Welcome & Overview
Welcome to the On-Demand version of the AI for Educators Design Sprint! I’m Jennifer Maddrell, your guide on this design experience. If you’ve ever thought, “I can’t tell if my student wrote this or if it was AI,” you’re not alone.
However, I view academic integrity issues as a symptom of AI integration rather than the root problem. When AI can complete a high-stakes assignment in minutes, that’s not student misconduct. It’s a design challenge!
Design Sprint Focus
In this self-paced replay of our June 2026 Design Sprint, you’ll work through a structured, replicable design process to take one learning experience from AI-vulnerable to AI-resilient. On your own schedule, you’ll work through four design sessions to diagnose what’s no longer working and end with a design plan tailored to your learners that clarifies what to change and why.
Here’s my working definition of the design problem and design aims we’re tackling in this Design Sprint:
- Our Design Problem: An AI-vulnerable learning experience
- Its goals, tasks, or assessments have lost their ability to meaningfully support or measure learning when learners have access to AI tools.
- It relies on outputs, processes, or performances that AI can easily generate, making it difficult to distinguish between tool-produced work and genuine learning of the intended skills and knowledge.
- Our Design Aim: An AI-resilient learning experience
- It meaningfully supports and measures learning even when learners have access to AI tools.
- It makes intentional decisions about the role of AI, and is designed around clearly articulated learning goals, tasks, and assessments that surface and credibly measure learning of the intended skills and knowledge.
This Design Sprint is not about AI-proofing assessments or finding better ways to catch cheating. It’s about designing AI-resilient learning experiences where:
- Learning is visible
- The learning process matters
- AI supports learning rather than replacing it
While you won’t walk away with a finished, polished redesign, you will leave with something more useful at this stage:
- a clear diagnosis of why your learning experience is vulnerable,
- a design decision that names what matters,
- a set of redesign options with their implications weighed,
- a direction you are ready to test, and
- a process you can use again on any learning experience you design or redesign.
How this On-Demand Design Sprint Works
This self-paced design process is built around a simple sequence:
Discover → Define → Develop → Deliver
You’ll bring one of your own learning experiences and work through a process to:
- Discover: Diagnose where and why the experience is AI-vulnerable
- Define: Clarify what meaningful learning should look like in an AI-integrated world
- Develop: Explore redesign options, name trade-offs, and consider promising directions
- Deliver: Plan how you will test and evaluate your redesign
The on-demand Design Sprint blends:
- Two recordings from the live sessions held in June 2026 (the Design Sprint Preview and the Recap)
- Slides from the live Session 1 and Session 4
- Guided design activities to work on independently at your own pace
- Individual design reflection
Importantly, this design process is replicable. Once you’ve applied it here, you can use it again for any learning experience you design or redesign.
Self-Paced Design Sessions
- Start Here | Design Sprint Preview ~45 minutes
Identify an AI-vulnerable learning experience using two Design Brief worksheets. - Discover: Design Session 1 ~60 minutes
Clarify where and why the learning experience is breaking. - Define: Design Session 2 | Guided independent design work ~60 minutes
Audit learning goals and write a clear design challenge statement. - Develop: Design Session 3 | Guided independent design work ~60 minutes
Generate design options, identify trade-offs, and choose a direction. - Debrief & Plan: Design Session 4 ~60 minutes
Reflect on your decisions, surface patterns, and plan next steps for development and reuse.
Note: The Design Sprint Preview and Recap videos are recordings from the live Design Sprint held in June 2026. Slides from the live Session 1 and Session 4 are included on those pages.
The Design Decisions Document
The Design Decisions Document, linked on the Start Here page, helps you capture your thinking during each of the four design sessions of the sprint. It’s structured to help you consider all phases of the Double Diamond design process. You’ll start with a bit of prework and by the end of the last design session, you’ll have documentation for each design step you took along the way.
Jennifer’s Design Challenge
I’ll also be working right along with you on my own AI-vulnerable design challenge related to an Annotated Bibliography assignment that AI can complete in a couple of minutes! Look for my design notes within each design session, which document my thinking and decisions and mirror your own design process in the sprint.
Design Reflections
Each design session also includes opportunities to reflect on your project. You’ll be prompted to consider one thing that feels especially clear or strong, one implication or trade-off you might name out loud, or one question you are curious about.
Optional Resource: AI for Educators Design Lab Podcast
Everything you need is shared on these pages. However, I want to note that this Design Sprint applies the design considerations from episodes 1 and 2 of my AI for Educators Design Lab podcast. While listening to those podcasts is not a prerequisite to your participation, they are available to you for free as optional supplemental background information.
Yours in learning,
Jennifer Maddrell, PhD
Next Path Design