Our campus teaching community is broad and diverse with varying disciplinary needs and expectations. Because of this, there isn’t a mandated, one-size-fits-all approach to AI in the classroom and, accordingly, classroom practices with AI vary. This flexibility allows you to start with your stance on AI and tailor your course appropriately—but it also means designing policies and assignments for students who are left grappling with different expectations from class to class. Each of us has an obligation to  clearly communicate to students about how and why our stance on AI and other technology has shaped the course, its content, its assignment and/or its policies. The Writing in the Disciplines website on teaching and AI addresses these issues and more.

The Writing in the Disciplines Program regularly offers workshops on teaching and AI, such as: 

• Developing an AI policy that helps students focus on the relationship between learning, technologies, and assignments. If your AI policy is organized around a desire to police and surveil your students, it can create an unhelpful atmosphere of mistrust.  Your AI policy is best rooted in your teaching philosophy, your field, and your sense of how the larger context for AI affects learning.
• Communicating with students about AI.  Whether or not your course/assignments require or prohibit the use of AI, it’s important to keep a conversation going with students so they understand how your technology choices fit into your course goals and your discipline. A syllabus policy is important, but it is not the only vehicle for helping students learn how to engage with your expectations.
• Incorporating AI into your assignments or adjusting assignments in light of what AI makes possible.  There are many ways in which assignments can be adjusted in light of AI.  Some instructors are incorporating assignments that explicitly invite students to test and evaluate AI output.  Others have assignments that rely on AI tools to facilitate tasks.  In other cases, instructors are adjusting assignments to rely more on local sources or data, or to work in contexts that would be less appealing for AI use.  
• Learning about AI tools. Whether or not you are inclined to incorporate AI in your teaching, it is a good idea to learn enough about common tools to develop a critical perspective for your field.  In addition, considering the environmental, ethical, and social implications of AI use may affect which tools you choose to use and how.

AI tools offer many possibilities for instructors and students.  Course and assignment goals are the foundation of all decisions about AI. Your approach to incorporation or exclusion of AI will likely vary course to course and assignment by assignment; it’s best to think about what fits your particular learning goals. Transparency and clarity with students are the best ways to keep the emphasis on learning with integrity.

Some instructors find AI tools useful for course preparation, with uses varying from querying generative AI tools to get feedback on assignments (using prompts like “identify any passages a sophomore student might find confusing” or “suggest ways to make this assignment more concise”), to using AI tools to draft slides or suggest topics. 

AI tools have varying capacities for writing processes.  The Writing in the Dsciplines website has a section on the varying roles AI tools might play in helping writers manage their work. Khalifa and Albadawy (2024),  in Computer Methods and Programs in Biomedicine Update, provide an overview of six domains in which academic writing can be enhanced by various sorts of AI tools (their literature review trends heavily toward science sources). The American Psychological Association’s “The Promise and Perils of using AI for research and writing” offers a more nuanced analysis of AI use for academic writing and includes information on transparency and citation.