Explore Kentucky's future education ecosystem in 2040 with Horizon 3, focusing on equity, agency, and lifelong learning through AI and community. The post Kentucky’s Learning Ecosystem in 2040: A Day in the Life appeared first on Getting Smart.
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.
As our next horizon learning series comes to a close, we wanted to bring many of the threads together. We’ll be doing this in two ways.
- This week we imagine the learning journey of a 14 year-old high school student in Kentucky in 2040, moving back in time to show what their earlier education was like and jumping forward to show what their future might hold.
- Next week, we’ll be synthesizing the 20 blog posts in the series into a manifesto with design, policy, and funding recommendations.
Introduction: Kentucky in 2040
The year is 2040, and learning in Anytown, KY, moves with the rhythm of its students. Education is no longer bound by walls or bells—it flows through homes, parks, innovation labs, and bustling city streets. Every space holds the potential for discovery.
This transformation began with a movement. Families, educators, and communities came together through United We Learn and shaped the iterative Portrait of a Learner, a shared vision that turned Kentucky’s schools into dynamic ecosystems of exploration and growth. They also developed a local accountability model that, after multiple prototypes, testing, and iteration, became the promise of collaboration and excellence connecting schools and their communities.
Jordan, 14, wakes up ready for another day of learning without limits, surrounded by teachers, other adults, and peers who serve as guides, mentors, and collaborators—adapting their support to each student’s journey. Let’s go on this journey, moving through Jordan’s past, present, and future.
Early Years: The Spark of Curiosity and the Foundation of Inquiry and Agency
From the moment Jordan could walk, learning felt like an adventure. Mornings filled with stories under the sycamore trees, afternoons spent following trails of ants through the community garden, collaborative play with other three to five year olds. Questions led to more questions, and every discovery sparked a hundred more.
At three, Jordan spent hours in the Anytown Early Learning Hub, where classrooms blended into forests, art and discovery studios, and open-air theaters. One morning, Ms. Rivera, a literacy specialist, gathered children on a sunlit rug and opened a beautifully illustrated book. As she read, she traced her finger under the words, encouraging the children to follow along. Jordan pointed at a word—“river”—and sounded it out with her.
Reading grew from moments like these, from tracing letters in the dirt with sticks, from street signs on daily walks, from the rhythmic call-and-response of storytelling circles.
Math wasn’t taught in isolation. It was part of everyday play—counting seeds in the garden, comparing the sizes of footprints in the mud, measuring how far they could jump. Mr. Patel, a numeracy coach, didn’t give worksheets; he asked questions: “How many steps does it take to cross the bridge? If we take bigger steps, does the number change?” Math was movement. Math was a discovery.
Inquiry and agency, as well as literacy and numeracy, were woven into everyday life, as natural as running and climbing. Adults helped share the learning with families by documenting students’ interests and creativity, growth and development, in digital portfolios which families also could contribute to. Learning happened everywhere.
Elementary School: Strengthening Foundations, Agency, and Inquiry
Elementary school buildings were living learning hubs, integrating AI- and human support in foundational skills labs for math and language literacy, in-school design labs, home-based exploration experiences, and real-world experiences. The Anytown Young Learning Commons, Jordan’s home base, was a space where students of many ages gathered to tackle big questions and acquire the skills they needed to address them.
One day, Jordan, in a group of seven to ten year-olds, designs solar-powered lights for a neighborhood park. Ms. Chen, a math mentor, sits beside them, sketching out a design specification. ““The park wants to power 10 streetlights, each consuming 20 watts per hour for 10 hours each night. How many solar panels would we need to install to ensure the battery has enough energy stored? Jordan frowns, pulls over a piece of paper, and starts playing with the numbers. Math isn’t an abstract concept—it’s a tool that helps bring ideas to life. When he needs additional support with the fundamentals of division, Jordan can spend time in the foundational skills lab which he gladly goes to, because he wants to be able to work on the parks project.
That afternoon, Jordan and a small team gather at the Design Lab, where the early years teachers have given them a different challenge, one that addresses a very real need the teachers have: create a toy that helps 4- and 5-year-olds learn how to share.
Ms. Alvarado, a design mentor, encourages them to empathize and think about what makes sharing difficult. “What do little kids argue over the most?”
“Taking turns,” Jordan says. “And they don’t like when someone messes up what they’re building.”
