AI Guidance for Teachers

The Poorvu Center recommends crafting a statement that clarifies your course policies on the usage of AI. If we assume our students are already using AI tools in various ways, it is helpful for them to understand how you, as an instructor, want them to use or not use these tools and the rationale behind those choices. Students need to understand what you consider to be an academic integrity violation, as your policy may differ from a colleagues’. The simplest way to state a policy is to address it in your syllabus, but you can also have a discussion with your students in class. For additional resources, we offer examples of  AI policy statements from various Yale instructors.

Instructors should be direct and transparent about what tools students are permitted to use and the reasons for any restrictions. If students are permitted to engage with AI tools, you should be explicit about how you expect them to use them and how they should make you aware they’ve been used.

Some questions for you to reflect on when writing an AI course policy are:

• What are your personal views on AI?
• What does your department and field say about the use of AI?
• What course objectives could AI be useful or harmful for?
• Are there any skills that would be beneficial for students to know after Yale where AI could help?
• Will you be using AI in your instructor role in the course (e.g., provide feedback, write emails, etc.), and if so, how will you communicate that to students?

If you are co-teaching or working with teaching fellows, ULAs, or tutors, be sure that everyone on your teaching team is on the same page regarding your AI course policy.

 There is no tool or method to detect AI use (link is external) with any certainty. Turnitin (link is external) has acknowledged a reliability problem with its detection tool software, and Yale has not enabled this feature in Canvas. However, if you are concerned about a student’s use of AI, this can be reported to the Executive Committee.

If you suspect misuse of AI, as discussed in the Handbook for Instructors of Undergraduates in Yale College, it is good practice to talk to the student about your observations of the level of work or any changes in the work that may have caused you to suspect AI use. This becomes a discussion focused more on standards and the writing process and less on accusations.

Authentic Assessments

Authentic assessments are assignments that:

1. have a sense of realism to them.

2. are cognitively challenging.

3.  require authentic evaluation.

Authentic assessments also align with practices that prioritize student learning and make it harder to generate  generic responses with AI tools, including: 

• Asking students to use resources that are not accessible to generative AI tools, including many of the amazing resources in Yale’s collections.
• Using alternative ways for students to represent their knowledge beyond text (e.g., facilitating a discussion, recording a podcast episode). Consider adopting collaboration tools like VoiceThread for students to use for their assessments. 
• Asking students to share their work and respond to questions about it in-person, either as a presentation to the class or a short discussion with you or another member of your teaching team.

AI Literacy

Long & Magerko (2020) defines AI literacy as a “set of competencies that enable individuals to critically evaluate AI technologies, collaborate effectively with AI, and use AI as a tool online, at home, and in the workplace.” 

If students are expected to lead an AI-infused future (2024 Yale AI Task report), then it is crucial for instructors to help students develop the skills necessary to engage with these technologies. We have listed examples of AI literacies from Ng et al., 2021. As you review these, consider how these literacies can be integrated within your classroom (e.g., learning outcomes, assessments, in-class activities, etc.). 

• Knowing the basic functions of generative AI and understanding how generative AI applications work.
• Applying AI knowledge, concepts, and applications to different contexts and fields.
• Situating the creation and evaluation of AI within higher-order thinking skills (e.g., evaluate, appraise, predict, design).
• Understanding human-centered considerations (e.g., fairness, accountability, transparency, ethics, environment, safety) when using AI.

You can review our AI Literacy handout to learn more about these examples or engage with Yale Library’s AI Literacy framework. In addition, you can review this webinar series from the University of Kent.