Is no curriculum, no classrooms, no teachers, and no assessment (in short, No Education) the future of learning?

Four transformations from 20th century education to 21st century learning

The 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:

1. Vocational / career relevance
2. Gender, class, culture, race, family norms