AI in education should be treated as seriously as driving a motor vehicle. We don’t throw our car keys to a child and say “have at it.” We introduce them to the rules of the road, let them practice behind the wheel in empty parking lots, drive on local roads with an adult in the passenger seat, and then let them go it alone after passing a competency test.
AI is no different. We need to provide proper scaffolding, and we need to navigate through certain checkpoints ourselves before guiding our learners through each step.
AI will be an accelerant in every field it touches. In K-12 education, it’s our responsibility to guide it toward the future we envision, one where all learners know who they are, thrive in community, and actively engage in the world as their best selves.
This broader view of success requires a learner-centered approach that embraces co-design with learners and communities. It will be important to keep this aspirational future in mind and to ensure educators are actively engaged in co-creating and building together.
There are opportunities and risks with AI we will need to navigate on the journey. On one hand, AI presents the opportunity to personalize learning in new and profound ways, automate small or redundant tasks so we can focus on building deeper relationships with learners, and enhance accessibility through adaptive technologies that improve access to learning materials. On the other hand, AI presents many challenges around establishing ethical standards (e.g. data privacy), ensuring we have proper training in place to establish and evolve good AI practice in classroom settings, and avoiding an over-reliance on AI to do our thinking and creating for us.
Understanding how to effectively incorporate AI tools into our learning communities, so we can take advantage of the opportunities these tools provide (and mitigate the challenges), is every educator and administrator’s responsibility. This integration process has four key checkpoints—starting with the most rudimentary (e.g. understanding what AI is) and building up to advanced applications (e.g. building AI tools).
Checkpoint #1 : Understanding What AI Is
AI, at its core, involves systems capable of performing tasks that normally require human intelligence. These tasks can range from recognizing speech to making decisions based on visual inputs to sensing non-verbal cues. For educators, a foundational understanding of AI’s capabilities and limitations is crucial.
Remember, we’re looking to develop understanding. We understand a car isn’t going anywhere with a flat tire or a dead battery, but we don’t necessarily need to know how to create a tire or build a battery. The same is true for AI. Let’s understand how it works, so we can confidently and competently talk about it with our colleagues and students.
We have found it helpful to ask educators to define AI, share examples and models with them, and then ask them to redefine AI. This unearths what is known, misconceptions, and common questions. This brief exercise builds shared context and common language to support collaboration and movement to the next checkpoint.
In a recent workshop where we took participants through this exercise, educators initially described AI as a powerful calculator that was strong at specific, tangible tasks. After we provided brief definitions and examples, including a primer on how novelty is a key feature (and bug) for Large Language Models (LLMs), the attendees were able to redefine AI based on an enhanced foundation of conceptual understanding.
Developing shared understanding and common language establishes the base for the next Checkpoints and addresses a common key barrier to getting started—a lack of foundational AI literacy.
Checkpoint #2: Engaging With AI Tools
Before introducing AI tools to our students, we as educators should engage with these technologies ourselves. This direct interaction allows us to evaluate the tools’ effectiveness and relevance to our educational objectives. It also prepares us to address any potential issues the technology might present like hallucinations and bias or security risks. This step ensures educators are not just passive recipients of technology but informed users who can critically assess and effectively integrate these tools into their teaching practices.
Educators who lack direct experience with AI tools are often unaware of how these these rapidly evolving tools can enhance performance. We have observed that educators who are active users of AI have an expanded sense of possibility and are well-positioned to identify opportunities for AI to be used productively in their professional roles.
Take Carissa Solomon, an educator at Embark Education in Denver, Colorado, as an example. After engaging with AI herself, Carissa noticed, “Learners had already been experimenting with ChatGPT but doing so secretly because they thought it was forbidden.” Rather than keeping the technology in the shadows, she created space for her and her students to explore it together. As a result, they discovered potential uses for the technology that aligned with their learning goals and school culture.
Checkpoint #3: Customizing AI Tools
Integrating AI into education should go beyond general usage, involving customization that reflects the unique needs of each educational setting. AI operates on layers of data and algorithms, with a significant component being the reference layer. This layer acts as a context setter, ensuring AI operations align with specific goals and values.
