If you teach at Western, you might be wondering how peer educators at the WaLC (Writing and Learning Commons) navigate conversations around AI with students seeking support. The WaLC team would like instructors to know that an internal AI policy exists, and that it was developed to be as faculty forward as possible and while the policy allows for some flexibility, it’s conservative in its application.  

By default, peer educators ask students who come to the WaLC what their instructor has written in their syllabus (or assignment instructions) concerning the course’s AI policy. If there is no policy to be found, peer educators won’t encourage students to utilize AI in any way. If there is a statement that allows for AI use, peer educators can assist “in areas provided on the syllabus, or if not stated, in areas such as brainstorming, gathering information, interpreting feedback, outlining, and quizzing” (see AI Decision Tree, developed by the WaLC). 

Additionally, the WaLC team has open conversations with their own peer educators who feel uncomfortable using AI themselves (see Step 1 of the AI decision tree). If they encounter a student whose professor requires their students to use AI and they neither are familiar nor comfortable using AI, they can refer the student to a peer educator who is.  

One recommendation both the WaLC and the CFC have is for instructors to have a conversation with students of what is to be considered acceptable AI use in addition to having a course specific AI policy in the syllabus. For example, some students are still unsure if they can use certain software (Grammarly is a common example) in all of their course work, only for some activities, or not at all.  

The WaLC’s goal is to empower students to achieve their academic goals. To that end, the WaLC’s peer educators have come up with some creative ways in which they have utilized AI to help students. In one case, a recreational therapy major struggled using person-first language when discussing a patient’s disability. With the help of AI, they curated a vocabulary list consisting of words and phrases that helped the student expand their repertoire and become a more confident writer. Another example includes a student who couldn’t make sense of their instructor’s track changes and suggestions on their first draft since there weren’t any additional comments provided. They asked AI why the paper was marked up the way it was and concluded that a lot of their writing had been repetitive.

Sometimes, students do come into the WaLC with AI-generated writing. Peer educators are trained to approach those conversations similarly to the conversations about suspected plagiarism. These conversations all begin by asking open-ended, non-judgmental questions: “Do you know how to cite?” or “Did you forget to add attribution here?” to detect if plagiarism they noticed occurred unintentionally due to a lack of knowledge. Likewise, when a peer educator suspects AI use, they also ask probing questions to find out if and how AI was used by the student. Peer educators will always advise students to adhere to the instructor’s policy, and they remind students if they notice when AI was used, their professors will notice too.  

If you have questions about the WaLC’s AI policy, feel free to reach out to Haylee Melton at wilkieh@wcu.edu; if you would like support on how to approach your own AI policy, reach out to Coulter Faculty Commons at cfc@wcu.edu.

The CFC would like to extend its thanks to Haylee Melton,
Associate Director of the Writing and Learning Commons, in collaborating on this article.