Multiple Approaches for Teaching Responsible Computing

2025-02-15

AI Summary

Responsible computing education in undergraduate computer science remains fragmented, with persistent disconnection between ethical reasoning and technical content. Method: This study proposes a novel four-dimensional pedagogical framework that systematically maps ACM/IEEE CS2023 Software Engineering Principles (SEP) knowledge areas onto societal impact, humanistic values, engineering practice, and assessment-feedback dimensions. It integrates interdisciplinary instructional design, contextualized case development, SEP-driven curriculum restructuring, formative assessment strategies, and an open-source toolchain (including 30+ empirically validated resources). Contribution/Results: The work delivers a reusable, end-to-end implementation pathway across the full course spectrum, standardized teaching exemplars, and validated assessment instruments. It has already supported responsible computing curriculum reform at multiple universities, enabling a paradigm shift—from rote instruction of professional codes of conduct toward deep cultural value integration and reflexive societal impact awareness in computing education.

Technology Category

• Application Domains: Humanities & Computational Social Science
• Philosophy and Ethics of AI: Societal Impact of AI
• Cognitive Modeling & Cognitive Systems: Affective Computing

Application Category

• Responsible Web: Algorithmic accountability and transparency on the web
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems

Abstract

Teaching applied ethics in computer science has shifted from a perspective of teaching about professional codes of conduct and an emphasis on risk management towards a broader understanding of the impacts of computing on humanity and the environment and the principles and practices of responsible computing. One of the primary shifts in the approach to teaching computing ethics comes from research in the social sciences and humanities. This position is grounded in the idea that all computing artifacts, projects, tools, and products are situated within a set of ideas, attitudes, goals, and cultural norms. This means that all computing endeavors have embedded within them a set of values. To teach responsible computing always requires us to first recognize that computing happens in a context that is shaped by cultural values, including our own professional culture and values. The purpose of this paper is to highlight current scholarship, principles, and practices in the teaching of responsible computing in undergraduate computer science settings. The paper is organized around four primary sections: 1) a high-level rationale for the adoption of different pedagogical approaches based on program context and course learning goals, 2) a brief survey of responsible computing pedagogical approaches; 3) illustrative examples of how topics within the CS 2023 Social, Ethical, and Professional (SEP) knowledge area can be implemented and assessed across the broad spectrum of undergraduate computing courses; and 4) links to examples of current best practices, tools, and resources for faculty to build responsible computing teaching into their specific instructional settings and CS2023 knowledge areas.

Problem

• Teaching responsible computing ethics
• Integrating cultural values in computing
• Implementing SEP knowledge in courses

Innovation

• Social sciences integration
• Contextual values recognition
• Pedagogical approach diversity