The Future of Present Past

What is the future of m-Learning? Is it truly the ‘shape of things to come’, or merely a temporary fad that will end up in the dustbins of history much like the typewriter, the Sony Walkman, or learning from audio tapes received in postal mail?

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Often overwhelmed by the hype that surrounds mobile learning, in the onslaught of hurray-optimism from its fervent proponents, this question gets frequently overlooked. The answer ostensibly is so self-evident as to not merit any serious consideration at all: m-Learning is the future, and the future is m-Learning – period. Or so its theoreticians would have you believe.

As a genuine heretic at heart, I cannot help but smile at this notion. In 10 to 15 years, I sincerely doubt we will still be talking about mobile learning at all! Personally, I think mobile learning is a strictly temporary phenomenon, with a built-in expiration date that is already hovering over the horizon.

First of all, mobile learning is too caught up with (and in) the characteristics of an intrinsically fleeting form of technology to last beyond a couple of decades. This is the fate of all device-centric movements: if you align yourself with a piece (or even a single class) of machinery as the flagship of your theory, don’t be surprised if that ship becomes outdated by the time it manages to sail into the theatre of your battle. There is a reason we still use the term e-Learning: we did not try to build its theory around a single device, and did not attempt designate it ‘desktop PC learning’ or ‘laptop learning’. The more narrowly you identify your approach with a single class of devices, the more vulnerable you make it to inevitable obsolescence.

But the myopic drive to associate mobile learning with cell phones and tablets (and even with specific types thereof!) is not the only reason behind its inevitable demise. Computing has been following an uninterrupted trend towards mobility and miniaturization since its very invention. While Moore’s law may have its own problems, and may (arguably) show signs of deceleration, it is not about to disappear at least within the next decade – and this is considering only current technologies, without taking into account alternate approaches (e.g. quantum computing) coming up in the pipes.

On one hand, this means that with the continued decrease in size and increase in function, within 10 years the vast majority of personal computing devices will all be considered ‘mobile’, hence rendering the adjective moot. We do not talk about ‘mobile’ as opposed to ‘stationary’ reading, even though to a monk of the 12th century imagining a codex that does not require two people to transport it from one room to another would have seemed revolutionary.

On the other hand, and just as importantly, our very notion of learning is changing as well. The field of artificial intelligence is about to explode (if it has not already) and it will fundamentally change how we approach learning and teaching. Within 15 years, I believe, AI will encompass all types of sophisticated computing machines designed for complex human interaction, and will set a radically new paradigm of human-machine interaction, very much including learning as well.

In this new paradigm, the role of the teacher will largely be relegated to the functions of a) instructional designer programmer, and b) AI coordinator manager.* The traditional function of ‘facilitation’ per se will be largely taken over by AIs; human agency will be concentrated on developing and programming AIs with a distinct educational bent, and supervising, coordinating, and managing their operations from a distance.

AIs, in turn, will serve as complex diagnostic and responsive teaching machines. The very first time a human being initiates his/her very first interaction with such an AI (probably shortly after birth), the AI will start developing and compiling a learner profile, which will include biochemical and biophysical information (based on e.g. blood tests, ECG, DNA, and a whole slew of other biological, chemical, and physical tests and characteristics of the learner). With every subsequent interaction, this profile will become more detailed and complex. Every instance of interaction between any AI and the learner will expand upon this profile. How you solved the problem of fitting the right plastic cube into the right slot at age 2 will be recorded and stored in this profile, just as your manners and style of writing at age 10, your way of understanding differential equations at age 16, your way of processing auditory versus visual information at age 25, and so forth and so on – throughout the learner’s entire life.

This profile will be the learner’s digital learner ID (DLID), carried on – nay, IN – the learner’s body in the form of a chip/storage device. It will record his/her learning preferences, learning styles and approaches to problems, and a whole slew of other information, all of which will continue to expand, change, and refine the learner’s DLID in precision with each successive interaction between the learner and any educational AI s/he interacts with at any point in his/her life.

This will result in a continuously ongoing iterative process that combines needs analysis, design and delivery, and evaluation in a single endless loop, but on a strictly personalized, customized, individual basis. AIs will have a myriad of routines and subroutines – branches of learning, if you will – for every learning event, topic, problem, etc., for every single individual. Every time the learner ‘logs in’ on an event, the AI will automatically calibrate the learner’s current learning experience to meet his/her preferences, strengths and weaknesses – his/her DLID, essentially; and every learning experience, in turn, will enrich this DLID with new, additional information, noting changes as well as constants, further refining and customising the learner’s profile.

