give students the feeling and experience of working on a large project via a sequence of carefully-crafted homework assignments. This project helps students gain experience with Object Oriented Programming in Java, combined with software development techniques, commenting and documenting code for maintenance, unit testing with JUnit, exception handling, event-driven programming and use of pre-built Java Swing components. The project culminates in a fully-functional graphical user interface and leaves plenty of room for creative expression.

The project was designed and developed with a neutral position regarding gender, race, and other protected classes. We believe the end product has a universal appeal for users of technology and the potential software developers of tomorrow.

Lottery and the Wealth Gap

This assignment helps students gain experience and proficiency with lists, loops, and random number generators. Students will learn how to think through and write branching logic, plot data, and modularize their code. Through this assignment, students will learn how the lottery contributes to a growing wealth disparity by redistributing money from low income families to middle and high income students in the form of scholarships. With this basic simulation, students can visualize and learn about the mechanisms that cause the wealth gap to widen. This handout is based on a math assignment by Justin Allman.

ACM Digital Library Entry

CS2 Syllabus

The CS2 course introduces object-oriented programming, data structures, and more sophisticated algorithms than in CS 171 (Computer Science I) which is a prerequisite for this course. You are not expected to have any prior experience with Java. In terms of the ACM’s Computer Science Curriculum 2013, this course addresses the following knowledge areas: • Algorithms and Complexity (AL) • Discrete Structures (DS) • Programming Languages (PL) • Software Development Fundamentals (SDF) • Software Engineering (SE)

This course is a required intro-level course for two of the three Lewis & Clark CS departmental majors: Computer Science and Computer Science and Mathematics.

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