How to Use Inquiry to Integrate AI Into Your Classroom

Do you want to understand how artificial intelligence (AI) can enhance your students’ learning but aren’t sure where to start? Are you curious about AI’s rapidly growing role in education but feel overwhelmed by the options available? If these questions sound familiar, you’re not alone.

Today, teachers around the globe find themselves grappling with how to integrate AI into instructional practice in ways that truly enhance student learning.

As a teacher, you know your students and community, and you are well-positioned to make informed professional decisions about AI’s use in the classroom. Still, as the pace of technological change accelerates, there is no one-size-fits-all set of answers to questions about if, when, and how best to integrate AI into your instructional practice. Fortunately, teachers are forging innovative pathways forward through these uncertainties by leaning on a time-tested approach to professional learning: practitioner inquiry.

Defined as systematic, intentional study of one’s own practice, inquiry places you in the driver’s seat of your own professional learning as you pose questions for investigation that emerge from real-world dilemmas in your classroom, such as how best to integrate AI into instructional practice in meaningful ways.  Teachers’ questions, also known as wonderings, are then addressed through a four-step process that entails:

1. capturing the thinking and experiences relevant to the question that occur as a part of teachers’ everyday work (data collection);
2. intentionally reflecting on what has been captured and the meaning it holds for your own learning and the learning of your students (data analysis);
3. making informed changes to improve the learning of your students (action); and
4. communicating what you have learned through inquiring with others (sharing).

This process can occur in shorter daily bursts (i.e., within one lesson executed that contains an AI component), entire school year investigations (i.e., within a professional learning community centering their school-year’s work on investigating the integration of AI into instructional practice together), or anywhere in between. Over the past year, we have collected many examples of how teachers are innovating their teaching by exploring AI with their students through inquiry. Read onward for one example.

Sara Montgomery, a middle school science teacher, decided to use the process of inquiry to investigate the ways new AI technologies could help solve a persistent problem in her science classroom: students’ being able to create models that both look good and show deep conceptual understanding of the content being taught. Although Sara and her students would make many models throughout the year, her students often struggled with hand-drawn models. Some students, who were artistic, focused on the “art” of creating the model, working to create a perfect drawing at the expense of why they are creating the model in the first place.  Other students, who didn’t feel confident in their artistic abilities, were paralyzed by their perceived inability to draw.  Their insecurities about art caused them to be overly focused on the mechanics of model creation, and they struggled with their own creative representation of phenomena. After years of trying to convince her  students that she was not concerned with the quality of their drawings, what she really was interested in was how they explained the model, Sara decided to change tactics.

Enter AI.  Instead of creating hand-drawn models, as in previous units, Sara used the process of inquiry to investigate what would happen if she introduced students to Adobe Firefly (an AI image generator) to create an AI generated image representing one of Newton’s Laws of Motion during a new unit she was teaching on this topic. She developed the following wonderings, “How can the use of AI generated images provide a framework for middle school students’ annotation of scientific models to demonstrate their understanding of scientific phenomenon?”, and “How does the use of Adobe Firefly impact student engagement with the scientific modeling process?”

Once introduced to Adobe Firefly, students used a graphic organizer to keep track of their model’s progression and as a place for self-reflection and peer feedback.  These graphic organizers became one form of data Sara collected to gain insights into her wonderings.

From analyzing her students’ graphic organizers, Sara learned that many students were initially frustrated with creating an image that showed their thinking. For example, many of her students began their interaction with Adobe Firefly with the basic prompt, “Create an image that shows Newton’s 2nd law”. The students who used this prompt initially were frustrated to find an image of the “scales of justice.” After Sara discussed with her students why this might happen (the image generator focusing on the word “law”), they came to the realization that they needed to make a better plan about what they wanted to portray and ask for that instead. Sara’s analysis of her students’ graphic organizers showed that as students worked with Adobe Firefly, their prompts improved. Eventually, students were able to engineer their prompts to create an image that displayed the images in their head, and represented their conceptual understanding of Newton’s Laws.

Through engagement in a simple inquiry cycle (posing wonderings, collecting and analyzing data in the form of student work, and taking action to teach her students more about how to effectively use Adobe Firefly to create their models), Sara gained new insights into the role of generative AI for reducing barriers to students’ engagement with modeling their understandings of scientific phenomena.  Sara shared her findings from this inquiry with colleagues during a school-wide professional learning day.  As a result of this presentation, teachers at Sara’s school developed a heightened awareness of the necessity of teaching students how to formulate and refine prompts when interacting with AI image generators and/or chatbots to meet particular learning goals.  Inquiry served as a powerful professional learning vehicle to gain insights into AI’s use not only for Sara, but her colleagues as well.

As this example illustrates, by utilizing inquiry as a means of integrating AI, teachers are finding creative ways to make AI a part of—rather than apart from—their teaching and, ultimately, to enhance the learning of the P–12 students they serve. For more creative ideas about integrating AI into your classroom through inquiry, check out our new book, The Reflective Educator’s Guide to Practitioner Inquiry (5th edition), available now from Corwin Press.