Addressing AI Tool Use in Classes

With all the hype and hex around AI, be sure to set clear expectations for students

Did you know there is a UMass-only GenAI platform? 

 If you or your students are using AI tools, consider using the UMass GenAI Platform housed within UMass Amherst's secure infrastructure. Students, faculty, and staff can access this platform by logging in with their UMass NetID, which provides access to leading generative AI models such as OpenAI (ChatGPT), Anthropic (Claude), Meta (Llama), Cohere, Mistral, and more. User data is encrypted both in transit and within the system, and no data used to train models outside the UMass platform.  Use of the platform is free, although there is a daily cap.

If you are concerned that students in your classes may be tempted to use an AI to circumvent the learning process, here are some suggestions on how you can shape the use of these tools.  

Be clear and specific about your expectations 

Companies are actively promoting generative AI tools as labor-saving devices. The default faculty senate policy is to ban all use in classes, while allowing individual instructors to set their own policies. With so many mixed messages, it is important to be very clear with your students about your expectations. Standard academic honesty statements about plagiarism and paper-buying should cover the most obvious misuses of AI, but adding specific language will help make your position clear (see below for example language). 

Generative AI can be used for more than content creation. GenAI tools can also be used to help with other cognitive processes such as: summarizing readings, organizing ideas, planning projects, and getting feedback on drafts. If your course objectives are focused on developing such skills, make it clear to students that you are discouraging/prohibiting use of AI for these activities because it will interfere with their development of these skills. If use of AI for cognitive support will not interfere with your course objectives, addressing this in your AI policy will let students know that this kind of use is allowed. Keeping in mind that for some first generation, international, and neurodivergent students, AI LLM tools can provide one-on-one support that  may be hard to find at a large university. 

Craft a syllabus statement addressing AI use

The first place to set expectations about AI is in your syllabus. Without a clear statement, students are left to interpret and make assumptions about what is and is not allowed (especially when some companies actively push AI use on students by implying certain uses 🙄 are OK.)  

Resources and Templates to help craft an AI policy: 

Note about enforcing AI policies

GenAI Large Language Models (LLMs) have evolved at a rapid pace, and it is becoming more difficult to spot AI-generated content in students’ work. While some AI content is generic, bland, slightly off topic, and can include hallucinated sources and evidence, it is important to keep these two issues in mind: 

  • Automated "AI checkers" do not have a good track record of accurately identifying AI-generated content, and should only be used as a tool to flag work for further checking by a human.
  • Some language use that gets flagged as AI-generated (by both humans and automated tools) can also be produced by a human who is less familiar with typical language conventions used in AI training models, which can include international, neurodivergent, second-language learners, and other marginalized language groups. 

If you have the capacity (or a small class), it is best to assume good intent and approach students who you think may be using AI with questions before dropping accusations of unethical behavior. 

Point out how using AI can affect learning 

Friction plays a critical role in a student's learning, motivation, and development of communication skills that aid in making meaningful connections with others. By removing friction, AI and LLMs can circumvent the learning process by eliminating the much-needed difficulties that drive learning and growth. 
No matter if you decide to ban or allow the use of AI in the classroom or on class assignments, it is important to remember that struggle is part of the learning process, and reminding your students of this is crucial. Below are a few suggestions of how to promote friction as a positive part of the learning process: 

  • Provide guidance that will help students maintain productive friction 
  • Design assignments where students are tasked with comparing an AI output with course readings to uncover biases and discrepancies 
  • Ask your students to outline their reasoning for using AI on an assignment. This is also an excellent way to see what topics students are having difficulties with in your class 

Resources with more about the importance of friction in learning: 

Design assignments that favor authentic learning

When an assignment is crafted like an AI prompt ("Please summarize the main points of...") it can be hard to resist using AI as a shortcut. When the instructions for an assignment seem too vague, or too complex, AI can offer more certainty. If you are concerned about AI use, and have the time to make adjustments to your assignments, there are ways to design assignments that can make AI use feel less productive.  

Starter suggestions

  • Personal reflections and application of content to individual experience.
  • Low stakes writing assignments (or survey responses) early in the class to get a sense of writing style and ability before assigning longer, higher-stakes assignments.
  • Split larger assignments into stages that are turned in along the way for review and revision.
  • Formats that require in-person work or are not (yet) as easy to produce with AI; such as handwritten responses on paper, visualizations, in-person presentations, or recordings of live demonstrations. (Caution: many of these approaches will require accommodations for people who have been able to typically use technologies to overcome physical or cognitive limitations. Be prepared to offer alternatives.) 

Many of these are adapted from strategies developed by Peter Elbow and outlined in several of his teaching handouts and articles on Low Stakes Writing Assignments. 

Design assignments that critique and reflect on AI use 

Use of GenAI is becoming commonplace in the workplace. Before students are asked to use AI for a job, we can help them better understand what AI is capable of doing and the risks of over-reliance on large language models that simply spout the "most likely answer" with a confidence that doesn't allow for bias, uncertainty, or edge cases that exist no matter what probability has to say. If you have the bandwidth, making AI use an active part of your course can help students in the long run. 

Starter suggestions: 

  • Explain your own position on the use of genAI tools (pro, con, skeptical) so that students understand your views on the topic. 
  • Run an assignment prompt through AI and share it with students to critique before they write their own versions of the assignment.
  • Ask students to write their own response to a prompt, then ask an AI, then write up a comparison of the two works.
  • Assign prompts that can reveal biases or misconceptions in the models (my favorite is "explain Bloom's Taxonomy") and ask students to critique the responses.
  • Prompt students to interrogate the AI after getting a response and report on the exchange: "Why did you give this answer?", "how certain are you that this is correct?", "what did you leave out of this response?"
  • Explain the probabilistic nature of large language models and have students look for patterns that reveal how the output is shaped by a probability-based word guesser, not an actual intelligence.

Where to learn more  

Torrey Trust in the College of Education continues to provide excellent advice on adapting to student use of AI in ways that look more closely at motivations of students, concerns of faculty, and the true functionality of AI tools. These posts are a good place to start:

If you have questions or concerns about AI tools, the folks in the college's digital learning group are happy to chat about creative options and connect you with strategies that match your objectives and your capacity. Contact digitallearning [at] umass [dot] edu or visit their page on Addressing AI tools.