The Google of Learning - Part III
12 February 2013
In the original article on this subject (The Google of Learning – Part I), I defined a set of attributes for the online learning university I called the Google of Learning. In a prior article (The Google of Learning – Part II), we talked about content, what content-rich is and what automatic categorization is about.In this article, I explore Personalization – what such an online university system should do for me. We all know of many organizations that subscribe to thousands of e-learning courses but very few of them are actually used. Why? They simply aren’t personalized to the individuals. In other words, there is a library, but that is not of interest to me because it doesn’t serve my needs and interests.
There are a few attributes that come to mind, in no particular order. They are related to the “what, when and how” of the learning elements. In order to demonstrate the points, I take a non-corporate example such as cooking a vegetable lasagna.
i.e., Provide me with the learning elements at the right time
This is now a commonly expected behavior of many applications – that the notifications and learning elements are delivered when you need them, not too much earlier or later. It’s like performing any task – be it mountain climbing or swimming or bicycling, for that matter. Unless the key tips for doing the job are learned closer to the time of the actual event, the tips may well be irrelevant, because we may well forget.
But Just-in-Time also means the ability to replay and re-learn things when we want it. For example, in Mathematics or in Physics, we might want to hear the techniques a couple of times before we actually perform the mathematical task or the physics experiment.
For example, in the case of a vegetable lasagna, can a simple recipe be delivered when I want it (yes – today!); Watch a video of a cook making it (yes, probably!); but real learning happens if I get asked a question: “What would happen if you added coriander to this lasagna sauce?”
i.e., Provide the right learning elements at the right time
We all know of many organizations that subscribe to thousands of e-learning courses but very few of them are actually used. Why? They aren’t personalized to the individuals.
The contextual characteristic goes hand-in-hand with the “Just-in-Time” requirement. What is relevant to me at a particular time differs from what another employee needs at that time. The ability to distinguish that comes from an understanding of the historical perspective of my needs and actions. In many ways, this is similar to the Google search – how it anticipates what you are likely to type.
That is, the system must be smart enough to provide me with the next learning elements based on historical experience. One could stretch this further and ask the system to anticipate the learning elements in the current context – i.e., literally “just-in-time”, but that simply destroys the joy of living and discovery, in my humble opinion – that would be more suitable for robots.
In the vegetable lasagna example, one context might be that I do not have much time. In such a case, I might actually appreciate learning about whether there is a quick and dirty way to make a vegetable lasagna? Or are there other alternate dishes that are easier to cook and have a similar pasta-cake like feel?
Discovery versus informational
i.e., Allow me to discover versus simply provide information
One of the biggest drawbacks of general purpose courseware is that they lack the fun elements of learning. When courseware becomes fun, it becomes learningware. It is well known that discovery fosters learning and that puzzles and games accelerate learning because there are many elements to discover. Even physics, chemistry and biological experiments may be considered as games, in some extreme cases.
It is therefore meaningful to structure learning elements in various puzzle and game-like methods for effective learning; the easier it is to do, the better the Google of Learning will be. In that sense, the Socratic method (asking questions) is supreme for learning effectiveness.
This begs the key question: What kinds of puzzles, games, simulations and other such methods must be possible in the Google of Learning?
In the vegetable lasagna example, I might appreciate learning more about what vegetables can go in a vegetable lasagna, and what not. And more importantly, why!
i.e., Allow me to leverage the right kinds of sensory behaviors for effective learning.
This characteristic is a little tricky and necessarily complex. It is well known that the learning styles of people differ and many people may call themselves visual, auditory, etc. With the advent of the touch-sensitive devices such as iPad and Tablets, the number of possibilities to deliver learning elements compound dramatically.
What then is the right approach? The Google of Learning may itself have to discover the user’s learning style using a combination of methods, and senses, when and where they are applicable. For example, learning how to cook a vegetable lasagna well by reading a recipe is very different from learning from an accomplished cook – learning by watching and doing.
This explains why the iPad is a big hit with the young children – they tend to learn by feeling, touching and tasting, in addition to seeing and hearing. When the opportunity to play with the iPad presents itself, I have never seen ANY kid shy away. Now, that is saying something!
In the case of the veggie lasagna, I might be interested in a learning element that allows me to touch and feel the lasagna – I for one like the top crispy! Do we have ANY devices that allow us to experience that kind of feel?
Probably not! Probably soon to come!