The future is here, but our education systems are stuck in the past
Loknath DasMay 13, 2019Comments Off on The future is here, but our education systems are stuck in the past0129
he future of work is changing quick. Our planet is in trouble. Education reforms are slow. Is autonomous learning in these wicked times a part of the solution? 21st-century researchers have understood that learning happens best when the learner is self-directed and connections are formed. Authentic learning, situated learning, informal learning, experiential learning, and collaborative inquiry are all examples of this approach in action.
Slowly but surely, there have mushroomed several learning environments in the world that support autonomous learning like the Sudbury Valley School in the United States, Swaraj University in India, or Agora School in the Netherlands, where students decide what to do with their time and learn based on needs rather than through classes or a standard curriculum. There are coaches, mentors, resources, and experiences made available to facilitate the breadth and depth of learning. The key difference is instead of the institution deciding ‘this is what you must learn’ and ‘this is how you must learn it’, the institution is partnering with learners and (g)local communities to meet individual and collective needs through robust and agile structures.
Don’t be afraid—knowledge is being shared, skills are being built, mastery is being achieved, learners are thriving in universities and at work, and learning is continuing beyond schooling and university age. A number of those who have had the freedom to listen to their inner voices and space to experiment and fail have gone on to do great work for a better world.
The future of learning is here. This is it.
Here are four questions or transformations I’ve been thinking about and believe that every student, teacher, educator, parent, administrator, and policy maker should ponder.
1. Why learn?
We all have different reasons to learn, and being human, we are always learning. It’s why machine learning is coupled with artificial intelligence. Among the top motivations to learn something are:
Vocational / career relevance
Gender, class, culture, race, family norms
Natural desire to find meaning / self-fulfillment
Personal relevance / Improve quality of life (e.g. health)
Opportunity to increase capital (social, economic, cultural)
Meeting shared goals
Whichever way you look at it, we learn to meet needs.
If you look into the roots of the word education you’ll find that the use of the word came about in 14th century France to mean ‘childrearing’ and ‘the training of animals’. Around 1610, it came to use in English to mean ‘systematic schooling and training for work’. This remains the active meaning of education today. We go from primary to secondary, then college, and some of us to university before entering the job market. At each stage of this process we are assessed and labelled as a success or failure. Post education, the ultimate benchmark for success and failure in society is usually profit or financial reward.
But the needs of the 21st-century human life are not only related to work and employment and profit making. They are much more nuanced and depend on individual, community, national, and international priorities. We live in an interdependent world after all. Why we must learn is about the same as asking what our current layers of needs are.
The first transformation is questioning why we learn — do we want to go beyond work and profit? Should we be humanists?