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Exploring how to implement AI effectively in your classrooms or programs?

I work with institutions to design practical, structured approaches to AI integration that support student learning and faculty adoption.

Artificial intelligence is rapidly becoming part of students’ everyday academic experience. Many are already using AI tools to complete assignments, study, and make sense of course material, often without clear guidance on how to use these tools effectively or responsibly.

At the same time, instructors are navigating a difficult balance: how to integrate AI in ways that support learning without undermining the thinking process that education is meant to develop.

This guide is grounded in a simple premise:

AI should be used to support thinking, not replace it.

In traditional classroom structures, certain assignments, such as discussion boards, are designed to promote interaction, reflection, and engagement. However, in practice, especially in access-oriented and community college settings, these activities do not always achieve their intended outcomes. Students often complete them under time constraints, participation may be uneven, and responses can become procedural rather than meaningful.

The introduction of AI has intensified these challenges. Without intentional design, it becomes easier for students to generate responses without engaging deeply with the material.

Rather than focusing on restricting AI use, this guide proposes a different approach: redesigning existing assignments to make thinking visible and required.

The method presented here replaces traditional discussion boards with AI-guided thinking logs. Students use AI as a structured support to work through ideas step by step, respond to questions, and reflect on their learning. They then submit their full interaction, allowing instructors to see not just what students produce, but how they think.

This approach is informed by principles from constructivist learning theory, where knowledge is developed through active engagement, questioning, and revision. It is also shaped by direct classroom experience with students balancing work, language development, and varying levels of academic preparation.

Importantly, this method:

• Requires no new tools
• Uses platforms students already access
• Can be implemented immediately
• Supports multilingual and diverse learners

The goal is not to replace the human aspects of teaching, but to extend them, to create more opportunities for guided thinking, feedback, and reflection in ways that are practical and sustainable.

What follows is a concise, ready-to-use framework that instructors can adopt and adapt in their own classrooms.

Discussion boards have long been used in higher education as a way to extend learning beyond the classroom. The intention is clear: to promote interaction, encourage reflection, and give students space to engage with course material and with each other.

In practice, however, the outcomes often look very different, especially in classrooms serving working students, multilingual learners, and those balancing multiple responsibilities. Participation tends to be uneven, with many students completing posts close to the deadline. This limits meaningful interaction and reduces opportunities for dialogue. What was designed as a space for engagement often becomes a task to complete.

From a learning perspective, this structure can fall short. Students benefit most when they are actively processing ideas, making connections, and revising their thinking. When discussion boards are completed quickly or without genuine interaction, the opportunity for that kind of thinking is reduced.

The integration of AI tools has added another layer to this challenge. Students now have access to tools that can generate responses instantly. Without intentional design, it becomes easier to produce a response without engaging in the underlying reasoning. This can further shift the focus from learning to completion.

This is not a failure of students. It reflects a mismatch between the design of the activity and the realities of how students engage, manage time, and use available tools.

In Practice

• Students often post at the last minute
• Replies are surface-level or repetitive
• Interaction is limited or nonexistent
• Participation depends on timing rather than engagement
• AI makes it easy to generate responses without thinking

Why This Matters

• Instructors have limited visibility into student understanding
• Misconceptions remain hidden
• Engagement becomes inconsistent
• Students miss opportunities to develop reasoning skills

Instructor Insight

In my own classes, I found that even when discussion prompts were thoughtfully designed, the structure itself limited meaningful engagement. The issue was not the topic or the students—it was the format.

If the goal of discussion boards is to promote engagement, reflection, and interaction, then the question is not whether those goals matter—but whether the current structure supports them.

In many classrooms, interaction depends on timing, participation, and student availability. When these conditions are not aligned, the result is often limited dialogue and reduced engagement. At the same time, students are already turning to AI tools as part of their learning process, whether guided or not.

This creates an opportunity to rethink the structure of the assignment.

Rather than asking students to simulate interaction through discussion posts, this approach shifts the focus toward guided thinking. Students engage with course material by working through ideas step by step, using AI as a support for questioning, clarification, and feedback.

