1 Introduction
DeepEdu Network
1.1 A Future
Let’s start with a future view of an individual’s education. Many of us have used the internet to educate ourselves with the many media from high-quality videos, papers, articles, podcasts to how-tos being uploaded from numerous individuals, groups, and institutions like never before (60 hours of video are uploaded to youtube.com every minute).
Let us imagine that all of what you have learned online, throughout the entirety of your life, from the hundreds of Youtube videos, Wikipedia articles, Nature papers, and podcasts you’ve read, watched, or listened to, were all added structurally to your knowledge journey, and what if that journey could be consolidated into what we might call a knowledge footprint that could be shared with others? Could this replace static degrees? Or augment them to be more inclusive of a learner’s true knowledge? How might we test such knowledge? Could we even predict and provide the guidance on what an individual should be learning next to best support their knowledge acquisition?
1.2 A Comparison
Now, let’s go back to our current approach to education. Many of us treat knowledge acquisition like a chapter in the individual’s life that is limited to one or more formal places i.e. universities. This is misleading since we accrue knowledge from everywhere and most recently the internet has become a primary source of knowledge acquisition but has gone mostly unaccounted for in terms of recognition (i.e. watching a whole series of Youtube lectures on the Information Theory or Discrete Mathematics goes mostly unnoticed when someone views one’s resume or by simply looking at his or her degree). The current approach makes it much harder for people to switch to working and exploring the domains or professional fields outside of their degree area. Knowing rigorous mathematics and not having a degree in it, is said to be surprising, therefore the current “thumbnail view” of an individual’s knowledge is necessarily inadequate to the new mediums of knowledge acquisition.
The ideas behind this knowledge ecosystem, presents only one of many possible solutions to bringing our education system into modernity. The goal of it would be to promote the long-held idea of the life-long learner. Moving away from the “education chapter”" of an individual’s life to the individual as an evolving learner; learning the necessary skills for what life presents them with today or might tomorrow. It would (combined with traditional education) show us a more accurate depiction of a learner’s knowledge and therefore that of a society’s collective knowledge.
Visualised over time, we could begin to capture a learner’s so-called knowledge journey. Composed of every piece of content they’ve gained knowledge from mapped to the human knowledge graph. Showing how an individual has traversed through the world of human knowledge.
This would also serve as a way for others, who may be on a similar knowledge journey to connect with “their” cohort which may not need to be bound by geography or demography. This could be the start of meetups, study groups, flexible class models and so on.
For those who are looking for a change, they may find different journeys that help them decide what step to take next. You would also be able to connect someone’s occupation to their knowledge journey.
On aggregate, we could begin to cluster similar knowledge journeys through unsupervised learning, which might lead to completely new journeys that others may be inspired to follow.
1.3 Knowledge Ecosystem
In this essay, we will propose a knowledge ecosystem, a new way of approaching education that attempts to build a more accurate depiction of a learner’s true knowledge. It will require significant effort to bring to life but we believe the benefits will outweigh the costs. We will talk about how we can use machine learning, deep learning, in particular, to help create and support a knowledge ecosystem which is made up of the learner’s knowledge footprint, knowledge journeys, and a collective human knowledge graph. We will walk you through some most recent research findings that would enable us to take the space of unstructured educational content on the web and do the following:
classify content to higher level subjects
map content unto the human knowledge graph
test a learner's knowledge of recently viewed educational content through questions and answers, no what matter the subject.
We will also argue that this imagined future is not only desirable for society but something similar is required to ensure individual’s knowledge to be well represented in a time where the pace of change is rapidly speeding up.
Let us not forget, that even software engineering is currently being recreated with machine learning as a key pillar which wasn’t much of a thought 5-10 years ago.
It is going to be tantamount if we have an adaptive system that can represent our current knowledge and also make us predictable to others given the future pushes us to know more than ever and knowing whom to collaborate with to apply such knowledge.
This hypothetical future isn’t just conceptual, most of what we will present to you today is currently feasible due to the most recent advances in machine learning, and in particular deep learning
In the last section of this essay, I will review what has been proposed and also call other researchers, educators, and designers to collaborate on such an ecosystem, even if it is just in part.
*Note: For the purpose of this essay we will talk mostly about digital knowledge acquisition and leave the reader to extend the basics to knowledge obtained elsewhere.