Evaluated December 2021
This module has students role play various roles surrounding a potential rollout of self-driving busses in a city. This module could be used in a networking, computer vision or cyber security course. These scenarios are designed for class sessions that run up to 2 hours in length. Therefore, this module will require finding that amount of time in the term.
It covers material in Intelligent Systems/Fundamental Issues, Information Assurance and Security/Foundational Concepts in Security.
In this role-playing module students are divided into roles and provided some perspectives associated with those roles. There is outside reading to help students better understand issues associated with each role. By identifying additional readings or videos on disabilities and how to understand social dynamics related to neighborhood configurations, an instructor can give students a more in-depth experience. This module offers great opportunities for computer science faculty to collaborate with faculty in psychology, sociology, geography and environmental studies. An instructor with background in general ethical frameworks or diversity and equity will be well-prepared to support students as they move through this exercise. Faculty must be prepared to actively facilitate discussions regarding the viability of each scenario.
Students who have had at least one course in computer science prior to engaging in these scenarios will be in a better position to understand the role that computing professionals play. In addition, students who have had at least one course in philosophy (e.g., ethics), cultural anthropology, psychology, social psychology, sociology or geography will be better prepared to discuss aspects of these exercises.
Students are expected to engage in either substantial prework based on provided scenarios, or they are expected to quickly bring discrete experiences to bear to perform particular roles. Upper division students, with ability to quickly assess an assignment and who have developed both strong compare contrast and analytic ability will handle these scenarios best.
This module will resonate most with students in urban environments.
General learning outcomes are provided for the students. More specific ones could also be easily developed. There is a grading guideline and an instructor adopting this module will need to develop ways to interpret the results.
The evaluation of this module was led by Colleen Greer and Jaye Nias as part of the Mozilla Foundation Responsible Computer Science Challenge. Patrick Anderson, Emanuelle Burton, Judy Goldsmith, Darakhshan Mir, Evan Peck and Marty J. Wolf also made contributions. These works are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.