While AI has come on strong in higher education, there are many situations in which it’s important for students to do the cognitive work themselves, think critically, analyze deeply and develop their own voices. Yet getting students to work without AI can be a challenge.
Several strategies can nudge students toward relying on their own reasoning and reflection, including setting clear expectations, designing AI-resistant assignments and creating authentic opportunities for original thinking.
Clear Policies
Setting and communicating clear policies can establish boundaries around acceptable AI use. This in turn helps make expectations clear, reduces confusion and prevents unintentional misuse.
Syllabus statements
Consider the approved University of Alabama syllabus statements regarding AI use. Be sure to discuss your AI policy on the first day of class or provide a short video explanation in your online courses. Having a strong syllabus statement provides students with broad guidance for their AI use throughout the class.
Statements for each assignment
Include a brief statement about appropriate AI use with each assignment. Express why AI is not beneficial for helping students reach the desired learning outcomes in this situation. This approach provides students with a reminder of the general course policy or signals potential variation in appropriate use across different assignments.
Class honor code
Work with students to develop a class honor code for AI usage. The goal is for students to think through situations where AI usage might or might not be appropriate and to consider the rationale for their assessments. This approach can improve student adherence to the rules and reduce anxiety about when they can or should use AI.
Direct Appeals to Students
Appealing to students in ways that align and resonate with their values can improve buy-in and increase intrinsic motivation. These direct connections help students understand why AI limits matter and decrease the likelihood they will use AI to shortcut the learning process.
Skill development appeal
Explain how overreliance on AI can inhibit the development of critical thinking skills they will need to be successful in future coursework and that employers value in the workforce. Sharing research demonstrating that employees with strong critical thinking skills thrive in decision-making, problem-solving and adapting to change may discourage students from using AI. This approach reminds students that avoiding shortcuts allows them to build the skills necessary for their future careers.
Academic honesty appeal
Remind students that academic integrity is a foundational expectation of the University community and is clearly outlined in the Student Code of Conduct. Encourage them to take pride in producing original work that reflects their own thinking, effort and understanding. Emphasize that honesty in coursework builds trust between students and instructors and strengthens the value of their education. This appeal reinforces the idea that integrity and originality are essential to authentic learning and personal growth.
Environmental appeal
Discuss the environmental impacts of AI with students. These discussions might center around the amount of energy derived from fossil fuels used to power AI models and how that contributes to climate change, or how data center cooling and electricity generation consume large amounts of freshwater, which can hamper local water supplies. This appeal helps students connect their choices to broader sustainability values.
Copyright appeal
Discuss ownership with students. Raise the legal questions around whether AI-generated work is considered “original” and protected by copyright laws. It’s not legally settled whether the creator, the AI developer or anyone can claim copyright over AI-generated material. In short, students may not own the material they create with AI, so underscore the importance of originality. By understanding how AI outputs are generated, students may gain greater appreciation for originality and authorship as key dimensions of academic and creative responsibility.
Adding Friction to AI Use
Structuring assignments so they are interactive or not fully text-based can make it more difficult for students to use AI.
Use videos for assignment instructions
Deliver instructions through a medium that cannot easily be copied and pasted into AI tools. This tactic creates additional steps for students who want to offload tasks to AI.
Require annotated drafts or annotated PDFs
Ask students to document their revisions and thought processes or reasoning. This approach forces students to “show their work,” making their thought processes transparent and harder to fake with AI assistance.
Require voice logs
Ask students to explain their processes step-by-step in a video or audio recording. Similar to annotated drafts, voice logs require students to verbalize their choices and reasoning, which encourages authentic engagement.
Require source transparency
Ask students to document and justify their research process, including how they located and evaluated sources. This strategy allows students to explain their research choices and discourages hidden reliance on AI-sourced material.
Integrate unpredictable prompts
Use dynamic prompts that reference recent events, class discussions or evolving course material to make AI-prewritten responses less relevant. This approach keeps assignments timely and context-dependent, reducing AI’s effectiveness.
In-Class and Do-Now Assignments
Incorporating in-the-moment activities can require students’ immediate, personal engagement and thus limit the opportunity for AI use. These assignments encourage students to think independently, participate actively and demonstrate their learning in real time.
Writing Assignments
- Quick Write: A brief learning assessment technique where learners respond to an open-ended prompt.
- Letters: Students assume the identity of an important figure in your discipline and write a letter explaining their thoughts on an issue, theory, or controversy to another figure with a different perspective.
In-class writing assignments require students to think and produce content spontaneously in a time-bound setting while limiting the opportunity to use AI tools.
AV Assignments
Digital Stories: Students use computer-based tools such as video, audio, graphics and web publishing to tell personal or academic stories related to course themes.
Giving students specific tools and parameters to complete in-class digital assignments significantly reduces their potential to use AI negatively.
Peer Discussion Assignments
- Jigsaw: Students work in small groups to develop knowledge about a topic before teaching what they have learned to another group.
- Role Plays: Students act out or assume identities or roles they would not normally take to explore course concepts.
Peer discussion assignments focus on collaboration and discussion with limited need for AI assistance.
Quizzes and Exams
- Oral Exams: Use brief, structured oral assessments to gauge understanding and reasoning.
- Blue Book Exams: Use timed, handwritten responses to assess understanding of key questions or concepts.
- In-Class Presentations: Have students present key takeaways, case studies or discussion summaries.
In-class assessments require students to produce or present original work with minimal opportunity for inappropriate AI use.
See the Cross Academy for additional ideas for active learning activities.
Checking Process
Building in steps that document students’ processes discourages AI use by emphasizing accountability and providing visible evidence of original effort.
Multiple drafts
Ask students to document their work in drafts. For example, the Process Feedback extension, free through the Google Chrome store, allows instructors to track the edit history of a document created in Google Docs. This approach provides a verifiable record of student progress and authenticity.
Peer review
Ask students to comment on each other’s drafts in class or online. When students submit their final papers, have them provide a cover letter explaining how they responded to peer comments. This approach emphasizes transparency and creates multiple checkpoints to identify inappropriate AI use.
Process portfolios
Ask students to document and explain their writing process for each assignment. Examples may include multiple drafts, reflective cover letters, process notes or revision memos. These assignments help students think critically about how they approach their work. This strategy builds metacognitive awareness and makes AI-produced work easier to detect.