From a learning perspective, this aligns with how students develop understanding: by actively engaging with concepts, attempting solutions, making mistakes, and refining their thinking. AI, when structured intentionally, can support this process by providing immediate, responsive interaction.

The key shift is this:

👉 The assignment moves from producing a response to engaging in a thinking process

Instead of asking students to post and reply, students:

• Work through a concept or problem using AI
• Respond to follow-up questions
• Attempt answers and revise their thinking
• Submit their full interaction
• Reflect on what they learned

This creates a form of interaction that is:

• Immediate rather than delayed
• Individualized rather than dependent on others
• Structured to support thinking rather than completion

Importantly, this does not remove the role of the instructor. Instead, it extends it. The instructor designs the structure, sets expectations, and reviews student thinking in a way that is more visible and actionable.

In Practice

Instead of asking students to:

• Post an initial response
• Reply to two classmates

Shift to:

• Think through a problem using AI
• Engage in a step-by-step interaction
• Submit the full conversation
• Reflect on their learning

What Changes

Traditional Model

• Focus on responses
• Peer timing dependent
• Surface-level replies
• Easy to complete passively

Shifted Model

• Focus on thinking
• Immediate interaction
• Guided reasoning
• Requires engagement

Why This Works

• Makes thinking visible
• Encourages persistence and effort
• Reduces passive AI use
• Supports students at different levels
• Provides instructors with insight into student understanding

Instructor Insight

In my own classes, this shift changed the nature of student work. Instead of submitting isolated responses, students began showing their process—where they were confused, how they approached a problem, and how their thinking evolved. This made it easier to support their learning in a more targeted way.

The goal of this method is to create a structure that promotes active thinking while remaining simple to implement. Rather than adding new tools or increasing workload, it reframes an existing assignment, such as a discussion board, into a guided learning process.

Students already have access to AI tools and are often using them independently. The challenge is not access, but structure. Without guidance, AI can be used to generate answers quickly. With the right structure, it can support questioning, reasoning, and reflection.

This method is designed to do exactly that.

It introduces a clear process where students engage with AI as a guide, respond to prompts, and make their thinking visible. The assignment shifts from a single submission to an interactive process that unfolds over multiple steps.

The design is intentionally minimal so it can be implemented immediately in any course, without requiring new platforms or additional training.

Step 1: Give Students a Structured Prompt

Students begin by using a prompt that sets expectations for how AI should respond. Starting with their name helps establish ownership and creates a more intentional interaction.

Prompt Template

My name is [Your Name].
I am learning about [topic].
Do not give me the answer right away.
Guide me step by step by asking questions so I can think through this.
If I make a mistake, explain why and help me fix it.
Here is my question or problem:
[Paste assignment, concept, or problem]

👉 This ensures that AI supports the thinking process rather than replacing it.

Step 2: Require Interaction, Not a Single Response

Students are expected to engage in a back-and-forth interaction. This is a critical part of the method.

Set clear expectations:

• Respond to follow-up questions
• Attempt answers, even if unsure
• Continue the interaction for multiple turns

The goal is not to get the answer quickly, but to work through the process.

Step 3: Submit the Full Interaction

Students submit (copy-paste):

• The complete AI conversation
• Not a summary
• Not just the final answer

This allows instructors to see:

• How students approached the problem
• Where they struggled
• How their thinking developed

👉 The interaction itself becomes the assignment.

Step 4: Add Reflection (Required)

Reflection helps students process their learning and makes their thinking explicit.

Reflection Template

• What did you understand better after this interaction?
• Where did you struggle?
• What question helped you the most?
• What would you still like help with?
• Highlight one moment where your thinking changed.

👉 This step reinforces learning and provides valuable insight for instructors.

Optional Step: Highlight Thinking Shifts

• A mistake they made
• A moment they changed their understanding
• A question that helped them move forward

In Practice

• Replace one discussion board assignment
• Provide the prompt
• Require full interaction + reflection
• Collect submissions

No additional tools or setup required.

