EESE: Collaborative Research: Understanding and Preparing Future Computer Professionals for the Ethical Complexities of a Diverse World

University Of Wisconsin-Stout, Menomonie WI

Investigators

Abstract

Are computing professionals adequately prepared for the ethical challenges that they will face in an increasingly global and interdisciplinary workplace? In this multi-institutional research/education project, the PIs will investigate the gap between the need for ethical computing professionals and the ethical learning that occurs in graduate computing programs. They will then apply these insights to develop and disseminate best practices in graduate ethics education. The mixed-method research combines surveys, interviews, focus groups, content analysis, and experimental design, and will be conducted in partnership with ACM's SIGCAS and the IEEE's SSIT. The project will begin with an investigation of computing programs and courses at four diverse institutions: a traditional research 1 university, a rural polytechnic, an urban liberal arts college, and a leading institution for online education. What are the existing goals and strategies used in graduate computing ethics education at these sites? What ethical issues are covered? What pedagogical approaches and materials are used? Faculty and students will be surveyed and interviewed about their perspectives on computing ethics education. Observations of teaching ethics across the courses will be conducted at each institution by the project team and the evaluation team. With baseline data from these four institutions, the PIs will survey members of leading professional associations to gauge alignment between industry practice and interests and the education in ethics provided by postsecondary institutions. Finally, the PIs will refine a set of best practices and pedagogical recommendations for CS ethics education, and disseminate their findings along with examples of teaching materials designed to be applicable across a range of institutional settings. Specific research questions to be addressed include: 1. What specific ethical issues are CS instructors currently teaching and what pedagogies are currently being used in graduate-level computing courses? a. What are the similarities and differences in computing ethics issues covered within curricula across different institutions? b. What materials (texts, readings, videos, simulations, social media, etc.) are used in classes? 2. How can professionals? experience in the computing industry enrich teaching about ethical challenges in the workplace? a. What do computer professionals think students should know about ethics before entering the workplace? b. How do computer professionals think this information can best be conveyed? 3. How can computing ethics education be improved? a. What do CS students need to learn about ethics that they are not currently learning? b. What are the best pedagogical approaches for teaching students these ideas? Project outcomes will include a report on the state of ethics education in graduate computer science/technology, a report on industry needs for an ethically knowledgeable workforce, and recommendations for best practices in ethics education effective in graduate education and the workplace. The project will ultimately result in computing professionals who are more attuned to their ethical responsibilities to the public, leading to more reliable computing systems. Broader Impacts: This work will fill an important gap in the research literature about the appropriateness and effectiveness of pedagogical approaches currently used to increase graduate computing students' awareness of ethical issues relative to the challenges that they will face in the workplace. Results of the study will be based on, and thus applicable to, a broad range of stakeholders in graduate computing ethics education, and thus could transform curricular standards promulgated by professional societies such as the ACM and IEEE. The innovative mixed-method approach that will be used has merit not only for this study but could also be applied to future studies in other domains.