Design Through
Teaching in the Age of AI
Integrity Through Design is grounded in the idea that academic integrity is not just upheld, it’s actively cultivated through thoughtful course design .
Pedagogical Strategies:
Design for Learning, Not Just for Assessment
These strategies emphasize designing authentic, meaningful, and sca olded experiences that are harder to outsource and more aligned with human cognitive and emotional engagement, even in an AI-enabled world. Authentic assessments model the ethical and civic responsibilities we hope students will carry beyond the classroom—an approach aligned with the values of Principled Innovation.
Use a variety of low- and high-stakes assessments to monitor learning throughout the term.
Replace or supplement objective tests with projects, reflections, debates, presentations, or other performance-based assessments.
Assign prompts that incorporate students' lived experiences, goals, or current events to reduce the usefulness of generic AI-generated responses.
Include process-based writing assignments that require drafts, peer review, and annotated feedback loops.
Invite students to explain their use of AI tools in completing an assignment (e.g., what was used, what was changed, and why).
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Design assignments that require citation of both AI-generated content and human-authored sources, using transparent frameworks like ASU's Generative AI Disclosure Guidelines.
Ask students to compare AI-generated responses with their own reasoning, highlighting strengths and weaknesses in each.
Use portfolios, journals, or ongoing, evolving projects to build a unique body of student work over time.
Incorporate brief oral check-ins or video reflections on major assignments to promote authentic understanding and reinforce student ownership of their work.
Provide clear rubrics with criteria that reward originality, process, and reflection.
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Design incremental summative assignments that build in complexity across the term.
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O er a variety of assessment formats—such as recorded interviews, concept maps, or sca olded planning documents—especially when academic integrity concerns arise. These approaches shift focus from final products to the learning process itself, reducing the appeal and feasibility of AI-generated shortcuts.
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Use open-resource, open-AI exams when appropriate to model real-world problem-solving with available tools.
Technology Strategies:
Smart Systems for Smart Integrity
Technology should reinforce academic integrity by supporting clear expectations, ethical engagement, and inclusive assessment design. When thoughtfully applied, digital tools can make academic expectations more transparent, streamline communication, and reduce opportunities and temptations for dishonesty. Leveraging learning technologies with intention helps create equitable environments where integrity is built into the design.
Use LMS-based tools to randomize questions, set time limits, and manage access (e.g., Canvas settings).
Encourage students to use AI ethically—provide examples of acceptable vs. unacceptable use with assignments.
Academic Integrity Pledge
Incorporate version control tools (e.g., Google Docs version history or GitHub) to track progress over time.
Limit feedback shown after assessments to reduce content sharing.
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Ask students to sign an academic integrity pledge with AI-specific clauses.
Use browser lockdowns and proctoring tools when necessary, but clearly explain their purpose to students—framing them around fairness and shared responsibility—and align them with thoughtful assessment design.
Ensure that tech-based security measures (e.g., browser lockdowns, proctoring tools, or timed exams) are inclusive and accessible. Account for students with disabilities, varied learning needs, and unstable internet access by o ering equitable alternatives or flexibility where appropriate.
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Use analytics (e.g., time on page, participation) to identify opportunities for timely feedback, re-engagement, or additional support.
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Create AI literacy checkpoints or quizzes to help students understand ethical use, bias, and limitations.
Community & Culture Strategies:
Build Trust, Build Integrity
Students are more likely to uphold standards when they feel supported, respected, and included in a community of learning. Integrity flourishes in environments where students are treated as partners in the learning process and are encouraged to bring their authentic selves. Creating space for connection, purpose, and voice within the learning experience can increase student motivation, trust, and accountability.
Proactively discuss AI tool usage and limits in your syllabus, and revisit the conversation regularly.
Have students reflect on their own learning goals and how integrity supports them. 30 31 32 33
Celebrate original thinking and e ort—use badges, praise, or reflective spotlights.
Co-create AI use guidelines with students to foster shared responsibility and ethical learning.
Model your own AI use as an instructor and share how you decide what is ethical and helpful.
Discuss implications of AI use, explore expectations, and ethical considerations of AI use in professional and academic settings.
Provide grace and flexibility where possible—rigidity often leads to desperation and dishonesty.
Foster a climate of curiosity rather than suspicion—assume students want to learn.
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Foster shared understanding through cultural awareness, ethical exploration, and peer modeling—use structured scenarios to navigate gray areas in AI use, acknowledge di ering norms, and empower TAs or peer mentors to reinforce academic integrity.
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Normalize help-seeking behaviors by connecting students with writing centers, libraries, and tech support.
Clarify where collaboration is encouraged and where it is not appropriate, especially with AI collaboration.
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Build regular touchpoints for human interaction (forums, video check-ins, group work).
+ AI-Aware Course Design Traditional Strategy
Traditional Strategy (Pre-AI Focus) AI-Aware Course Design (Modern Considerations)
Require citations for writing assignments
Randomize test questions and answers
Assign discussion posts based on textbook prompts
Require drafts of papers
State academic integrity policy in syllabus
Administer proctored or lockdown browser exams
Assign group projects to build accountability
Clarify where collaboration is and isn’t allowed
Use cumulative assignments
Give feedback after grading
Require AI + source citations and ask students to explain how/why they used AI tools
Design open-resource or open-AI exams that emphasize application and reasoning over recall
Use discussion prompts that require critique of AI responses or exploration of ethical dilemmas with AI
Require version history (e.g., Google Docs) or reflection on drafting process, including AI tool use
Include a Generative AI Use Policy with examples of acceptable and unacceptable uses
Combine limited proctoring with oral follow-ups, process videos, or reflection assignments
Assign group work that includes peer evaluation of AI use and contributions
Specify how students may collaborate with AI tools (e.g., brainstorming, outlining, revising)
Use iterative, real-world scenarios that are sca olded weekly and reduce generic solution viability from AI
Provide feedforward before due dates, encouraging revision and self-checking (AI-assisted or not)
Define cheating in early modules
Host an ongoing dialogue about academic integrity in an AI world, evolving with student use patterns
Fostering academic integrity
in the age of AI calls on us to practice Principled Innovation; to design, teach, and respond in ways that are inclusive, reflective, and grounded in ethical decision-making. In this evolving landscape, both educators and students are learning how to navigate responsible AI use. When concerns arise, especially early on, treat them as teachable moments—opportunities to clarify expectations, promote reflection, and strengthen a shared commitment to integrity.
What strategies will you try out?
Sources
As higher education continues to evolve in the age of digital learning and generative artificial intelligence, the challenge of fostering academic integrity has become both more complex and more urgent. AI-assisted tools and conversational technologies now shape the teaching and learning landscape in profound ways, demanding new approaches to fairness, accountability, and trust.
This resource synthesizes insights from contemporary scholarship on learning and generative AI, drawing on the following research:
• Holden, O. L., Norris, M. E., & Kuhlmeier, V. A. (2021). Academic Integrity in Online Assessment: A Research Review. Frontiers in Education, 6:639814.
• Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239.
• Joyner, D. (2024). A Teacher's Guide to Conversational AI: Enhancing Assessment, Instruction, and Curriculum with Chatbots. Taylor & Francis.
• Mollick, E. (2024). Co-intelligence: Living and Working with AI. Portfolio/Penguin.
• Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: A threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21, 2.
This work was further enriched by collaboration with the EdPlus Digital Learning team and leadership from the O ce of the Provost at Arizona State University, reflecting a shared commitment to fostering academic integrity across digital learning environments.