This will maximize the effectiveness of each and every learning experience for each and every learner. Printed academic transcripts, dusty diplomas, their painfully reductionist digital copies, and awkward and vulnerable physical portfolios will all be replaced by these complex DLIDs. If a student wants to enroll in a post-secondary (or any other) ‘course’, at any level, the AI will automatically identify whether the student has the pre-requisites based on his/her DLID, and consequently grant him/her access either to the selected learning intervention, or to a remedial intervention that prepares the student to his/her desired learning event.

Diplomas, degrees, and issues arising from differences between different educational institutions and different standards will be a distant memory of the past. So will be formally graduated and standardized progression from elementary through secondary to post-secondary education. If a learner’s DLID shows that s/he has all the requirements to engage in a post-secondary physics course at age 10, s/he will be granted access to it at age 10. Conversely, if a learner’s DLID shows that s/he only possesses the profile for a kindergarten activity at age 25, that is what s/he will be directed to.

Learning as an activity tethered to isolated locations/institutions, and fragmented into specific lots across time and space, will cease to exist. Schools as institutions will disappear. Every human being will be able to engage in a learning event at any time, any place, and of any duration; a skill-acquisition activity that you started on Friday at 10:00AM at age 5 may be completed on a Sunday at 11:00PM at age 27. Your progress and results will be stored, mastery assessed and recorded, lapses and lack of maintenance due to disuse diagnosed, tracked, and addressed immediately.

Every learner will earn credits for every learning activity (regardless of its nature or content) so there will be no ‘unnecessary’ or ‘unused’ learning, merely different paths that you are more – or less qualified – for engaging and pursuing. Human beings will be rewarded for all learning – indeed, for all problem resolution – in the form of credits.

‘Communal processing’ will replace both today’s volunteer activities and ‘normal’ employment/work. Much like today one can hook his/her computer that is not used into a network to process data (see e.g. SETI@home), every human being will have their learning activities (essentially, problem solving and creation) integrated into a supernetwork (I would call it COGNET), and will earn credits (both in the educational AND in the financial sense) with the completion of every activity.

Since much of the work traditionally performed by human beings will be accomplished by machines, members of society will earn their ‘keep’ – their financial resources, their welfare if you will – based on how much cognitive processing they log in on COGNET, and based on the relative complexity and difficulty of their processing output. The more you log in and the more complex problems you solve, the better you will become at it, and the more resources (free time, access to stuff, etc.) you will earn. Geniuses will be ‘millionaires’ by age 10; people who are less disciplined, who spend more time lazing outside COGNET, or whose intellectual processing capacities are limited, will be the underclass.

Accordingly, mobile learning will become a redundant phase not only because almost all computing technology will be considered ‘mobile’, but also because the new and all-pervasive modality of learning will be fundamentally different from the atomized, instanced learning that characterizes mobile learning today, just as much as it will be different from the tethered and location-bound institutionalized learning of semi-yesterday. Learning will not be an activity confined as a part of life separate from working; it will be life itself.

In a sense, therefore, mobile learning will fail by succeeding. Consider this: up until a few decades ago, science fiction was regarded as an esoteric genre by most, largely the domain of lonely adolescents, pimple-faced miscreants, and intellectual wierdos (or so went the common wisdom), something that no (or at least very few) serious minds were willing to openly embrace. Today, it has become not merely mainstream, but – indeed – THE defining genre of our socio-cultural construction dialogue, amply evidenced by its almost exclusive dominance of both the box office and the bookshelves. The notion of learning on the go anywhere and anytime is prone to change in a similar manner: instead of being a unique and distinct brand, it will be the only brand; instead of anytime anywhere, it will be learning everytime, everywhere. Yet shedding its centuries-old baggage will also transform it into a phenomenon qualitatively different from its own roots, including from the most fundamental characteristics of our contemporary notion of mobile learning.

So, my friends, get your processors ready; it’s gonna be a wild ride!

*Portions of this post incorporate in whole an earlier message from author, which were posted in the Unit 6 forum (Computer-based technologies) of Athabasca University’s Master of Education course, MDDE620: Technology in Education and Training on 6 July 2015.