Learning Ecosystems - Rewrite
In this section we will consider a foundational concept in learning: that it happens within a broader ecosystem.
We will look at the features that make up this landscape, as well as the levels of organisation at which we can understand it, and finally take a future facing view as to how this understanding can influence our approach (both from a design and infrastructure perspective).
We will consider the Ecosystem at four levels:
Let’s consider each of these in turn, then look in a bit more depth at the last one, to consider how a Curated Coherent System can help unlock insights from Learning Science.
[1] Learning Ecosystem
We can consider the broadest Learning Ecosystem from an individual learner’s perspective: imagine the path we take to mastery of a new subject. It’s typically through a mixture of experiences, the people we learn with in our communities, the content we are given, and various technologies, all spread out over time.
Maybe we start with curiosity, with ‘how to’ videos, and self driven exploration through books, listening to podcasts, perhaps an online course, then a class. There will be opportunities to put knowledge into practice, to create new meaning and share it. Perhaps trial and error, experimentation and failure will all shape our learning. Our journey may include mentoring, as we take higher stake opportunities to put our learning into practice.
And that’s just to learn one ‘thing’.
Multiply this across all the other subjects that we know, and skills that we have developed, all intersecting and multiplying through our lives.
The journey is non linear, and varied in output: in some areas we achieve mastery, whilst in others we remain lost, confused, or simply playing around. We may move from simple to nuanced, from mechanical to automatic, from ‘beginner’ to ‘expert’.
At the broadest level, our Learning Ecosystem is ‘everything, everywhere’. Experienced alongside ‘everybody else’. All our formal eduction (from primary education to professional seminars), everything we learn as we travel (on the job learning) and the Social Learning that surrounds and permeates all the structured elements and spaces. The Learning Ecosystem includes every subject, every level of complexity, and every form of delivery across time.
This Learning Ecosystem is both unconstrained and unstructured. Partly visible and partly hidden, even to ourselves.
We learn within this cacophonous construct!
There is a skill, called ‘Metacognition’ (which we will discuss separately), that some people develop: it’s a skill in self directed learning, in navigating without ostensible structure. But often, and to many of us, this landscape is wild. Daunting. Unnavigable.
[2] Walled Gardens
We have always had mechanisms and approaches to impose structure and discipline on this landscape: classically that meant someone blazing a trail, with a few apprentices. In more recent centuries we have tried to cultivate order by building Walled Gardens: we define controlled learning experiences around codified bodies of knowledge and skill. We use methodological instructional design processes and, latterly, the insights of scaled data and analytics, edging towards automation.
We have developed the ability ti draw boundaries around knowledge: ‘this’ is a semester-long biology class for 8th grade students, ‘that’ is a day-long teamwork seminar for surgical teams, and so on.
These boundaries help us to manage instructional activities, and to cull out the ‘weeds’ (such as the complexity of other subjects), as well as to foster specific desired and definable outcomes.
Creating Walled Gardens also let us control who enters, we can even charge admission, and verify the quality of ‘produce’ that people leave with (through degree or licences).
Through the formalisation, and codification, of learning as an activity, we have learned to create structures of organisation and understanding.
But Walled Gardens have drawbacks. Because they are highly curated, there is a limited amount of foliage in each: their focus is necessarily narrow, and they tend to be bounded by time and complexity.
Whilst this makes them more manageable, it also means that they’re only optimised at local (episodic) versus ‘neighbourhood’ (or broader) levels. Or to put it another way, they are tidy, quantifiable, and because they have boundaries, they can be owned, and give at least the illusion of control.
But that beauty and tidiness does not reflect the system at a biological level or true Learning Ecosystem level.
We have created an understanding, or perspective, as a level of abstraction.
Each Walled Garden typically treats each visitor (or learner) as a blank slate, and can fail to account for the wealth of contextual information that could have been gleaned from that person’s history or related knowledge.
Many Walled Gardens have controlled admission gates, limited by time or resources, and the boundaries between various Gardens create artificial barriers that force individuals to make sense of the assembly (of the range of learning experiences) independently.
Less formal (Social) learning experiences are often ignored – relegated to the obscured wild outside of the wall, along with performance contexts too, as well as the informal Social Learning Communities within which meaning is created.
Said another way, the Walled Garden approach allows for focused control by reducing learning into controllable chunks. This creates a high level of manageability but at the cost of ecological complexity, authenticity, and broader (‘neighbourhood’) outcomes.
In practice, this means that each learning experience, as well as the aggregate continuum of learning – is less efficient and effective than it could be, and that some learners are unable to access the ‘right’ (for them) learning experiences, in the right ways, at the right times.
[3] Glasshouses
We can take an even narrower view, looking specifically at the subset of the landscape curated and owned by individual Organisations. These share many of the features of the Walled Gardens (indeed, they are walled) but have even narrower focus, and can tend to rely on owned and clearly defined technologies.
They often try to reduce or restrict permeability between what is inside the Glasshouse, and what is outside it. Indeed, they go even further and will often segregate learning by systems of power, seniority, role etc.
The idea is to have a greater diversity and interconnectedness than a Walled Garden, but still with a high level of hierarchical control. In practice, this typically looks like a Learning Management System paired with a few other components like a mobile app, digital grade-book for in-person seminars, and something like a catalogue of skills and credentials.
Sometimes these systems also include some personalisation based on performance, goals, or attributes like occupation or seniority.
