KnowledgeWorks futurists have been looking back at the disruptions from Recombinant Education: Regenerating the Learning Ecosystem to see how the education landscape is looking now, compared to what we thought possible in 2012.
As I scan these reflections, my big takeaway is that the wave of disintermediation that had been restructuring many sectors ended up affecting education less deeply than we had thought it might. Public education systems remain the dominant form of organizing learning, though they have innovated considerably. And, while personalized learning has spread, that has happened largely through traditional schools instead of through the expanded learning ecosystems that the forecast emphasized.
That said, there has been some regeneration of learning ecosystems – what the forecast described as putting together new combinations of learning experiences, resources and supports to meet learners’ needs and achieve systemic objectives. It has simply been uneven. In addition, we now have a more nuanced view of the promises and perils of bringing some technologies and big data into education.
How much change did the disruptions bring?
The last decade brought more interest in, and acceptance of, innovation in education. In working with educators to imagine future possibilities, I noticed this shift. Plus, we are all aware of how the COVID-19 pandemic forced educators’ hands in enabling more digital and hybrid learning. But, as Maria Crabtree highlighted when reviewing the Democratized Startup disruption from the forecast, innovation for innovation’s sake can falter or cause harm. Aligning innovation to shared and intentional visions of the future is necessary to ensure that education stakeholders work together to make education future-ready and supportive of each learner, especially those who come from historically marginalized yet resilient backgrounds.
The last decade has also seen significant movement toward personalized learning, along with attempts among schools and other learning providers to clarify their value propositions. In looking back at the Customizable Value Webs disruption from the forecast, Jason Swanson applauded these attempts to meet and support learners’ needs, interests and goals. Yet he also cautioned, as the forecast had, that we risk perpetuating inequities via systemic fracture or a proliferation of selective, boutique offerings. We need to tend the learning ecosystem more deliberately to make sure that each learner’s needs are met and that learners receive support in thriving in the ways that matter to them.
In looking back at the Shareable Cities disruption from the forecast, Katie King concluded that the public education system has not been engaging with expanded learning landscapes in a meaningful way and that access to community-based learning experiences remains uneven. A few strong examples of community-based learning ecosystems, such as Remake Learning and CommunityShare, exist in the United States. There is also a robust network of STEM learning ecosystems. It promises to be bolstered through the federal CHIPS and Science ACT 2022, which allocated funding for a new K-12 STEM grant program that will aim to scale up best practices. In addition, people around the world are working to foster learning ecosystems. But much of the collaboration between in- and out-of-school-time educators remains up to individuals.
While fully realized learning ecosystems remain uncommon, networks to support differentiation and specialization have spread. As Jason Swanson asserts in reconsidering the De-Institutionalized Production disruption from Recombinant Education, networks of educators are likely to have enduring power. In addition, educators and other stakeholders will have an ongoing need to identify and certify the knowledge, skills and dispositions needed for changing employment and civic sectors. While efforts to develop portraits of a graduate hold promise, our current, dominant forms of assessment and accountability seem inadequate for emerging conditions.
Big data is one tool that can help education stakeholders continue to consider the best systems and structures for supporting learners and for ensuring that learning is happening as intended. As Maria Crabtree argues in her review of the High-Fidelity Living disruption from the forecast, we need to use big data with caution. Education stakeholders need greater insight into the platforms that make automated recommendations based on it, and we need to make sure that big data is used to augment, not replace, human decision-making.
The weight of persistent inequities
It is taking education longer to disintermediate and regenerate than we thought it would when we wrote Recombinant Education. The pull of the status quo is strong. Whatever forms and approaches end up being right for the emerging era, we need to continue to encourage adaptation and informed risk-taking in education systems. We have not done enough to eliminate the persistent inequities that continue to lead to all-too-predictable outcomes for learners from historically marginalized yet resilient sub-groups. Let’s make a renewed effort to ensure that the world of learning described by the forecast becomes a reality for each learner.