The Future Of Mobile Learning

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Last week Amit and I made a small presentation to the Mobile Learning MOOC (MobiMOOC) about the possibilities in the future of mobile learning. We’d like to share what we presented because it encapsulates technologies that will impact/affect the future of mobile learning and learning in general, readers of this blog will probably find it of special interest.

You can find our presentation here. Our presentation identified four key technology areas that will impact learning in the future:

  • Big data, huge quantities of user generated content and sophisticated curation.
  • Ubiquitous and pervasive computing.
  • Social (human) and Machine networks.
  • The Semantic Web and Intelligent Agents.

It goes without saying the future of learning is mobile. In fact, the future of computing itself is mobile. As computing size approaches zero, a whole world of possibilities emerge.

In my candid opinion, there is no such thing as big data, there is only an increased volume of data. While the web buzzes with talk of ‘big data’, it only indicates the huge amount of data that is now being generated by human and machine activity and resident in the cloud. What is important is that we are now building enough computing and storage power ‘in the cloud’ to process and make sense of this data – sophisticated data mining. Our interface to this world of data will likely be contained within our mobile devices.

User generated content is exploding on the internet, YouTube and Flickr are great examples of that. The gateway to this profusion has been mobile devices enabled with photo/video cameras and internet connections allowing quick sharing with the world-at-large. This trend has only contributed more to the deluge of data. Being able to leverage this user generated content for a variety of learning application is something learning designers will need to master soon. Already, academia and the corporate workspaces are encouraging students and employees to generate content that is used to document knowledge. The gateway to such a system both inward and outward is almost certain to be a mobile personal computation device carried on the person. (what smart phones are today, and all phones will be). Given this generation is a continuous and ongoing process it leads to the development of a huge amount of content that can be used – subsequently incorporated into courseware or reference material.

I’ve mentioned the physical size of computing approaching zero and what that means. Quite simply, it’d mean ubiquitous and pervasive computing – the ability to put a computer in anything one might see fit. And it’s not just a computer, but internet connected, IP assigned addressable computer, that can send/receive data to/from the cloud. This will probably represent a paradigm shift in how we view computers, computing and the very nature of connectedness.

This being able to put a tiny computer that is capable of connections in everyday objects will require a new sort of network (see IPv6) that these millions of computers will connect, we will gradually see the emergence of the true ‘internet of things’ and machine to machine networks. These will be in addition to the networks humans build using what can only be termed as ‘social technology’. Human networks will continue to use technology for greater connectedness (the social human need), over time I think we will learn to make sense of our worlds using a combination of human and machine networks.

The semantic web is developing all along, and the ‘making sense’ that I spoke of earlier will probably depend a lot on the emergence of well defined ontologies for data exchange between machines. I’ve written about this before, and it will remain a key theme for the future of mobile learning and technology. I’m still quite clueless about how it might be leveraged for learning, yet am certain someone will definitely come up with an innovative way to do it.

We already live in an era where our interaction with technology can be simplified and governed by technology agents (Siri is a good example). As artificial intelligence develops further, we will probably be seeing more of these in daily life. Almost in all instances, they will assist us in identifying trends, making decisions, and providing data based on the context of your location, activity, time of day, etc. I seriously doubt they will take over our lives; however we will trust them more and more to make sense of large volumes of data.

There are a whole bunch of examples and links in the presentation for each area that we spoke about

You’ll notice that while I describe the broad themes in this post, the presentation is structured to show technological impacts in the distant future, the near future and those making impacts starting now and extending into the immediate future.

Please don’t forget to take all this with a pinch of salt, because technology evolves at a fantastic rate. We often see technologies fail before mass-market acceptance, and those elements of technology never make it into our hands. The success of a technology depends on its mainstream adoption, which in turn depends on a lot of factors not necessarily linked to the quality or utility of the technology. It is also likely that we may have missed some elements of mobile technology that is still emerging. However, given the current state of technology, we think the trends discussed stand a good chance of coming to mass-market fruition and will definitely impact learning.

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