As AI tools become part of everyday life, educators are facing a growing challenge that goes beyond simple detection or prohibition. Beyond asking whether students are using AI, it may be more realistic to ask how they are using it and whether that use supports or undermines learning.
In many schools and universities, conversations about AI are often divided. Some educators embrace AI tools enthusiastically, while others respond with concern about academic integrity, overreliance, and the loss of authentic student thinking. In reality, most educators are somewhere in between.
What Students and Faculty Need Most Right Now is Clarity on Effective Uses of AI to Support Student Learning
During our School of Education meetings and related faculty work sessions at Concordia Irvine over the past year, we explored a framework for thinking about AI use through the lens of student learning rather than focusing solely on compliance or punishment. Our goal was not to create a rigid policy, but to help preserve higher-order thinking by clarifying expectations for the appropriate and inappropriate use of AI for specific assignments.
The first step in clarifying AI expectations was to develop a shared understanding of various levels of AI use. Several discussions centered around these three categories of AI use: augmentation, substitution, and abdication (Newmeyer, 2025).
These categories are not meant to function as a hierarchy, but rather as a spectrum. Depending on the context and learning goals, there may be appropriate uses for each category. However, when viewed through the scope of student learning, the central question remains: Are students demonstrating their own thinking and engaging in “meaningful,” intellectual work?
To foster discussion and reflection among faculty and students, we practiced classifying different educational uses of AI into the following categories. What has made our discussions interesting is that not everyone always agreed on the categorizations, which led to rich dialogue and ultimately moved us closer toward a shared understanding of effective AI use.
Three Categories of AI Use
Augmentation occurs when AI enhances learning without replacing intellectual effort. In this category, AI acts more like a coach or assistant, helping students brainstorm ideas, refine writing, organize thoughts, and receive feedback. Students still perform the essential cognitive work: analyzing, synthesizing, reflecting, and making decisions. Learning is preserved because the student remains the primary thinker.
Substitution is when AI may be used to replace tasks that students could reasonably complete themselves, often for efficiency or convenience. For example, AI tools may be useful in providing summaries, formatted discussion posts, or partially completed assignments. On the other hand, while the use of AI may save time, it can also reduce opportunities for skill development if overused. The learning risk increases because students may begin outsourcing important parts of the thinking process. Ultimately, awareness of this risk allows educators and students to make more intentional decisions about when AI can appropriately support learning while still preserving critical thinking, reflection, and authentic engagement.
Abdication is when students surrender responsibility for the learning task entirely and rely on AI to generate the final product. The student is no longer engaged in meaningful intellectual work. At that point, the issue is not simply technology use; it becomes a question of authenticity, integrity, and whether learning is occurring at all. On the other hand, one effective example of abdication is having AI generate an essay and then having students evaluate, revise, and improve the output in alignment with the rubric. In this case, the thinking may come on the back end as students analyze, critique, and apply judgment to the AI outputs.
Beyond School AI Policies, Expectations Need to Be Outlined for Specific Assignments or Types of Assignments
One of the challenges many instructors face is that students often do not actually know what level of AI use is acceptable. It is becoming apparent that, in addition to an AI policy for the institution and/or the course, students need more clarity on specific assignments. In the absence of clear expectations, students fill in the gaps themselves, assuming that AI is prohibited or is acceptable as long as the criteria are met. Neither assumption serves learning well.
To address this issue, we developed an AI Expectations Template designed to help instructors clarify assignment expectations in light of AI use. The template includes an opportunity for faculty to clarify the use of AI on assignments by reflecting on the following:
- AI-supported tasks: What will you allow or encourage students to use AI for?
- Human critical tasks: What higher-order work will you require students to perform without the use of AI?
The framework also encourages instructors to reflect on ethical and transparency requirements in considering the following questions:
- Using Servant Leadership virtues (humility, compassion, honesty, and courage), how will you teach ethical AI engagement for this assignment?
- How will students disclose AI use?
Servant Leadership Virtues
At Concordia University Irvine in the School of Education, our Servant Leadership framework offers an ethical foundation and a shared set of virtues to guide our community through complex decisions, in this case, how to use AI in ways that preserve student thinking, authenticity, and voice. During faculty sessions, we reflected on the ethical engagement of AI with the virtues of courage, compassion, humility, and honesty.
Through our discussions, we see that ethical AI use calls for humility in recognizing AI as a tool that can support learning and spark critical thinking without replacing human effort and judgment, compassion in using AI in ways that serve and support others within the learning community, honesty through transparent acknowledgment of AI’s role in one’s work, and courage to engage in thoughtful conversations about responsible AI use while making decisions that preserve authentic student learning and voice.
AI Use Disclosure Statement
Several instructors have also begun requiring students to submit an AI Use Disclosure Statement with assignments. Rather than creating a culture of suspicion, disclosure statements promote transparency and reflection. Students briefly explain whether and how they used AI tools, what tasks the tools supported, and how they ensured the final work reflected their own thinking and voice.
AI Use Statement Prompt: In 3–5 sentences, describe if and how you used AI tools to support your work on this assignment. Be specific about the tasks (e.g., brainstorming, drafting, grammar checks) and which tools were used. Reflect briefly on how you ensured that your final product reflects your own thinking and voice.
This approach helps students develop responsible judgment and critical reflection on their use of AI tools. Additionally, the AI Use Statements have provided valuable insight into how students use AI and have helped instructors clarify AI expectations, if needed.
The clarification of AI expectations is not ultimately about technology, but instead, focuses on student learning. We want to create learning environments that offer opportunities for reflection, analysis, discussion, creativity, and problem-solving. When it appears that a student may have been overly reliant on AI, we take the opportunity to return to our learning goals for the assignment and focus on the value of their growth, perspective, and voice, reminding them that they are a crafted masterpiece, uniquely designed in Christ Jesus for a purposeful life, and our commitment to support them along their educational journey.
For we are God’s handiwork, created in Christ Jesus to do good works, which God prepared in advance for us to do. Ephesians 2:10
Newmeyer, M. (2025, August). Using AI with HEART. Research and Assessment Day (RAD). Concordia University Irvine, Irvine, CA.
Newmeyer, M. (2026, March). Keeping the HEART in counseling: Faithful presence and ethical AI integration. Christian Association for Psychological Studies Annual Conference, Columbus, OH.
Tarbutton, T., Doyle, L., & Stuewe, Y. (2026). Grounded in human-centered values and servant leadership virtues: A conceptual framework for assignment redesign in the age of AI. [Conference presentation]. Baylor Symposium on Faith and Culture, Technology and the Human Person in the Age of AI, Waco, TX, United States.
Yvette Stuewe
Assistant Professor of Education
Dr. Yvette Stuewe, Ed.D., is an Assistant Professor in the MAED and Teacher Credential programs at Concordia University Irvine with 30 years of experience in Lutheran education. Her career has included teaching and leadership roles at St. John’s Lutheran School in Orange, Orange Lutheran High School, and Concordia University Irvine, where she has served as a teacher, curriculum leader, induction mentor, conference presenter, and online learning administrator. A National Board Certified Teacher, Professor Stuewe is passionate about reflective teaching practices, meaningful collaboration, and the thoughtful integration of technology in education. She has extensive experience with one-to-one learning environments and digital tools. She earned a doctorate in Instructional Technology and Distance Education at Nova Southeastern University.
Rejoice always, pray continually, give thanks in all circumstances; for this is God’s will for you in Christ Jesus. 1 Thessalonians 5:16-18