Learning styles, technology-driven teaching, and self-direction are all concepts that anyone interested in education should be familiar with, yet the foundations for their adoption into the classroom, lab or boardroom are more suspect than you might think. Today we look at the three urban legends of learning and what that might mean for education, innovation and beyond.
What kind of learner are you? Are you a visual learner perhaps, where you need information presented in a particular visual style to make sense of it? Maybe you need to problem-solve to learn because that’s the way you’ve been told is best for your education.
Perhaps you are a self-directed learner who is one that, when given the right encouragement and tools, will find your way through the muck to the answers and that others just need to get out of the way. With tools like the web and social media, you have the world’s knowledge at your disposal and have little need to be ‘taught’ that stuff, because its online.
And if you’re a digital native (PDF), this is all second nature to you because you’re able to use multiple technologies simultaneously to solve multiple problems together with ease if given the ability to do so. After all, you’ve had these tools your entire life.
An urban legend, urban myth, urban tale, or contemporary legend, is a form of modern folklore consisting of stories that may or may not have been believed by their tellers to be true.
The authors are quick to point out that there are differences in the way people approach material and prefer to learn, but they also illustrate that there is relatively little evidence to support much of the thinking that surrounds these practices, confusing learning preferences for learning outcomes. I’ve commented on this before, noting that too often learning is conflated with interest and enjoyment when they are different things and if we were really serious about it we might change the way we do a great deal many things in life.
In the paper, the authors debunk — or at least question — the evidence that supports the ‘legends’ of digital natives as a type of learner, the presence of specific learning styles and the need to customize learning to suit such styles of learning, and that of the lone self-educator. In each case, the authors present much evidence to challenge these ideas so as not to take them as truths, but hypotheses that have little support for them in practice.
Science and its inconvenient truths about learning
Science has a funny way of revealing truths that we may find uncomfortable or at least challenge our current orthodoxy.
This reminds me of a terrific quote from the movie Men in Black that illustrates the fragility of ideas in the presence and absence of evidence after one of the characters (played by Will Smith) uncovers that aliens were living on earth (in the film) and is consoled by his partner (played by Tommy Lee Jones) about what is known and unknown in the world:
Fifteen hundred years ago everybody knew the Earth was the center of the universe. Five hundred years ago, everybody knew the Earth was flat, and fifteen minutes ago, you knew that humans were alone on this planet. Imagine what you’ll know tomorrow.
One of the problems with learning is that there is a lot to learn and not all of it is the same in content, format and situational utility. Knowledge is not a ‘thing’ in the way that potatoes, shoes, patio furniture, orange juice, and pencils are things where you can have more or less of it and measure the increase, decrease and change in it over time. But we often treat it that way. Further, knowledge is also highly contextualized and combines elements that are stable, emergent, and transformative in new, complex arrangements simultaneously over time. It is a complex adaptive system.
Learning (in practice) resists simple truths.
It’s why we can be taught something over and again and not get it, while other things get picked up quickly within the same person even if the two ‘things’ seem alike. The conditions in which a person might learn are cultural (e.g., exposure to teaching styles at school, classroom designs, educational systems, availability and exposure to technology, life experiences, emphasis on reflective living/practice within society, time to reflect etc..) and psycho-social/biological (e.g., attention, intelligence, social proximity, literacy, cognitive capacity for information processing, ability to engage with others) so to reduce this complex phenomena to a series of statements about technology, preference and perception is highly problematic.
Science doesn’t have all the answers — far from it — but at least it can test out what is consistent and observable over time and build on that. In doing so, it exposes the responsibility we have as educators and learners.
With great power comes great responsibility…?
Underpinning the urban legends discussed by Kirschner and van Merriënboer and not discussed is the tendency for these legends to create a hands-off learning systems where workplaces, schools, and social systems are freed from the responsibility of shaping learning experiences and opportunities. It effectively reduces institutional knowledge, wisdom and experience to mere variables in a panoply of info-bites treated as all the same.
It also assumes that design doesn’t matter, which undermines the ability to create spaces and places that optimize learning options for people from diverse circumstances.
This mindset frees organizations from having to give time to learning, provide direction (i.e., do their own homework and set the conditions for effective learning and knowledge integration at the outset). It also frees us up from having to choose, to commit to certain ideas and theories, which means some form of discernment, priority setting, and strategy. That requires work up front and leadership and hard, critical, and time-consuming conversations about what is important, what we value in our work, and what we want to see.
When we assume everyone will just find their way we abdicate that responsibility.
Divesting resources and increasing distraction
In my home country of Canada, governments have been doing this with social investment for years where the federal government divests interest to the provinces who divest it to cities and towns who divest it to the public (and private) sector, which means our taxes never go up even if the demands on services do and we find that individual citizens are responsible for more of the process of generating collective benefit without the advantage of any scaled system to support resource allocation and deployment throughout society (which is why we have governments in the first place). It also means our services and supports — mostly — get smaller, lesser in quality, more spread thinly, and lose their impact because there isn’t the scaled allocation of resources to support them.
Learning is the same way. We divest our interests in it and before you know it, we learn less and do less with it because we haven’t the cultural capital, traditions or infrastructure to handle it. Universities turn campus life to an online experience. Secondary schools stop or reduce teaching physical education that involves actual physical activity. Scholarly research is reduced to a Google search. Books are given up as learning vehicles because they take too long to read. It goes on.
It’s not that there are no advantages to some of these ideas in some bites, but that we are transforming the entire enterprise with next to no sense of the systems they are operating in, the mission they are to accomplish, a theory of change that is backed up by evidence, or the will to generate the evidence needed to advise and the resources to engage in the sensemaking needed to evaluate that evidence.
Science, systems and learning
It is time to start some serious conversations about systems, science and learning. It would help if we started getting serious about what we mean when we speak of learning, what theories we use to underpin that language and what evidence we have (or need) to understand what those theories mean in practice and for policy. This starts by asking better questions — and lots of them — about learning and its role in our lives and work.
Design thinking and systems thinking are two thinking tools that can help us find and frame these issues. Mindfulness and its ethics associated with non-judgement, open-mindedness, compassion and curiosity are also key tools. The less we judge, the more open we are to asking good questions about what we are seeing that can lead us to getting better answers rather than getting trapped by urban legends.
Doing this within a systems thinking frame also allows us to see how what we learn and where and how we learn is interconnected to better spot areas of leverage and problems in our assumptions.
This might allow us to make many of our urban legends obsolete instead of allowing them to grow like the alligators that live in the sewers of New York City.