America’s education system was a groundbreaking effort to help a growing nation thrive in the 19th century. Now, 200 years later, the world has changed; the horizon looks drastically different. Collectively, we need to redesign our education system to enable all of our children — and, by extension, our nation — to thrive today and tomorrow. “Horizon Three” or “H3” names the future-ready system we need, one that is grounded in equity serving learners’ individual strengths and needs as well as the common good. This series provides a glimpse of where H3 is already being designed and built. It also includes provocations about how we might fundamentally reimagine learning for the future ahead. You can learn more about the horizons framing here.
By: Collective Shift
An audio podcast version of this blog, created by Notebook LM.
In the first article in this series, Tom Vander Ark outlined three opportunities for shifting education from a traditional, efficiency-based industrial model to a future-ready, learner-centered “Horizon 3” model: new school development, the creation of learner experience networks, and school transformation. School transformation is in many ways the most complex, as evidenced by the fact that we’ve historically struggled to do it at scale. Although the world has changed vastly, the majority of the U.S.’s 54 million K12 students and four million teachers still spend six or more hours per day in schools reflecting the “Horizon 1” model, where teaching and learning don’t look significantly different than they did half a century ago. Finding ways to transform the collective educational experience is critical.
H3 Graphic from Learner Studio
Collective Shift – an alliance of eight organizations that combined have over a century of experience envisioning, designing, and building competency-based, learner-centered classrooms, schools, and systems – believes that today’s advances in generative AI present a unique accelerant to successfully transforming schools and school systems.
What is Generative AI and How Might It Change the Game?
Generative AI refers to artificial intelligence technology capable of creating new content, ideas, or solutions by learning from vast amounts of existing data. People naturally use AI to make their work easier, and they build what they know. If the majority of educators are in Horizon 1 schools, the sorts of AI uses they’re likely to envision will perpetuate the practices of a Horizon 1 education system: more multiple choice tests and assignments, worksheets, and lesson plans. There’s plenty of that out there, with or without AI support.
Our classrooms are diverse, and students have differing needs, something educators struggle with supporting, given the many demands on them. Creative educators are using generative AI to:
differentiate teaching (to meet some of the needs of small groups of students)
individualize teaching (meet some of the needs of an individual learner)
personalize teaching (think, the barista putting your name on your Starbucks latte).
For example, at a recent AI event we attended, an educator was deeply excited to build a chatbot that could generate new multiple-choice quizzes for the group of students who were absent on the day of the in-class quiz. Another educator created a chatbot that improves textbook math problems by taking inputs about grade level, content standards, geographical location, and comfort with the topic. On the left is a problem the AI chatbot generated for a teacher to use with 6th graders in Los Angeles, while on the right is a classic textbook-style problem. The AI version spices the problem with local context and personalization. You can imagine an AI chatbot that could instantaneously generate a different word problem for each child using their name – Starbucks on steroids.
Mia, a sixth-grader at a Los Angeles middle school, is designing a poster for her school’s upcoming film festival. She wants to create a rectangular poster with a star-shaped cutout in the center, representing the Hollywood Walk of Fame. The poster’s dimensions are 24 inches by 18 inches, and the star cutout is a regular pentagon with each side measuring 6 inches. a) Calculate the area of the rectangular poster. b) Find the perimeter of the star-shaped cutout. c) Determine the total area of the poster, excluding the star-shaped cutout.
These are all powerful uses of GenAI, but they aren’t moving us to the horizon of student-centered learning, student agency, competency-development, or more fluid boundaries between school and the world outside. GenAI is currently primarily serving as an accelerant of the Horizon 1 to Horizon 2 shift. Think the math problem above, or instant development of lesson plans that take into account learners’ interests, or access to unlimited AI-powered one-to-one tutoring. The majority of AI tools currently being built and deployed in schools fall into this shift towards more responsive teaching. AI companies in education, whether nonprofit or for-profit, go where the market is, so they promote products and practices that perpetuate and even entrench H1 and H2, both of which focus first and foremost on mass or small-group teaching.
In short, Generative AI is currently enabling what Barbara Bray and Kathleen McClaskey years ago defined as differentiation and individualization of teaching vs. the personalization of learning.