Why This Works

• Students engage actively rather than passively
• Feedback is immediate and responsive
• Thinking is visible rather than hidden
• Reflection reinforces understanding

Instructor Insight

In my own classes, this structure changed how students approached assignments. Instead of looking for quick answers, many began engaging more directly with the material—asking questions, revising their thinking, and spending more time on the process. It also made it easier to identify where support was needed.

One of the most common barriers to adopting new teaching strategies is time. Even when an approach is effective, instructors need materials that are ready to use without additional development.

This section provides fully structured, copy-and-paste templates that can be placed directly into a learning management system (Canvas, Blackboard, etc.) or shared with students as assignment instructions.

The goal is to reduce implementation effort while maintaining clarity and consistency in how students engage with the activity.

Template 1: Assignment Instructions (Student-Facing)

You can paste this directly into your LMS:

Assignment: AI-Guided Thinking Log

For this assignment, you will use an AI tool (such as ChatGPT or another available tool) to work through a concept or problem step by step.

Your goal is not to get the answer quickly, but to engage in the thinking process.

Instructions:

1. Copy and paste the prompt provided below into your AI tool.
2. Replace [Your Name] and [topic] with your information.
3. Paste your question, problem, or assignment where indicated.
4. Engage in a back-and-forth interaction with the AI:
   • Respond to its questions
   • Attempt answers, even if unsure
   • Continue the interaction for multiple steps
5. Copy and submit your full interaction (not a summary).
6. Complete the reflection questions at the end.

Your submission should include:

• The full AI interaction
• Your reflection responses

This assignment is graded based on your engagement and thinking process, not just the final answer.

Template 2: Student Prompt

My name is [Your Name].
I am learning about [topic].
Do not give me the answer right away.
Guide me step by step by asking questions so I can think through this.
If I make a mistake, explain why and help me fix it.
Here is my question or problem:
[Paste assignment, concept, or problem]

Template 3: Reflection Questions

Reflection

1. What did you understand better after this interaction?
2. Where did you struggle?
3. What question helped you the most?
4. What would you still like help with?
5. Highlight one moment where your thinking changed.

Template 4: Simple Grading Rubric

Grading Criteria

• Engagement with AI (multiple steps, not one response): ✔ / ✘
• Evidence of effort and thinking: ✔ / ✘
• Reflection completed: ✔ / ✘

Focus is on process, not perfection.

Optional Template: Academic Integrity Statement

AI Use Expectations

You are expected to use AI as a tool to support your thinking, not to complete the assignment for you.

Submitting responses generated without engaging in the process does not meet the expectations of this assignment.

Your grade is based on your interaction, effort, and reflection.

In Practice

• Copy Template 1 into your LMS
• Provide Template 2 as the required prompt
• Include Templates 3 and 4 in the assignment
• Optional: add Template 5 for clarity

Instructor Insight

Providing clear templates significantly increases the quality of student engagement. When expectations are explicit, students are more likely to follow the intended process and use AI in a way that supports learning rather than bypassing it.

Discussion boards are widely used because they are intended to promote interaction, reflection, and engagement. These are important goals, and the use of discussion-based activities reflects a strong commitment to student-centered learning.

However, in practice, the effectiveness of discussion boards often depends on factors that are difficult to control, such as timing, participation levels, and student availability. When students complete posts at different times or close to deadlines, meaningful interaction becomes limited. What was designed as dialogue can become a series of isolated responses.

From a learning perspective, this creates a challenge. When engagement is inconsistent, instructors have limited visibility into how students are thinking, what they understand, and where they may need support.

The AI-guided thinking log does not eliminate interaction, it redefines it.

Instead of relying on peer-to-peer timing, students engage in a structured, guided interaction that is immediate, responsive, and focused on their own thinking process. This creates a more consistent learning experience across students, regardless of when they complete the assignment.

This shift is particularly valuable in classrooms where students have varying schedules, responsibilities, and levels of preparation. It ensures that all students engage in a meaningful process, rather than depending on conditions that may not align.

