Using AI tools with students to support their design inquiries

Over the past year I have been exploring how to use AI in the planning and delivery of design inquiries. These tools have opened up new opportunities and workflows, both for me and my students. I started by using AI tools to support the delivery of content to learners by providing differentiated background text and resources.

Recently my students and I have been exploring ways of using AI as a research assistant, critical friend, or colleague. This has lots of potential in the design inquiry process. Students can use chat bots such as ChatGTP, Poe, or Perplexity to inquire into, jumpstart, or scaffold various steps of a design inquiry. This might look like:

• Generating a persona of a user and then ask it questions;

• Asking AI to suggest possible design constraints to context;

• Having a conversation with a fictional user, expert, or secondary user in order to uncover needs or new perspectives

• Asking the AI to suggest possible research directions for further exploration;

• Asking the AI to suggest possible considerations or possibilities for a design solution.

The links above link to chats with ChatGTP and Perplexity, where you can see how a conversation develops.

Below is an example of a scaffold we are using with students to guide them in the creation of a persona in an Large Language Model AI such as ChatGTP.

As we have navigated this, we are coming to see the importance of user research to help frame and guide the AI. This powerful technology can swiftly offer generic persona templates, but creating a meaningful persona demands a foundation rooted in research. As such its important to guide students through a process that includes face-to-face interactions, observations, and interviews. These steps are vital for developing a nuanced understanding of user needs and fostering empathy, a cornerstone of human-centered design. The AI offers a way to consolidate, summarize, or present different perspectives - but it is not a substitute.

Below is an example of the kind of resource that we are working through with students.

I’ve shared more of these explorations and strategies on my Design and Inquiry site for design educators and students.

It is crucial for educators to recognize that the outputs of AI models represent nuanced interpretations influenced by the underlying training data. Therefore, critical thinking plays a pivotal role in equipping students with the capacity to formulate insightful inquiries during the design phase. This intellectual rigor prompts students, under the guidance of educators, to question assumptions, discern potential biases, and scrutinize the model's operations. Through emphasizing these analytical skills, students are empowered to move beyond surface-level acceptance of AI-generated results, fostering a mindset oriented towards depth, precision, and nuanced understanding.

Developing a Continuum of Inquiry: First steps

In Washington DC right now at the National Coalition of Girls Schools Global Forum II. My colleague, Kathy Binns, Head of Science, and I are presenting on our work integrating science and design in interdisciplinary projects. This has been a valuable opportunity for us to reflect on where our respective programs (Design and Science) are going, and how they overlap and support each other.

Our presentation shared what we have been doing and our thinking about future directions. As an IB school, we are focused on developing our students into inquirers and thinkers. Our interest lies in developing our students' skills to become collaborative and independent designers and thinkers.

Thinking of inquiry as a continuum, we have conceptualized it as above. Each grade level undertakes a large-scale IDU (Inter-Disciplinary Unit) during the course of the year. We envision these intensive experiences as opportunities to develop and apply skills and understandings, with each year building on the previous, towards a culmination in year 11.

• Grade 6: Collaborative experiences that develop these 
• Grade 7: Presentation and Communication of learning
• Grade 8: Risk-taking to develop unique solutions
• Grade 9: Inquiry using data and iteration to solve challenging problems
• Grade 10: Applying research and analysis to synthesize new solutions to challenging problems
• Grade 11: Collaborative scientific inquiry to support the Group 4 project (a mandatory part of the DP curriculum)

The Grade 9 and Grade 10 projects dealt with sustainable energy production and biomimicry, respectively. This year, Grade 8 inquired into developing oil recover systems using robots. This was inspired by an oil spill of the cost of Jeju Island. Our grade 7 unit was performance art based, while the grade 6 explored digital media and story-telling.

This framework is the first step for us. It builds upon what we already have in our curriculums. Yet, we did not really know what had until we started to reflect on the connections. Based on some conversations with others at the conference, as well as watching some excellent presentations, we are inspired to iterate these IDUs further. Developing service opportunities and authentic audiences are our next steps, as well as strengthening the connections we already have are our two goals.

Computational Thinking and the Design Cycle

The concept of Computational Thinking helped me see the teaching of coding in a completely new way. I was struggling to find a way to teach coding from an inquiry perspective, while at the same time ensuring students developed a strong foundation in basic principles. I wanted to avoid the rote teaching and practice of coding language, and instead engage at a deeper level with what coding is.

Framing the learning of coding from the perspective of computational thinking has helped me and my students really understand the essence of learning a computer code. There are several variations of computational thinking, but the one I'm following, and which is closely aligned with the IB computer science model, considers these four concepts:

• Algorithms: Understanding and creating rules
• Pattern recognition:
• Decomposition
• Abstraction

students creating shared understandings of computational thinking concepts

In the teaching of code, I've been emphasizing to students how computational thinking concepts can be applied to other areas of making. I shared the band Wintergaten's Marble Music Box, as an example of how computational thinking is employed to solve complex design problems. 

Students watched the video and discussed where they saw loops, variables, patterns, and so on in the performance and the machine. They discussed how the designer might have used concepts like decomposition to create the machine.

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Key to helping us understand and engage with computation thinking concepts were resources from Google and the BBC. 

BBC's Bite Size site has a really engaging introductions to coding and computer science. We used this site to explore the concepts.

Google's Exploring Computational Thinking for educators does a great job of showing how CT can be applied to other areas of inquiry, and how features some great examples of lessons that apply CT to different contexts such as history, science, and geography--great examples of interdisciplinary learning.