Copyright: Barbara Bray and Kathleen McClaskey
You will note that the left column in the chart above is the only one not focused on teaching – on what the teacher will do; it’s focused on what the learner does. We believe that GenAi can accelerate the transformation of school to personalized learning. Below are a few examples of how.
Lowering the Barriers to H3 Practices
A core element of Horizon 3 is a different set of responsive, reciprocal behaviors and relationships: between educators and students, between students, between school and families, between school and communities. School is no longer about teachers stuffing content into willing or unwilling students but rather about growing the competence of young people to become fulfilled, thriving, contributing, self-sustaining members of society. Competency-based education (CBE) is a shorthand for the set of teaching & learning practices at H3’s foundation. In a recent EdWeek Research Center survey, a majority of educators said they are interested in learning more about these practices, but 51% said they don’t know how to do them. For school transformation at scale, extensive educator professional learning will be needed. Generative AI cannot replace professional learning, but it can greatly accelerate access to H3 for everyone. In the sections below, we give examples of how AI can support school transformation across two domains – personalized learning (as opposed to teaching) and personalized coaching as support for personalized learning. We’ll explore examples for three different levels of experience:
Those who have no access to H3 professional development
Those dipping their toes into H3 practices
Those with moderate to significant experience with H3 practices
Localization and Personalization: Tailoring Education to Local Needs and H3 Design Experience
One of the most compelling applications of generative AI in education is its ability to personalize learning experiences to local contexts and resources. This means that adults and students can develop curricula and tools that resonate with their specific community values, cultures, and needs — and their Portrait of a Graduate, where many schools and districts start in their transformation journey. Once a community has created a Portrait of a Graduate (or Learner), they often don’t know what to do next. It’s all well and good to say we as a community want our students (and adults) to be ‘Capable Communicators’ – but what does that mean and how is a student or classroom teacher or school leader to work with this? This is one place where GenAI can accelerate change. Take the Grad Portrait Rubric & Progression Builder app developed on Playlab by the team at Building 21 (both of whom are members of Collective Shift). This tool enables schools to create competency-based progressions and rubrics aligned with their unique Portrait of a Graduate. A school or system can input their community-designed set of competencies, and the app generates customized frameworks that young people and adults can use to assess their learning progress. Without the help of such an AI tool, progressions would take tens of hours of human time to build; the AI tool creates an excellent working draft in less than 30 seconds. Here you can see the conversation we had with the GenAi tool to build out what ‘Capable Communicators’ means from ages 4 to adulthood. It took less than a minute. For coherent school transformation, Collective Shift strongly recommends that Grad Portrait-aligned progressions be used at a school-wide (if not district-wide) level, rather than each educator creating their own version. For education to be relevant to young people, they need to explore issues and solve problems in their local context that matter to them personally. Consider a school aiming to incorporate local history and community issues into their learning design. Teachers just getting started with H3 transformation can use Playlab to create a chatbot that is “trained” to reflect these local elements and embed it into their learning experiences. Or, they could use a project-builder AI that lets adults or students design a local context project in a fraction of the time it would take to build by hand. Each student could, if they desired, build their own personally compelling exploration of their community. This level of personalization empowers students to see themselves and their communities in their education at a much deeper level than before and allows them to take full advantage of the community engagement work that goes into the development of a local Portrait of a Graduate. Horizon 3 transformation doesn’t mean that students do everything. Teachers, in fact, have an even more active role in building a strong relationship between students, communities, knowledge, and knowledge application processes: they become designers, co-designers (along with students and often community members), coaches, and facilitators of learning experiences (projects). As Antonia Rudenstine described in a previous article in this series, helping students develop future-ready competencies requires “relevant, meaningful projects, designs, products, artifacts, and more”. Doing this well takes a lot of time and effort – and GenAI can serve as a powerful co-pilot. For example, Inkwire, also a member of Collective Shift, has developed an AI-powered tool designed to assist teachers in crafting transformative educational experiences. As hurricane