Side-by-Side Comparison

What Changes for Students

• Less pressure to “perform” for peers
• More space to work through confusion
• Immediate feedback and guidance
• Greater focus on understanding rather than completion

What Changes for Instructors

• Clearer visibility into student thinking
• Easier identification of misconceptions
• More meaningful submissions to review
• Less need to manage or prompt discussion participation

Why This Matters

When assignments are structured around interaction that may or may not happen, learning can become inconsistent. By shifting to a model that guarantees engagement through guided interaction, instructors can create more reliable opportunities for students to think, practice, and reflect.

This does not replace the value of human interaction in the classroom. Instead, it ensures that each student engages in the learning process, making in-class discussions and instructor feedback more informed and effective.

Instructor Insight

In my own classes, this shift reduced the variability I often saw with discussion boards. Instead of some students engaging deeply and others minimally, most students participated more consistently. The work they submitted provided clearer insight into their understanding, which made follow-up instruction more targeted and effective.

When this approach is implemented consistently, the most noticeable changes are not necessarily in final answers, but in how students engage with the learning process.

Because the assignment requires interaction and reflection, students spend more time working through ideas rather than completing a single task. The structure encourages them to attempt answers, respond to questions, and revisit their thinking. This creates a shift from completion-focused behavior to process-focused engagement.

From a learning perspective, this matters. Students develop understanding not only by arriving at correct answers, but by working through confusion, testing ideas, and refining their reasoning. This method creates space for that process to occur more consistently.

It also provides instructors with a clearer window into student thinking. Instead of seeing only final responses, instructors can observe how students approached a problem, where they struggled, and how their understanding developed over time.

In Practice, You May Notice

• Students spending more time engaging with the material
• More attempts, even when students are unsure
• Stronger and more specific questions
• Greater willingness to work through confusion
• More consistent participation across students

Changes in Student Work

• Responses reflect process, not just outcomes
• Misconceptions become visible
• Students show evidence of revision and adjustment
• Reflection becomes more meaningful and specific

Changes in AI Use

• Less direct copying of generated responses
• More interaction with AI as a guide
• Increased use of follow-up questions
• More intentional and structured use of AI

Changes in Instruction

• Easier to identify where students need support
• More targeted feedback opportunities
• Better alignment between assignment and learning goals
• Reduced need to prompt or manage participation

Why These Changes Occur

These shifts are not the result of the tool itself, but of the structure around it. When students are required to engage in a process—responding, attempting, reflecting—they are more likely to participate actively.

AI provides immediate feedback, but it is the assignment design that determines whether students use it passively or as a learning support.

By making thinking visible and required, this method encourages behaviors that support deeper learning.

Instructor Insight

In my own classes, one of the most noticeable changes was the quality of student questions. Instead of asking general or surface-level questions, students began asking more specific and focused questions based on where they were in their thinking. This made it easier to support them and address misunderstandings early.

As AI becomes more integrated into students’ academic work, questions about academic integrity and appropriate use are becoming more common. In many cases, the concern is that students will rely on AI to complete assignments without engaging in the learning process.

These concerns are valid. However, in practice, restricting access to AI tools is often difficult and can shift focus away from learning.

This approach takes a different perspective:

👉 Instead of focusing primarily on limiting AI use, it focuses on structuring assignments so that meaningful engagement is required.

From a learning standpoint, students are more likely to use AI productively when expectations are clear and the assignment design emphasizes process over output. When students are asked to show how they think, rather than just what they produce, it becomes more difficult to rely on AI passively.

The goal is not to eliminate AI use, but to guide it in a way that supports learning.

What Counts as Productive Use

In this model, appropriate use of AI includes:

• Asking questions to better understand a concept
• Responding to follow-up prompts
• Attempting answers before receiving full explanations
• Using feedback to revise thinking
• Reflecting on the learning process

What Does Not Meet Expectations

AI use does not meet expectations when:

• A response is generated and submitted without interaction
• The student does not attempt to engage with the process
• There is no evidence of thinking, revision, or reflection
• The submission reflects only output, not engagement

How the Structure Supports Integrity

This method naturally reduces misuse by requiring:

• Multiple steps of interaction
• Student responses throughout the process
• A complete conversation, not a final answer
• Reflection on learning

Because the assignment is based on process, not just correctness, it becomes more difficult to complete without engaging.

