Practical Supports for Human-Centered AI Integration in Teaching and Learning
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.
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.
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.
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.
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.
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.
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.
Reflection at this level focuses on independent thinking and awareness of the learning process without AI support.
Reflection at this level focuses on how AI influenced early-stage thinking without replacing the student’s own reasoning and writing.
Reflection at this level focuses on how students interpret, evaluate, and act on AI-generated feedback.
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.
These prompts can be used across assignments to build ongoing awareness of how AI shapes learning and thinking over time.
The goal is not to determine whether AI was used, but to understand how it shaped thinking, decision-making, and learning.
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.