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Such systems have value, and most could arguably be called ‘Learning Experience Platforms’, but we can do better.
Such hierarchical learning stacks are still walled, and although their acreage may be larger than a conventional Walled Garden, they’re still constrained in ways that limit their flexibility, authenticity, and strategic impact.
One way to consider it is this: if an etymologist wishes to understand the biosphere bubble of an oak tree, they may put a net under it and shake the tree, or smoke it, to catch all the bugs. These can be counted and categorised. Through observation (who flies in and out) and direct collection, we may come to understand that tree. But dig it up and put it into a sealed Glasshouse, with all those bugs, and the tree will die.
The biosphere bubble of the oak tree is held within a broader ecosystem, acting upon it and being acted upon. We may gain local insight and understanding, but the true ecosystem is broader and interdependent.
Glasshouses are a subset of Walled Gardens, but are included as a structure of understanding in their own right as they are the prevalent feature of our areas of operation and work.
More recently there has been a surge of interest in (and capability around) meta-organisational structures: Communities of Practice, alumni networks, Social Learning approaches at scale, all of which break the panes of the glasshouse. Yet often this exploration is done through the lens of ownership, power, and control.
But let’s move out again from this narrow focus, into an area where we have seen rapid experimentation and insight over the last twenty years or so.
[4] Curated Coherent Ecosystem
There has been investment in, and research around, creating a broader and coherent view of our collective learning systems. This will be something that has the boundless authenticity of the true Learning Ecosystem at it’s broadest level, as well as aspects of the manageability, quantification, and validation of the Walled Gardens. It may even include Glasshouses, but not as totally isolated systems.
We’ve used the term ‘Coherent’ to distinguish these artificial and semi structured environments from the true (unstructured and natural) Learning Ecosystem that it still sits within.
When engineered effectively, a Curated Coherent Ecosystem gives us an increased span of control, more opportunities for optimising outcomes, and greater flexibility in terms of access to, and availability of, learning.
In theory, this lets us monitor, measure, personalise, and optimise learning at a grand scale, not simply within one Organisation, but between many.
Why would we care about this?
Because that is the path that people travel: not in one Organisational system, but between many. Talent flows more readily, removing one aspect of control of the Walled Gardens. If people are not trapped within them, then they flow anyway.
One way to imagine it is like this: today we tend to boundary learning experiences as defined by structure, technology, ownership, sequence, scope. All taking place within a broader natural Learning Ecosystem.
Through the potential of the emergent learning technologies, and with a more holistic mindset, we are able to bring the science of learning to bear, and reimagine our approach.
To create broader, Curated Coherent Ecosystems that still give us the benefit of being quantifiable, mappable, manageable, and yet also provide greater insight and stretch, adaptation and personalisation.
Curated Coherent Ecosystems are semi-natural habitats, through which we try to make the invisible natural Learning Ecosystem more discernible to both individuals and their organisations.
These human-crafted Curated Coherent Ecosystems also try to create discernible connections among their parts (that is, among the typically separate Walled Garden plots), and ideally, to enable meaningful interactions among those components.
Again: these are systems of flow: of talent, stories, knowledge, meaning.
In other words, a Curated Coherent Ecosystem is an assembly of learning experiences that are visible and intentionally interact with one another across the traditional boundaries – across subject areas, time, platforms, and institutions – to improve learning outcomes.
Curated Coherent Ecosystems in Practice
Although it’s impossible to truly know (let alone control) the natural Learning Ecosystem, there’s an attainable midpoint between it and a simple Walled Garden or Glasshouse.
In her prior work, Sae has called this concept the ‘Future Learning Ecosystem,’ but here we call it the Curated Coherent Ecosystem.
Ecosystem because it’s related to the natural, and is more highly interconnected and permeable than a Walled Garden or Glasshouse.
Such a system will make learning more visible, and connected up across time and between modes.
So, connected through out lives, between institutions, platforms, experiences, and across granularity, and to a degree between a range of formal and informal learning experiences.
‘Granularity’ is a term that refers to the level of focus of a learning experience, from a single lesson to a career-enabling assembly of expertise.
Although this system can’t fully reflect the breadth of the full natural Learning Ecosystem, it attempts to approximate that complexity by shifting from a hierarchical approach (where control resides within a single organisation) to a distributed model (where different organisations communicate and interact) – similar to how the internet works.
Control is passed from organisation to organisation over time, similar to how relay racers might pass a baton, although nonlinear.
This concept is enabled through technology, data exchange, and learning engineering processes. Although such advanced technologies aren’t technically required.
Alexander the Great, for instance, enjoyed a sort of ‘artificial learning ecosystem’ thanks to his famous cadre of tutors. But, since we’re not all as wealthy as the ancient king, the rest of us have to rely on AI and inter-organisational systems to fill the gap.
Despite the technical intricacy of this idea, it isn’t some hypothetical dream. These capabilities – including data and standards, interoperable competencies, learning analytics, adaptive algorithms, and learning engineering principles – already exist.
Our collective challenge is not so much technical as it is social and human-centric: How do we shift mindsets to accept this nonhierarchical approach across organisations?
It challenges legacy notions of ownership, permanence, validation, control, and truth.
How do we reliably expand craftsperson-like effects (such as top teachers) from local levels to larger scales? And how do we navigate this (soon to be) ‘new normal’ for learning outside of our old, walled-in methods?