Practical Supports for Human-Centered AI Integration in Teaching and Learning
Overview
This faculty toolkit is designed to support educators who want to integrate AI into their teaching in ways that remain clear, ethical, and centered on student learning. The goal is to move beyond vague AI policies and toward structured, assignment-level guidance that supports both faculty confidence and student accountability.
This work is grounded in a human-centered approach to AI in education. Students should remain active thinkers and decision-makers, and faculty should be able to communicate clearly when AI use is appropriate, when it is limited, and how reflection can deepen learning rather than reduce it.
Core Principles
Human-centered: Students remain the decision-makers in their learning.
Transparent: Expectations for AI use should be clear and visible.
Reflective: Students should think about how AI shaped their process.
Ethical: AI use should align with integrity, authorship, and responsible judgment.
Purposeful: AI should support learning goals rather than bypass them.
How to Choose an AI Use Level
A useful starting point is to ask what the assignment is meant to assess. If the goal is original reasoning, individual writing, or foundational skill development, lower AI levels may be more appropriate. If the goal is revision, feedback, collaboration, or critical evaluation of AI-generated content, higher levels may be appropriate.
Level 1: Use when independent performance must be assessed.
Level 2: Use when students need help generating ideas or structure.
Level 3: Use when feedback and revision are part of the learning goal.
Level 4: Use when students are expected to analyze, critique, and work with AI-generated material.
Sample Assignment Language
Level 1 Example
For this assignment, AI tools may not be used at any stage of the process. The purpose of this task is to assess your independent reasoning, writing, and understanding.
Level 2 Example
For this assignment, AI may be used for brainstorming, outlining, or organizing ideas. You may not use AI to generate full paragraphs or complete responses. Final work must reflect your own writing and judgment.
Level 3 Example
For this assignment, AI may be used to provide feedback on clarity, organization, or revision. You are responsible for evaluating that feedback and deciding what changes to make.
Level 4 Example
For this assignment, AI may be used as part of the creation process. You must critically evaluate AI contributions, revise them as needed, and explain how AI was used in your final submission.
Reflection Prompts Aligned to AI Use Levels
These prompts are designed to align directly with the four levels of AI use. Rather than asking only whether AI was used, these prompts guide students to evaluate how AI influenced their thinking, supported deeper understanding, or potentially limited their engagement with the task.
Level 1: No AI Use Allowed
Reflection at this level focuses on independent thinking and awareness of the learning process without AI support.
What parts of this assignment required the most effort or struggle, and why?
How did working without AI affect the way you approached the task?
What strategies did you use to develop your ideas independently?
Where do you think AI might have helped, and where might it have limited your thinking?
What did you gain from completing this work entirely on your own?
Level 2: AI for Brainstorming and Structure
Reflection at this level focuses on how AI influenced early-stage thinking without replacing the student’s own reasoning and writing.
How did AI shape your initial ideas or organization?
Did AI introduce perspectives you had not considered, or reinforce your existing thinking?
How did you decide what ideas to keep, modify, or discard?
Did using AI help you go deeper in your thinking, or did it make it easier to move quickly without fully engaging?
How would your approach have been different without AI?
Level 3: AI for Feedback and Revision
Reflection at this level focuses on how students interpret, evaluate, and act on AI-generated feedback.
What type of feedback did AI provide, and how useful was it?
What suggestions did you choose to accept, revise, or reject, and why?
Did AI feedback help you clarify your thinking or improve your argument?
Did AI make revision feel more efficient, and if so, did that affect how deeply you engaged with the feedback?
How did your role as the decision-maker shape the final version of your work?
Level 4: AI-Integrated Creation with Critical Evaluation
Reflection at this level focuses on co-creation with AI and the student’s role in evaluating, refining, and taking ownership of the final product.
How did you use AI as part of your creative or analytical process?
What parts of the work were most influenced by AI, and how did you adapt or revise those contributions?
Did AI help you think more deeply about the topic, or did it risk replacing parts of your reasoning?
How did you ensure that the final work reflects your own thinking and understanding?
What are the strengths and limitations of using AI for this type of task?
Across All Levels: Metacognitive Growth
These prompts can be used across assignments to build ongoing awareness of how AI shapes learning and thinking over time.
What did you learn about your own thinking process in this assignment?
When did AI support deeper thinking, and when might it have limited it?
How has your approach to using, or not using, AI changed?
What would you do differently in your next assignment to support deeper learning?
Reflection for Students Who Choose Not to Use AI
These prompts support students who choose not to use AI while still engaging in metacognitive reflection about their learning process and decision-making.
What influenced your decision not to use AI for this assignment?
How did working without AI shape your thinking, effort, or approach to the task?
At what points, if any, do you think AI might have supported your learning or made the process more efficient?
Do you think not using AI helped you engage more deeply with the material? Why or why not?
Were there moments of productive struggle, and how did you work through them?
How did your confidence in your work compare to assignments where you may have used AI?
What strategies did you rely on instead of AI to generate ideas, revise, or problem-solve?
Looking ahead, how might you decide when using or not using AI is most beneficial for your learning?
Choosing not to use AI is also a meaningful learning decision. The goal is to reflect on how that choice shaped your thinking, effort, and overall learning experience.
The goal is not to determine whether AI was used, but to understand how it shaped thinking, decision-making, and learning.
Implementation Tips
Use AI guidelines consistently across the course so expectations are clear.
Match AI levels to assignments for clarity and alignment with learning outcomes.
Explain why a specific AI use level is being applied to each assignment.
Support student choice and autonomy. If students choose not to use AI, they should still complete the metacognitive reflection, explain their decision, and follow the reflection prompts accordingly.
Ask students to reflect on how AI might have helped or hindered their work, even when they decide not to use it.
Make reflection a regular part of AI use so students see AI as part of the learning process, not a shortcut around it.
Review assignment wording carefully so AI expectations are specific, transparent, and easy for students to follow.
Ask students not only how AI helped, but whether it deepened their thinking, changed their confidence, or reduced productive struggle.
Use repeated reflection prompts across assignments so students can notice patterns in how AI shapes their learning, judgment, and agency over time.
Connection to HAIML
This toolkit is aligned with the Human-Centered AI Metacognitive Learning Model. Faculty can use HAIML to think beyond policy and toward deeper learning design by supporting experience, reflection, and ethical evaluation in AI-rich environments.
Faculty can use this toolkit when designing assignments, revising syllabi, facilitating discussions about AI, and creating reflection activities that support metacognitive growth. It is especially useful in courses where writing, reasoning, revision, and ethical judgment are central learning goals.
Over time, this approach helps students move from simply using AI to understanding how AI shapes their thinking and learning. That shift is essential for human-centered and ethically grounded education.