K-12 education changed overnight, thanks to Covid-19. “Homeschool” went from outlier term to common experience for many young learners. Millions of others shifted to class at home, via computer software, video lecture, or app, and states wielded data to track attendance and performance of students at public schools.
But for all its suddenness, Covid-19 only accelerated trends that were already building in K-12 education. Even before 2020, teachers were overwhelmed, burned out, and—as of 2018—in perilously short supply. Education software was short-sighted, attempting to retrofit digital technology onto analogue learning styles, and failing to build for the wide range of ways children use—or are distracted by—technology. And K-12 education was no longer seen as a secure ladder to a 4-year college degree and a job, thanks to the crumbling one-size-fits-all higher education myth.
Together, the trends of the 2010s and the effects of Covid-19 have accumulated to an inflection point in K-12 education—one that will determine the wellbeing of students for years to come.
Today, depression and anxiety are skyrocketing among young people. And schools—struggling with teacher retention, remote educational tools, and academic relevance—are increasingly relied on as the first, or only, source of mental health support for young learners.
What are the implications of this inflection point?
When considering the Future of K-12 Education, here are six themes we are digging into:
What follows are three of our own explorations into how a reimagining of education could change the future of learning. Here’s what K-12 might look like.
A human-machine teaching model unbundles education into its two primary capabilities:
With human-machine teaching, artificial intelligence (AI) handles the objective artifacts and knowledge “stuff” of education—things like creating syllabi, building curriculum, and setting proficiency bands. As objective sources of knowledge, the AI is the source of facts, resources, and tests, and can assess the accuracy of student work and track proficiency over time based on academic performance.
Human teachers (now called “Social-Emotional Learning (or SEL) Coaches”) balance the facts and figures of the machines, while mentoring students in the nuanced landscape of critical thinking and social and emotional learning. From the knowledge stack the student is building with AI, the SEL Coach focuses on interpretation, reflection, and application, working with the student toward developing autonomy and healthy collaborative relationships.
The “teachers” of the past will now be freed to move fully into coaching roles, supporting a student’s journey in a deep and long-lasting way. This shift allows students to receive the dual benefits of streamlined, instant education from AI and the transformative influence of a dedicated mentor with which to build a holistic education journey.
As physical location becomes less relevant to education, centers of learning adjust how they attract students, create cohorts, and distinguish themselves from others.
In the learning hub model, schools are organized around key resources or speciality subject areas rather than by location. With hybrid learning options, students can attend from anywhere in the world. Physical campuses are reimagined based on the speciality of a school: an old swimming pool becomes a school for marine biology; a formerly closed library becomes a school of literature.
Whether physical or digital, the “cohorts” at K-12 learning hubs are based on interest, learning style, and proficiency, rather than age and location. Hubs can be selected based on speciality and assessed as often as needed in a student’s pursuit of comprehensive education.
Students have the opportunity to interact with and learn from a wide range of perspectives and talent, gaining a deep appreciation for diversity of background and life experience. As the student moves between learning hubs, they will benefit from brief, intensive collaboration with others—and build a global network of peers and mentors as they go.
Imagine an AI portfolio in the cloud that a student carries with them into every new education center along the way—and eventually college and job applications.
The portfolio begins as a simple AI framework: the student uploads projects they are proud of, whether from school or extracurriculars. The AI visualizes patterns in the work, pulling out key indicators of growth, which evolve with each new uploaded piece of data.
Unlike a report card or LinkedIn profile using only metrics (grades or awards), the Living Portfolio assesses key aptitudes such as autonomy, self-mastery, sociability, growth, curiosity, and craft.
With each new addition, the AI looks for evidence that the student has tried something new, or has built on and deepened existing knowledge. It will also be looking for patterns in what type of projects the student is proud of and interested in to forecast future interests, successes, and aptitudes.
Eventually, the AI can generate “trend reports” for the student (and their SEL Coach) based on growth patterns. And the student can use the Living Portfolio to inform education and career moves based on an extensive analysis of their unique interests and competitive advantage.
From our vantage point in 2020, we are seeing a need—and an opportunity—for education to adapt to young people’s learning needs and desires, well before college. The future of K-12 education will rely on specialized cohorts and collaborative learning, rather than geographic location. It will prioritize social and emotional learning as a core feature of education. And it will understand data as a tool to shape a rich, unique learning path for every student. By providing models for students to acquire skills and develop autonomy, empathy, and adaptability, we can help shape a Future of Education that truly serves the young people of today.