Reengineering Education: Building Towards a New Ecosystem

This is the third article in a series on reengineering education — as a path forward to modern, effective, coherent learning ecosystems.

Thus far in this article series we’ve looked at the significant challenges with the structure of our current educational systems, the motivating factors and global shifts calling for a deep redesign, and why a ‘greenfield’ approach at the systems levels may seem out of reach but critically powerful.

Given the disappointing history of system reform in education, it may seem that such a transformative redesign is not likely. In recent years, what are witnessing instead, is a new ecosystem emerged around the old one.

As mentioned in the previous article, we are seeing a global shift to targeting skills and competencies. A major driver for this is rapidly changing workforce landscape, and the critical skills needed today and in our emerging future.


This is a fundamental pivot for most education systems — including Higher Education where many courses are still organized around discipline knowledge. Yet as Tony Wagner noted so plainly, “Today knowledge is free. It’s like air, it’s like water… There’s no competitive advantage to knowing more than the person next to you. The world doesn’t care what you know. What the world cares about is what you can do with what you know.”

Although we are seeing more and more schools moving in this direction, such a foundational pivot will not come easily, because the organization and structure of learning environments is very different when cultivating competencies versus learning discrete knowledge (Sturgis & Casey, 2018). Organizing schools in discipline-based classes that go for 45 minutes where quizzes and test assess understanding every so often works well when you’re focused on knowledge. But skills and competencies are fundamentally different. They require different contexts, different structures. Cultivating creativity, collaborative problem-solving, self-directed learning, empathy, can largely only happen effectively in rich, complex contexts — not squeezed into the 45-minute math lesson.

That is why in many schools working to make this transition, you see a fundamental restructuring of the learning environment—to leverage richer, deeper, more meaningful and contextualized learning through project-based learning (PBL), competency developmental progressions, and integrated formative assessment (Levine & Patrick, 2019). Such a deep restructuring does not come easily, and for many learning environments can only happen in certain ways or hardly at all due to current constraints and demands.

Education’s Pipeline Problem

Even in private/independent schools such a pivot is often incredibly challenging. This can be summarized simply due to education’s pipeline problem. Despite the global call for such a shift in education, ultimately it is still the fear of entrance exams and perceived entrance requirements to notable colleges and universities that stifles so much change. Each school community is left doing the dance of understanding how to do this kind of shift, while simultaneously educate/sell parents on why this is so important and how the school will still be able to effectively walk both lines — excelling a traditional education ‘basics’ and exams, while also preparing their kids to be highly skilled for our complex world.

While we have begun to see some shifts in higher ed entrance requirements, and more colleges and universities dropping the use of the SAT, it is still early days and definitely not universal enough to give K-12 schools confidence in taking such leaps in their model.

Unfortunately, once again, it’s ultimately the learner that suffers in the end.

An Emerging, Innovative Ecosystem

That could all change in the near future though. Finally we are seeing some top-down, and outside-in change to the education pipeline. Although it seemed employers had gotten used to having to spend several months re-skilling even recent college graduates, it seems the dramatic global shifts in jobs and skills looming large have pushed many into action to solve the skills pathways problem:

  • People often can’t communicate what they know and are able to do in ways that are meaningful to employers;
  • Yet employers, trying to find the right talent to fit their needs, rely on a person’s ability to communicate the value of their skills and experience;
  • Our talent marketplace is fragmented, preventing an individual’s record of learning from being transferable data. And any data that is collected, is siloed; and
  • With rapidly shifting jobs and industries in the next several decades, millions of people will need to navigate their way through re-skilling for workforce placement.

In 2018, a number of major global corporations, foundations, and the U.S. Chamber of Commerce Foundation came together to tackle the BHAG of creating the necessary infrastructure to solve this challenge. They established the T3 Innovation Networkᵀᴹ in order to collectively build an open, public-private data and technology infrastructure for a more equitable future, where emerging technologies and data standards to better align education, workforce, and credentialing data with the needs of the new economy. According to T3,

“This is the data and technology challenge we must solve to create more equitable and effective learning and career pathways for today’s learners and workers.”

Their motto is “skills and competencies are the new currency” and have outlined that the T3 Network will:

  • Define what a competency-based lifelong learner record should be so that all learning counts, no matter where it takes place.
  • Modernize technology and advance data standards to achieve seamless sharing of data throughout a person’s education and career pathway.
  • Empower individuals with a validated record of their skills and competencies in a way that all employers can understand.

Talk about idealized design. To date, the network has grown to more than 500 organizations working together to change the way we provide, access, and use educational and workforce data by using advanced technologies like AI, blockchain, and others to create an open and decentralized public-private data ecosystem.

As a result of this work, rather than hunting down data, job seekers will be able to display the breadth of their experience in a single, comprehensive learning record.

What results is an emergent, integrated ecosystem where the learner owns and drives their own skills development and pathways across a variety of contexts, and across their lifetime — ultimately resulting in many more flexible and supportive pathways to great careers, and employers more effectively able to identify great candidates and support their additional skills training when needed.

What are the Implications for Education?

The implications for education are significant. The T3 initiative has many aspects of this ecosystem already in development, and a number of them will plug right into education — including LERs (Learning and Employment Records), a digital record of learning can document learning wherever it occurs, including at the workplace or through an education experience, credentialing, or military training. LERs are similar to electronic health records (EHRs) and have the potential to improve education and hiring outcomes in the same way that EHRs have improved healthcare delivery.

The LearnX LER profile example

A number of major national and international organizations are running pilots to test how to best bring this vision to life. Some notable ones include LMS Global’s Wellspring Initiative, the IBM Learning Credential Network, and the Colorado Distributed Ecosystem Xchange (CODEX). Such efforts have eluded to the notion of an Internet of Education, modeled off of the Internet of Things idea, where learners are able to experience a ubiquitous and seamless learning pathway across a variety of contexts and environments by integrating and making sense of the learning across that pathway.

The good news for educators is that this emerging ecosystem and infrastructure are very much in alignment with the shift to mastery-based, competency-based learning. LERs are very similar to tools already used in many schools such as their LMS (learning management system) and/or digital portfolio — whereas many of these existing solutions only marginally support competency-based learning, LERs are purposefully built with this competency-based data architecture.

The bad news is arguably for higher ed, the most questionable segment of the pipeline (now being replaced by an ecosystem). The stronger this ecosystem gets, the less clear higher education’s future and relevancy becomes.

Perhaps a reengineered system is indeed possible. But what about K-12 schools? Millions of kids still go to a traditional learning environment, which research has shown has been largely resistant to change. How do we support schools to be a part of this reengineering revolution?

In the next article in this series, we will look at how learning environments can reengineer themselves, and be a critical driver for the future of learning and a major player in this emerging ecosystem.

This was the third article in this series. See also part 1 and part 2.



Learning Futurist. I research, design and create learning technologies, environments and systems. PhD @MIT Media Lab; CEO/Founder of Learning Futures

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Jennifer Groff

Learning Futurist. I research, design and create learning technologies, environments and systems. PhD @MIT Media Lab; CEO/Founder of Learning Futures