“Would you like to see a video of our littles playing on the rug yesterday?” the early years teacher asks.
The group watches and analyzes for patterns in behavior. They then discuss what they each observed, and formulate a problem statement.
Individually, students sketch ideas on butcher paper or tablets, whichever they prefer. Then they come together in small groups to brainstorm and decide on what to prototype. One group is interested in designing a cooperative building game, where pieces light up only when two players work together. Another proposes a storytelling puppet, where characters switch between players, encouraging turn-taking. Jordan’s group leans toward a marble run that only works when kids place pieces together, requiring cooperation. He snaps pictures of their ideas and uploads them into their digital documentation portfolios.
Over the next week, they build paper prototypes and then work with adults and older peers to fabricate their ideas. Some work with sewing machines, others in the wood shop, and still others with the 3D printer. They then test their prototypes with an actual group of 4-year-olds in the early learning hub. Some ideas flop immediately. The kids argue over who goes first, or ignore the cooperative elements entirely. Ms. Alvarado reminds them, “Great designers learn from mistakes. What can you change?”
Jordan and his team tweak their design, adding a timer that guides turn-taking. By the end of the week, the 4-year-olds are laughing and negotiating as they play, the early years teachers are happy, and Jordan feels the deep satisfaction of seeing an idea come to life. In his growth journal he reflects on learnings from the project: of the design process, of building techniques, the math they used to measure and design, what was difficult (collaboration, always!). He shares his reflection with his AI coach and, through back-and-forth, they sharpen the reflection. The AI coach then parses the reflection into skills and competencies and adds the data to the team’s learner wallets, ensuring that their skills are visible and easily communicable as they move throughout their learning lives. They then decide that this project is good enough to go into their mastery portfolio, and they make an appointment with Mr. Smith, their advisor, to review and discuss their portfolio entry.
Middle School: A Community-Based Ecosystem with Pathways for Deeper Learning & Ethical Decision-Making
By middle school, Jordan’s world stretched far beyond a single building. Traditional school buildings gave way to a citywide learning network where Jordan was empowered to follow his passions.
Jordan stepped into a flight simulation dome, fingers gliding over the controls as altitude numbers adjusted. Mastering flight requires a blend of technical knowledge, mathematical reasoning, and real-time decision-making. To intentionally engage with the learning experience, Jordan needs to grasp the fundamental principles of flight (lift & drag, thrust & weight, angle of attack – all applied physics concepts).
Jordan feels the AI’s feedback but doesn’t yet understand why his last turn caused a stall. Mr. Ellis, a former pilot who has been trained to support students, steps in: “You pulled up too sharply. Your angle of attack exceeded the critical limit, so airflow around the wings became turbulent, and you lost lift.” Jordan now has both digital visualization and human insight, making the mistake a powerful learning moment.
The next week, Jordan joins a community resilience project, working with city planners to study flood risks in a neighborhood park. AI processed weather data from the past 20 years, highlighting trends that students analyzed. Ms. Nembhard, a data science instructor, introduces them to probability models.
“There’s an 80% chance of heavy rain next week,” she says, pulling up satellite data. “Based on past storms, what’s the probability that the park will flood?”
Jordan and their team analyze elevation maps and past rainfall data. They calculate that when the soil is already wet, the flood risk jumps from 40% to 75%—a huge increase.
They present their findings to city officials, suggesting small bio-retention ponds to absorb excess water. Jordan begins to understand probability isn’t just numbers on a page—it’s the key to predicting real-world events and making smarter decisions.
Not all learning was technical. In Civic Engagement Lab, students were handed a real-world ethical dilemma: Should a city prioritize funding for affordable housing or environmental conservation?
AI acted as a neutral data aggregator, pulling policy insights, historical case studies, and community perspectives. But it was Ms. Wiggins, the ethics teacher, who guided the debate, challenging students to weigh the human impact. Jordan took a stance, then revised it after hearing counterarguments from three of his peers. At first, Jordan strongly resisted the counterarguments, insisting that their idea was the correct one. Ms. Wiggins urged Jordan to take a moment in the quiet space and spend some time with the collaboration competency progression (listening is a critical part), and talk it through with his AI coach. Jordan came to feel how his body was tensing and his emotions were dysregulated. Calmed, Jordan came back to the group, and asked if they would repeat their counterargument. Ms. Wiggins was so impressed with Jordan’s growth in this project that she asked them if they might want to add this project also to their mastery portfolio.