after hurricane hits the US, imagine a classroom of young people curious about exploring what’s going on. Their curiosity inspires their teacher to develop a project-based unit on topic but she feels overwhelmed by the planning involved. With a tool like Inkwire, she can input her goals, go through an AI-assisted brainstorming process, and come out on the other side with a scaffolded plan complete with resources, timelines, and assessment strategies. This is a very different approach to the math problems showcased above. Additionally, as teachers interact with these tools, they naturally upskill—learning new methodologies and strategies simply from their day-to-day use of the tools. For example, Inkwire partnered with the Professional Learning team at the High Tech High Graduate School of Education to embed their Deeper Learning design framework into the tool itself. This allows educators to “carry” these professional learning resources with them in their everyday tools. The AI doesn’t replace the teacher’s expertise but enhances it, making the adoption of H3 practices more attainable. Teachers, in the best future-ready way, learn what project-based learning is by doing it – rather than being told about it. Scaling Coaching: Making Expert Guidance Accessible Professional coaching is instrumental in driving school transformation, but it’s often resource-intensive and inaccessible to many educators. Generative AI offers a solution by encapsulating coaching expertise into scalable tools that educators can access anytime, anywhere. Ask Gabby is a thoughtful AI coach developed by Sujata Bhatt of Incubate Learning (also a Collective Shift member). Bhatt has decades of experience as a teacher, and as coach for school and district leaders, educators, and students. Designed to help users build their learning identities and based on the science of learning and development, Gabby provides personalized guidance, reflective prompts, and actionable feedback– for young people and adults. Through the process of designing Gabby, Bhatt was able to translate her expertise as well as research into an interactive, conversational tool that is accessible anytime, anywhere, in private and anonymously. Picture an educator in a remote district with limited access to instructional coaches. Through Ask Gabby or other AI-powered coaches, they can engage in reflective practices, set professional goals, and receive tailored advice to improve their teaching. They can role-play or debrief an experience or situation in real-time in private – as often as they’d like, 24/7. This not only democratizes access to high-quality coaching but also fosters a culture of growth mindset and continuous improvement. It fosters a culture of professional learning. Here is a sample conversation with Gabby. As the technology develops further, these AI coaches will be able to analyze patterns over time, providing insights into common challenges and areas for growth for individuals and across a school or district. This data-driven approach will enable leaders to make informed decisions about where to allocate resources and how to support their staff effectively in service of a Horizon 3 learning model. Moving Forward: An Invitation to Transform Collective Shift believes if we take collective action to identify, design, build, test (and fund) a suite of tools that enable the shift to the behaviors on the left of the table above, then Generative AI will be able to transform education by accelerating the personalization of learning. Actionable Steps for Education Leaders: Pilot AI Tools in Your Context: Begin by integrating AI tools in a small setting to assess their impact. Foster a Growth Mindset Among Staff: Encourage educators to view AI as a partner or co-pilot in innovation rather than a replacement, promoting openness to new technologies. Invest in Infrastructure and Training: Ensure that your school or district has the necessary technology infrastructure and provides professional development to maximize the benefits of AI tools. Engage with Stakeholders: Involve students, parents, and community members in conversations about how AI can enhance learning, addressing any concerns and setting shared goals. Collaborate Across Networks: Join or form networks with other education leaders exploring AI to share best practices, challenges, and successes. Join the Conversation The integration of generative AI in education is more than an opportunity to simply save time or automate workflows; it’s a call to action to redefine what education can be. It’s about creating learning environments that are as dynamic and diverse as the students they serve. We invite you to be part of this journey; together, we can push the boundaries of what’s possible. Collective Shift is an alliance of eight organizations working together to put the human back into AI. And put AI to work to help us redesign education. They are Building 21, NGLC, Incubate Learning, InkWire, National Equity Project, Learner-Centered Collaborative, Playlab, and reDesign. This blog series is sponsored by LearnerStudio, a non-profit organization accelerating progress towards a future of learning where young people are inspired and prepared to thrive in the Age of AI – as individuals, in careers, in their communities and our democracy. Curation of this series is led by Sujata Bhatt, founder of Incubate Learning, which is focused on reconnecting humans to their love of learning and creating.