Setting Clear Expectations

Providing clear guidance to students helps establish consistent use.

You may include a statement such as:

You are expected to use AI as a tool to support your thinking, not to complete the assignment for you.

Your grade is based on your engagement, effort, and reflection—not just the final answer.

Submissions that show little or no interaction with the process do not meet the expectations of this assignment.

Why This Approach Works

When expectations are explicit and the structure requires engagement:

• Students are more likely to use AI as intended
• Misuse becomes easier to identify
• The focus remains on learning rather than enforcement

This approach shifts the conversation from “What tools are students using?” to “How are students engaging with their learning?”

Instructor Insight

In my own classes, I found that when the assignment required students to submit their full interaction and reflection, concerns about misuse decreased. Students were more likely to engage with the process because that was what was being evaluated.

One of the strengths of this approach is that it does not require a full course redesign. It can be implemented by making a small, targeted change to an existing assignment.

In many cases, instructors are already using discussion boards or written responses to encourage engagement. This method simply reframes that structure to focus on guided thinking and reflection.

The goal is to make it easy to try, without additional tools, training, or preparation.

Step-by-Step: Implement in One Class

Step 1: Choose One Assignment

• Select a discussion board or short written assignment you already use.

Step 2: Replace the Instructions

• Remove “post and reply” requirements.
• Insert the AI-Guided Thinking Log instructions and prompt from this guide.

Step 3: Set Clear Expectations

Let students know:

• They must engage in multiple steps
• They must submit the full interaction
• They must complete the reflection

Step 4: Collect Submissions

Students submit:

• Full AI interaction
• Reflection responses

Step 5: Review for Process, Not Perfection

Focus on:

• Evidence of engagement
• Attempts and revisions
• Quality of reflection

What You Do Not Need

• No new software
• No additional subscriptions
• No complex setup
• No redesign of your entire course

Suggested First Use

If you are trying this for the first time, consider:

• A low-stakes assignment
• A concept students typically find challenging
• A week where discussion boards are usually less effective

This allows you to observe how students engage without adding pressure.

After the First Assignment

Take a few minutes to reflect:

• Did students engage with the process?
• What did you learn about their thinking?
• Where did they struggle?
• How might you adjust instructions next time?

This helps refine the approach for future use.

Optional: Introduce It to Students

You may want to briefly explain the purpose:

This assignment is designed to help you think through problems step by step, not just arrive at an answer. The goal is to make your thinking visible so I can better support your learning.

Instructor Insight

In my own classes, starting with one assignment made the transition manageable. It provided a clear example of how the structure works and helped set expectations for future work. Over time, this approach can be expanded to other assignments as needed.

You do not need to change everything at once.

A single shift in how one assignment is structured can:

• Increase engagement
• Make thinking visible
• Improve learning outcomes

The integration of AI into education is no longer a future consideration—it is part of the current learning environment. Students are already using these tools in a variety of ways, often without clear guidance on how to do so effectively.

This creates both a challenge and an opportunity.

The challenge is ensuring that AI does not replace the thinking process that learning depends on. The opportunity is to design assignments that use AI to support that process in meaningful ways.

The approach presented in this guide is intentionally simple. It does not require new tools, additional costs, or a full redesign of a course. Instead, it focuses on a single shift: moving from assignments that emphasize completion to those that make thinking visible.

By replacing traditional discussion boards with AI-guided thinking logs, instructors can create more consistent opportunities for engagement, reflection, and learning.

This approach is grounded in real classroom experience with students who are balancing multiple responsibilities, developing language skills, and navigating different levels of academic preparation. It is designed to work within those realities.

At its core, this method is not about AI.

It is about:

• Supporting how students learn
• Making thinking visible
• Creating structures that encourage engagement
• Extending, not replacing, the role of the instructor

Even small changes in assignment design can have a meaningful impact. Starting with one assignment is enough to begin.

The goal is not to change everything at once, but to make one change that makes learning more visible, more engaging, and more effective.

Questions? Email yrondon@ownablelearning.com

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