A framework for the Science of Learning:
Please watch this video from Jeff Hawkins on how brain Science will change Computing : Jeff Hawkins: How brain science will change computing
In this brilliant talk Jeff Hawkins points out that instead of a Scientific approach, too often we allow intuitively strongly held beliefs and factually incorrect assumptions to become a barrier to real progress, where even though the correct answer is in sight , we allow the cloud of intuitive and obvious beliefs to overwhelm us.
He draws upon the instances of Nicolaus Copernicus ( around 1543) and the Helio-centric solar system, Charles Darwin’s theory of evolution (1859) by natural selection and the relatively recent theory of plate techtonics. first proposed by scientist Alfred Wegener in 1912.
In the context of understanding the brain, he laments the lack of a framework of ideas.
Basic research about the brain mechanisms underlying learning in humans and other species has traditionally taken place in the fields of Neuroscience and Biology; research about how the human mind “computes,” developing and using knowledge, has taken place in Cognitive Science and Psychology; research about how machines learn has taken place in Computer Science and other areas of Engineering; and research about how learning occurs in the classroom has taken place in Education. The Science of Learning is an approach that recognizes the value and importance of cross-fertilization across traditional fields of study, drawing on many different methods and techniques to understand how learning occurs— with the ultimate goal of optimizing learning for all.
I have put together some thoughts that could help build a framework for the science of learning, which may develop over the coming decade. This is still work in progress. And I am sharing a set of thoughts that can help in building a proper framework for learning.
Manifestations of an educational system, not based on supporting evidence:
- Yearly progression through stages of learning, based on age of learner
- Arbitrary restriction on Combination of subjects ( which are rigid silos) at various stages: science with medical and non-medical, commerce, humanities, vocational…..
- Teaching load : papers……credits definition of Carnegie credits
- Outcome based learning……overfitting in case of Machine learning
- From courses to learning objects : structures of learning objects:
The idea of learning objects is to create media content that is:
- interoperable – can “plug-and-play” with any system or delivery tool
- reusable – can be used or adapted for use in multiple learning events
- accessible – can be stored a way that allows for easy searchability
- manageable – can be tracked and updated over time
- Learning journeys or pathways can be created by connecting ‘intelligent learning objects’. While linking learning objects, another interesting concept, the ‘ valence of a learning object’ becomes important. In this world of hyperlinked content, this is very important. Like the rich variety of objects and materials that Chemistry, Materials Science and Biotechnology can create, a huge amount of learning pathways fulfilling the lifelong needs of the entire world’s population.
- Braided learning: a new metaphor for education in the age of Artificial Intelligence: The mismatch between the outcomes of traditional education and the needs of the future is growing rapidly, and many acknowledge that new perspectives are needed. I propose here a new metaphor for learning that is suitable for the future, driven by Artificial Intelligence and similar disruptive technologies. It is now broadly agreed that narrow specialists of the past ( who knew more and more about less and less) must give way to broad knowledge of a polymath. Instead of condemning the “ Jack of all trades but master of none” we are now seeking “ Jill’s of all trades and masters of some”.
- An acronym that all computer professionals appreciate is the API ( application programming interface). In the pharmaceutical industry, API stands for active pharmaceutical ingredient whereas, excipients are pharmacologically inactive substances that are generally used as a carrier of the API in the drug. In the context of education, we could use the acronym API for Active pedagogical ingredient ( pedagogy, androgogy or heutagogy).
- Microsoft researchers began exploring machine teaching principles nearly a decade ago, and those concepts are now working their way into products that help companies build everything from intelligent customer service bots to autonomous systems.
Here is a link to the Science of Learning page from John Hopkins Science of Learning Institute : http://scienceoflearning.jhu.edu/science-to-practice/resources/what-is-the-science-of-learning/