Thought Partnering with AI: Working Smarter Means More Than Just Saving Time

Outline

CONTENT AND ENGAGEMENT

This 90-minute, hands-on session positions AI as a thought partner in lesson design rather than a shortcut. Participants will explore AI efficacy by reflecting on their own understanding and motivations for AI use in education, analyzing examples of AI use for effectiveness, distinguishing AI overreliance from AI fluency, and examining how cognitive offloading impacts decision-making. Using ChatGPT or Gemini, attendees will collaboratively design or refine a standards-aligned lesson component through an iterative Prompt → Review → Revise process. Educators will engage in peer-to-peer, small-group, and whole-group discussions, feedback exchanges, and live modeling that connect AI directly to authentic, student-centered lesson design. Each participant will leave with a new or refined lesson plan, a step-by-step record of their design process, and a replicable framework for effective and intentional AI integration in instructional planning. The session concludes with participants revisiting their initial perspectives on AI use in light of the insights gained.

Every element of the session is intentionally designed to model high-impact professional learning strategies that teachers can apply in their classrooms and instructional leaders can implement with their teams.

TIME

Welcome, Reflection, Objective (10 minutes):
Participants will reflect and craft a written response to the question: “How can I tell whether I am using AI effectively in my role as an educator?” Participants will then engage an X/Y AI mindset activity and discuss with a peer.
x% + y% = 100%
x = reduce workload
y = strengthen my output
x / y
After sharing out in a whole group discussion, the facilitator will introduce the session goals:
• Evaluate the role of Artificial Intelligence in our work as professional educators
• Examine research on AI dependence
• Develop an iterative approach to thought partnering with AI

Exploring Effective AI Use (15 minutes):
Participants will compare student created writing with student writing generated by AI and engage in peer-to-peer discussion, before sharing out to the whole group. Participants will then compare lesson plan feedback from an administrator with lesson plan feedback from an administrator generated by AI and engage in peer-to-peer discussion, before sharing out to the whole group. Afterwards, participants will reflect on their own AI use through the lens of actor-observer bias. In other words, do you scrutinize your use of AI the same way you scrutinize student and administrator use of AI?

AI Fluency Versus AI Dependence (15 minutes):
In small groups, participants will explore an excerpt from a Substack by Nigel P. Daly, “Educating for AI fluency: Managing cognitive bleed and AI dependency.” Afterwards, using small group interactive learning structures, participants will examine the following questions:
• What is cognitive offloading?
• What is the “use it or lose it” principle?
• What are the negative consequences of AI dependency?
As a whole group, the facilitator will guide a brief discussion on (1) the implications of cognitive offloading on instructional practice and (2) the implications of AI fluency versus Overreliance on AI for educators and students.
Note: This collective understanding and mindset work will establish the buy in for the rest of the session as we move towards adopting an iterative approach to AI as a thought partner and not just a shortcut.

Live Modeling—Prompting with Purpose Part 1 (15 minutes):
Participants will use ChatGPT or Gemini with facilitator guided prompts to (1) demonstrate how prompts affect AI output and (2) establish a need for iteration and revision in AI generated instructional materials. Specifically, participants will generate a parent letter using a generic prompt. Participants will then be given a more detailed prompt and compare outputs with a peer before a whole group discussion on analyses and the impact of iterating and revision in AI outputs.

Live Modeling—Prompting with Purpose Part 2 (10 minutes):
Participants will engage in a brief whole group discussion about the ACDQ Framework as an effective method for prompt writing. Afterwards, participants will be given a basic lesson prompt and challenged to revise the prompt using the ACDQ Framework.

Lesson Design Lab Work (15 minutes):
Participants will use a lesson design checklist that begins with a self-selected content standard, which they will use to generate a learning objective, along with a set of guiding questions which will be used to generate an aligned assessment and accommodating student centered lesson design. Participants will be required to use the ACDQ Framework. Following the checklist ensures the iterative approach. All participants will leave with the checklist and the chat record to further annotate with colleagues.

Making Meaning and Continuous Development (5 minutes):
Participants will share out experiences from Lesson Design Lab Work and receive guidance on annotating and sharing a record of their chat with colleagues.

Closing Reflection (5 minutes):
Teachers will revisit the opening question with new insights, “How can I tell whether I am using AI effectively in my role as an educator?”

PROCESS

Participants will engage in structured interaction approximately every five to seven minutes, ensuring consistent cognitive and collaborative engagement throughout the session. The facilitation sequence models effective classroom pedagogy by blending short demonstrations, guided analysis, collaborative design, and structured reflection.
• Peer-to-Peer and Small-Group Collaboration: Educators will participate in quick discussions and collaborative design sprints that allow them to apply new concepts, share insights, and refine lesson components in real time.
• Device-Based Application: Using ChatGPT or Gemini, participants will practice the Prompt → Review → Revise process to design or enhance standards-aligned lesson components through live, iterative engagement with AI.
• Live Modeling: The facilitator demonstrates each stage of the process—prompting, reviewing, and revising—before releasing participants to apply the strategies independently, ensuring clarity and coherence.
• ACDQ Method Integration: Participants learn and apply the ACDQ framework (Act like an expert, provide Context, think Deeply, and ask Questions) to strengthen the quality and intentionality of their AI interactions.
• Feedback and Reflection: Educators engage in feedback exchanges and whole-group synthesis discussions that connect AI-supported planning directly to authentic, standards-aligned, and student-centered instruction.

This continuous cycle of modeling, collaboration, and reflection ensures that participants leave with a replicable process for thoughtfully integrating AI into lesson design and enhancing instructional outcomes across diverse classroom contexts.

Outcomes

Attendees will leave with (1) a new or refined, standards-aligned lesson plan developed through AI collaboration and grounded in pedagogical expertise. They will also (2) take away a replicable process for integrating AI into lesson planning, captured in a step-by-step design checklist, along with (3) a record of their AI decision-making to share with colleagues and extend professional dialogue across their schools.

Supporting research

Educating for AI fluency: Managing cognitive bleed and AI dependency
https://nickpotkalitsky.substack.com/p/educating-for-ai-fluency-managing

Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task
https://arxiv.org/abs/2506.08872

Stop Skimming Chats, Start Annotating Them
https://mikekentz.substack.com/p/stop-skimming-chats-start-annotating?utm_source=substack&utm_medium=email&utm_content=share

Using AI as a Thought Partner, Not a Shortcut
https://www.edutopia.org/article/ai-thought-partner-teachers

AI Strategies from an Instructional Supervisor with Amir Taron Ayres – Easy EdTech Podcast 338
https://classtechtips.com/2025/09/23/ai-strategies-338/