Using the Code
Reinvigorating a Culture of Curiosity and Learning in Computer Science Education
We invite all computing educators, and especially those who do not have significant training in applying ethics, reflective practices, and thoughtful consideration of responsibility in teaching, research, and service, to consider moving their teaching away from a focus on having students create artifacts to one where students build understanding through an iterative process based in cooperation and collaboration. We encourage these practices to be applied throughout the computing educators efforts in teaching, research, and service.
Motivation: Being a good member of the faculty and being a good student has always been a challenge. Deep learning - that is, actual learning - can be emotionally challenging. With the advent of the internet, the opportunity to cheat the learning process and avoid the need to make an intellectual commitment to bettering one’s self is an easy choice. While this workshop would have been relevant thirty years ago, it has become especially significant with the unleashing of generative AI. It has changed the academic landscape in ways that we are still discovering and, unfortunately, still uncertain how to react to. Our workshop offers strategies that can help attendees, their students, and social structures (e.g. departments, review panels, organizing committees) that they are a part of become better equipped to deal with those who are more opportunistic in their methodologies.
About the workshop: In its purest form, the goal of teaching and learning is to cultivate a self-motivated intellectual curiosity. It is not uncommon for educators to take their own intellectual curiosity for granted and even ascribe that same level of enthusiasm for learning to their students. Over the last decade or two there have been an increasing number of social, political, structural, and technical changes in the world that nudge people (faculty and students included) to prioritize frictionless experiences that feel good and avoid challenges to their identity. As a result, the intrinsic value of learning, especially difficult or time-consuming learning, may not be as deeply ingrained in or rewarding to as many students (and faculty) as in years past.
This workshop explores approaches to education and its structures that center principles to advance a deeper commitment to intellectual curiosity. These more mindful approaches can also be applied to the administration of teaching and learning, as well as research activities. As computing professionals, we can use the Principles of the ACM Code of Ethics and Professional Conduct as a starting point. By centering the public good as the paramount concern, these principles are reflective of values held by many in the computing community and support a culture of creative, curious, and reflective practice.
As a more concrete example of our motivation, consider the impact of the public release of generative AI tools. While instructors have long had to adapt to changing technologies, these tools represent a fundamental shift. Prior evolutions, from the introduction of calculators to Wikipedia, gave learners powerful tools while still depending on the primacy of the user’s choices and engagement. In contrast, generative AI tools make it considerably easier for users to disengage, as the tools are designed to surmise the user’s goals with less explicit statements of intent. That is, generative AI makes it possible to lull students into a passive learning mode that avoids active engagement with difficult or frustrating experiences, while permitting the impression that whatever has occurred counts as “learning” because the assignment has been completed.
While generative AI tools provide a significant aspect of our motivation, this session is not focused solely on the question of how to teach with (or against) these tools. Our goal is to give space for discussing and reflecting on how we can choose to embody and model more intentional educational practices.
Presenters:
- Emanuelle Burton, University of Illinois, Chicago
- Michael Kirkpatrick, James Madison University
- Marty J. Wolf, Bemidji State University
Using the Code: Case Studies
With the release of the updated Code of Ethics, ACM has created companion case studies that demonstrate how the principles of the Code can be applied to specific ethical challenges. Illustrative examples of hypothetical violations of or adherence to specific principles found in the Code—highlighting key nuances and directives—form the basis of the case studies.

ACM Code of Ethics
The ACM Code of Ethics and Professional Conduct was updated in 2018 to address the significant advances in computing technology since the 1992 version, as well as the growing pervasiveness of computing in all aspects of society.