High School: A World of Possibilities
By high school, Jordan moved seamlessly between disciplines, designing his own learning path with the support of mentors, AI copilots, and hands-on experiences.
Mornings at the Anytown Innovation Lab hum with energy. One day Jordan and a small team gathers around a 3D printer, shaping a prototype for a disaster-resilient shelter. On another, Jordan is in Digital Storytelling Studio crafting an interactive narrative about his great-grandmother’s journey to Kentucky. AI helps transcribe old family interviews, suggesting narrative arcs, but it’s Mr. Thompson, their storytelling mentor, who pushes them to find the emotional core.
Later in the year, Jordan participates in an international AI collaboration challenge, working with students from Ghana, India, and Brazil. Their goal: design an AI model that helps farmers predict drought conditions. AI translates conversations in real-time, but Ms. Fields, their global studies mentor, reminds them that technology is only as good as the people who use it. The students discuss how to balance AI’s efficiency with the wisdom of indigenous farming practices—a lesson in both technology and humanity.
Afternoons open into deeper community work. Jordan joins a Civic Leadership Fellowship, helping redesign Anytown’s bus system. Meetings turn into brainstorming sessions, then working sessions, then real-world impact as Jordan’s team launches a student-led micro-mobility project.
Throughout it all, AI suggests learning experiences based on Jordan’s strengths and interests, but mentors like Ms. Fields make sure they’re also challenged in areas they might otherwise avoid. All along Jordan’s learning journey these experiences are added to Jordan’s wallet. Through short daily reflections, integrated and adaptive feedback and intensive reflections at the end of a project, Jordan is populating the beginnings of his lifelong resume. This record of growth and learning holds data-rich examples that are able to connect to career and college opportunities, and, because of the visibility that Jordan’s AI has into the data, it is an effective career mentor that suggests both local and global possibilities for what’s next in Jordan’s journey.
Graduation and Beyond: Giving Back to Anytown
Jordan’s learning journey never reaches a final stop. The world is full of open doors, but for Jordan, one door stands out the most—the one leading back to Anytown.
Some students step into careers right away, drawing on years of apprenticeships and hands-on work in fields like AI engineering, environmental science, and community design. Others take their learning to universities. In both instances, HR and admissions look to the learners’ wallet for evidence of growth, learning and verified skills. These digital records tell a rich story about the learner and are permissioned by the learner. This means that Jordan is empowered to make visible only the experiences that he is most proud of and demonstrates his most relevant and outstanding skills.
Jordan chooses a path that blends both—a social entrepreneurship incubator paired with a modular applied science degree—but with a clear goal in mind: to create economic opportunity in Anytown and ensure the next generation of learners has even more pathways to success.
During his time in the incubator, Jordan refines an idea that has been taking shape for years—a community-based micro-manufacturing hub where local artisans, tradespeople, engineers, and students can design, prototype, and sell sustainable products. They envision a place where young people don’t have to leave their hometown to find opportunity but can build thriving careers right where they are.
AI remains a vital part of their work—analyzing market trends, optimizing production, and connecting local makers with global buyers. But the real impact comes from the human connections—mentors, peers, and community members who share a vision for revitalizing Anytown’s economy.
Jordan’s former teachers, now lifelong mentors, remain just a call or message away, part of a vast learning network that extends beyond the school years. And soon, Jordan will step into their role as a mentor himself—helping the next generation of learners not just dream about the future, but build it.
Anytown once shaped Jordan. Now, Jordan is shaping Anytown.
Conclusion: AI as a Co-Pilot, Humans as the Heart
Anytown, KY, once defined by tradition, now serves as a model for what education can become—a thriving, interconnected ecosystem of agency, creativity, and real-world learning. AI enhances every step and empowers all people to consult a global expert at all times, but teachers, mentors, and community members ensure learning remains deeply human.
Jordan stands on the edge of something new, eyes bright with possibility. The future is not a set path but an open landscape, ready to be explored, shaped, and built.
Learning never ends. It only grows.
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.
The post Kentucky’s Learning Ecosystem in 2040: A Day in the Life appeared first on Getting Smart.