For example, in a learner-centered model, the reference layer might include your district’s vision, mission, values, Portrait of a Learner, and learning model. Then, when you interact with the tool, like creating a new lesson plan, the AI’s outputs will steer toward the objectives found within these core documents and frameworks.
At Learner-Centered Collaborative, we have been creating and incorporating references into AI apps. This process extends the capabilities of the AI so that the output is relevant and useful in various contexts. In the following example, we put the Encinitas USD Framework in Playlab to support educators in designing units aligned with their Portrait of a Learner.
In another collaboration, Playlab and Learner-Centered Collaborative worked with educators from Laguna Beach School District to design learning experiences that aligned to their specific context. In particular, the district wants to enhance environmental literacy across all age groups. By adding their environmental standards to the reference layer (along with their Portrait of a Learner), the AI tool was able to design meaningful learning units and activities that were both relevant and engaging to students.
You can try something similar with the free version of ChatGPT. Consider a lesson you would like to plan and write the following prompt:
“I would like to design a lesson for [insert grade or age range] around [insert topic]. For this to be a successful lesson at its conclusion, my students should be able to [insert outcomes that align to your assessment rubric]. This lesson design should follow [insert learning experience design principles].”
These examples illustrate the potential to leverage AI for contextualized deeper learning, enhancing the impact of learning experiences to support real-world problem solving in K-12 education. Further, the active customization of AI tools creates a sense of ownership that naturally leads to building original and impactful resources for authentic learning.
Once you reach this third checkpoint, your imagination and creativity will start ramping up. You’ll want to start creating solutions with more nuance around the specific needs of the learners you serve, and you might find some out-of-the-box AI tools aren’t quite serving your more advanced needs. That’s when the fourth and final checkpoint comes into play.
Checkpoint #4: Building Your Own AI Tools
The ultimate step in integrating AI into educational settings involves creating bespoke AI tools that fully align with an institution’s educational philosophy and goals. This involves customizing existing tools and developing new applications from scratch. Engaging in this process ensures AI tools are deeply embedded in the educational fabric of the school or district, providing tailored support that enhances learning outcomes and fosters a deeper connection between technology and education.
As an example, we conducted a workshop for the San Bernardino County Office of Education and district leadership teams in the county. During the session, we asked participants to create their own AI app. The team from Colton Unified School District generated a chatbot coach customized to their district strategy.
After our workshop, they shared the chatbot with a team of teacher innovators to begin expanding the learning and possibilities for AI throughout their district. Due to the initial success of this prototype, Colton Unified has decided to train a broader group of educators to build a wider array of AI applications.
This collaborative development of AI tools represents the next frontier in the Open Educational Resources (OER) movement. With AI, we can create our own resources, but we can also make them openly available to other educators. This expands the array of possibilities for learners and leverages the benefits of diverse perspectives and approaches.
Remember, AI is Just a Tool (and We Have a Role in How It Is Used in K-12 Education)
Integrating AI into our educational settings will only help us realize the outcomes our systems and processes are directing us toward. If our system prioritizes teaching to the test, requires students to comply with the system, and sifts and sorts kids, AI can help do that better. If our system encourages learners to know themselves, thrive in community, and actively engage in the world as their best selves, AI can help with that, too.
As you work through the four checkpoints for integrating AI into your educational setting, doing so with a goal toward openness and deeper learning can help us achieve a broader definition of educational success and create a brighter future.
Importantly, those who are engaged with the co-creation of AI resources will set the stage for what AI helps us create in the future. As learner-centered leaders, we must be involved in this co-creation process, so we can influence the direction. AI can happen to us or we can direct AI to help us shift to new models of teaching and learning.
Each of the checkpoints above builds towards a comprehensive understanding and utilization of AI. With a clear vision for the future and by staying a step ahead in understanding and applying these technologies, educators can ensure they are well equipped to guide their students through the digital age without compromising on the human touch that is at the heart of education.