Discussion Boards in an AI World

October 2025
AI, Discussions

A common pattern looks like this: a student copies your discussion prompt into a large language model (LLM) like ChatGPT or Gemini and pastes the generated answer as their own post. When it’s time to reply to peers, they copy a classmate’s response back into the LLM and paste the “peer reply” it provides. The result? A conversation of bots talking to bots: efficient, maybe, but not conducive to learning.

The good news is that we can design discussion boards that invite authentic student thinking and make AI shortcuts unattractive or easy to spot. Here are five proven strategies.

Use Multimedia to Change the Medium of Expression

Discussion boards don’t have to be all text. Try formats like:

a narrated two-minute video (with captions) explaining a concept, experience, or reflection.
an annotated image or infographic that visually represents an argument, process, or comparison.
a brief podcast-style reflection sharing insights or relevant stories.

For peer responses, invite students to engage through the same or complementary media, such as replying to a classmate’s video reflection with their own video response or providing embedded feedback by adding comments or highlights directly within a copy of a classmate’s infographic.

Why It Works AI isn’t as strong at image, video, and audio generation as it is at pure text generation. Switching the medium adds friction, makes AI easier to spot, and makes authentic participation the easier path.

Keep in Mind Multimedia assignments can create accessibility and technology barriers for some students. Be clear with your expectations and allow alternative options to help ensure equity.

Ask for Highly Specific, Personalized, Contextual Responses

LLMs are good at generic writing but often falter when prompts are tied to unique contexts. For example:

“Identify a challenge or opportunity in your local community. Describe the issue in detail and propose one actionable improvement.”
“Analyze hospital staffing data from your own department and propose a scheduling solution.”
“Think back to a formative learning experience from your own education or career. Describe the setting, what made it memorable, and how it shaped your approach to learning or professional growth.”

Gather student context early (e.g., interests, workplaces, local issues). By getting to know your students and asking them to work through personal/local applications, you should be able to identify whether discussion posts accurately reflect their experiences and perspectives.

Why It Works Consistent individualized detail is difficult for AI to fabricate believably, especially over the arc of an entire course. Students are also more likely to engage actively in discussions that directly apply to their own lives, interests, and/or professional aspirations.

Keep in Mind Even personalized prompts can be gamed with creative prompting or fabricated details. You may need to verify real student engagement through patterns over time or follow-up conversations rather than assuming all personal details are genuine.

Lean Into Authentic Assessments

Authentic assessments ask students to apply course knowledge and skills to complex situations that mirror the real world. Have your students tackle realistic, context-rich tasks that require applying course concepts and defending their decisions, such as:

designing a training plan for their workplace.
analyzing a local environmental issue.
developing a community outreach proposal.

Require them to explain the how and why of each choice and to reflect on possible next steps.

Why It Works Authentic assessments demand subjective judgment, decision-making, and reflection. Because the work is tied to genuine contexts and the student’s own reasoning, AI often struggles with the nuanced choices, lived details, and process explanations required.

Keep in Mind Authentic assessments often take more time to design and grade because they emphasize open-ended, individualized responses. Each student’s work looks different, which makes feedback more time intensive. Clear rubrics and exemplars can help ease the grading process and prevent overload.

Require Course-Specific Evidence

Ask students to support their ideas with specific references to course materials, such as timestamps in lectures, quotes from assigned readings, or references to previously covered topics. Prompts might include:

“Refer to at least one example, quote, or concept from this week’s video lecture. Include the timestamp and explain how it connects to your post.”
“Cite a specific quote from one of our assigned readings that supports or challenges your argument.”
“Reference a key concept or application from last week and explain how it connects to this discussion.”

Clearly state these expectations in your discussion instructions and grading criteria so students understand that references to course materials are required components of participation.

Why It Works Because LLMs cannot access or recall your specific course content, students must engage directly with materials to respond accurately.

Keep in Mind Students can still attempt to mimic engagement by paraphrasing course concepts vaguely, using false citations, and/or superficially inserting course-specific references into AI generated outputs. You may need to spot-check citations and model what genuine integration of course materials looks like.

Have Students Keep an AI Usage Log

Explicitly allow students to use AI but ask them to document:

the exact AI prompts they used.
the raw AI output.
how they revised or built upon it.

This transparency discourages wholesale copy-paste. Mismatches between the declared process and the final post can quickly flag questionable work.

Why It Works Disclosure creates accountability and provides insight into the student’s learning process.

Keep in Mind Some students may be hesitant to give full details of their AI use, especially if they fear penalties. This strategy works best when you foster psychological safety and frame the log as a tool for reflection, not surveillance.

The Big Picture: Make It Worth Answering

These strategies should help you avoid the dreaded “AI talking to AI,” but they’re only part of our recommended approach. Students often turn to AI because it seems faster or easier. When you make a strong case that your discussion boards are worth their time and creativity, that temptation drops.

Ultimately, students are more likely to engage honestly if the discussion is dynamic, relevant, and uniquely theirs. When discussions spark curiosity and ownership, authentic participation outshines anything a bot can produce.

References

Bielousva, G. (2023, April 24). Creating AI-proof assignments: A guide for university professors in social sciences and humanities. LinkedIn. https://www.linkedin.com/pulse/creating-ai-proof-assignments-guide-university-social-gra%C5%BEina/
Carleton College. (Summer 2025). AI-resistant assignments. https://www.carleton.edu/writing/resources-for-faculty/working-with-ai/ai-resistant-assignments/
Colorado State University. Academic integrity: How do I AI proof my assignments? https://tilt.colostate.edu/how-do-i-ai-proof-my-assignments/
Florida Gulf Coast University. (2024, July 2). GenAI proof your discussion forums. https://www.fgcu.edu/digitallearning/digital-learning-blog/2024-02-07-aiproofdiscussions
Macmillan Learning. (2024, April 4). Bits on bots: How to AI-proof any assignment. https://community.macmillanlearning.com/t5/bits-blog/bits-on-bots-how-to-ai-proof-any-assignment/ba-p/20031
Northern Illinois University Center for Innovative Teaching and Learning. (2024, February 28). Generative-AI-resistant assignments. https://citl.news.niu.edu/2024/02/28/generative-ai-resistant-assignments/
Northern Michigan University Center for Teaching and Learning. Creating AI-resistant assignments, activities, and assessments (designing out). https://nmu.edu/ctl/creating-ai-resistant-assignments-activities-and-assessments-designing-out
Teaching Channel. (2024, September 27). Outsmarting the bots: 5 strategies to create AI-resistant assignments. https://www.teachingchannel.com/k12-hub/blog/outsmarting-the-bots-5-strategies-to-create-ai-resistant-assignments/
University of Chicago. Strategies for designing AI-resistant assignments. https://genai.uchicago.edu/en/resources/faculty-and-instructors/strategies-for-designing-ai-resistant-assignments
University of Chicago. (2023, February 8). AI-resistant assignments? Show student thinking and promote better writing with UChicago-supported tools. https://academictech.uchicago.edu/2023/02/08/ai-resistant-assignments-show-student-thinking-and-promote-better-writing-with-uchicago-supported-tools/
University of Michigan–Flint. Assessments in an AI era: Discussions and strategy. https://www.umflint.edu/genai/assignments-in-the-ai-era/discussions-ai-redesign/
Washington University in St. Louis Center for Teaching and Learning. AI resistant assignments. https://ctl.wustl.edu/resources/ai-resistant-assignments/

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