Wednesday, November 12, 2014

Oculus Rift: Freezers, smilers, grippers, swayers, screamers and freak-outs – resistance is futile

Have a look at this video of my sister going apeshit on the DK2 (second Oculus Rift development kit. I’ve been demoing the Oculus Rift to as many people from as many backgrounds in as many places as I could muster. It’s been a hoot to see how universal its appeal has been. ‘Awesome!....Wow!....That’s amazing….’. No matter what age, race, gender or background; people have been astonished by how quickly their brain took them into other worlds.
Resistance is futile
Once you flood their field of view with a screen that has a high refresh rate with rock solid tracking so that your head movements mimic what would happen in that world, along with great audio – you’re there. That new world is your reality. Your old consciousness is replaced by a new one. This is far more than the suspension of disbelief you get, almost immediately, in the cinema. Here, it’s like wrapping the cinema around your whole head, then allowing you to look and move around inside the movie. The sense of ‘presence’, being there, is of a different order.
I’ve had freezers, smilers, grippers, swayers, screamers and plain, scary freak outs.
1. Freezers – stand stock-still, as if struck by the eyes of Medusa, usually men, often terrified
2. Smilers – they’re still but just smile, the smile of a person who has seen enlightenment
3. Grippers – hold onto your hand/arm with a vice like grip, as if letting go would result in death
4. Swayers – sway all ways, like a cheap IKEA wardrobe, they are always on the verge of falling over
5. Screamers – yip, even in a crowded room, they let rip, sometimes out of fear, often just pure joy
6. Freak-outs – goners, they flip out, scream in one continuous loud note, fall over and go crazy
I’ve had Government Ministers, CEOs, CFOs, young, old, extroverts, introverts, men, women, rich and dirt poor. It’s all the same – they’re blown away. What’s been fascination is the distribution of reaction against type of person. So what have I observed so far, from observing over 500 people?
Women have far stronger reactions than men
If we take the seven-point scale, so vividly described, I can certainly say that women are largely distributed towards the swayer, screamer and freak-out end of the spectrum.
Men tend to be freezers and smilers
Men, with a social role that says they shouldn’t show emotion as they tend to fight the induced emotions.
No real difference between young and old
Surprisingly, there seems to be no difference between young children, children, teenagers, young adults, adults and senior citizens, even people in their eighties. Age does not seem to be a determinant of reaction.
Gamers get it, love it, want it
When gamers, usually youngish men, come out of the experience they really want to know when and where they can buy it and at what cost. Having spent a considerable amount of time being immersed in 2D games, they know exactly what this switch to 3D means.

After seeing so many people, so impressed by whet is still just demonstration technology, I’m convinced that this will be huge. The fact that huge players, such as Facebook, Sony and Microsoft have entered the fray, one with a $2 billion acquisition, it’s hard to see this not being a commercial success. It’s not a matter of failure only a matter of how great the success.

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7 traits of online graduates that trump campus colleagues

For three years, I’ve walked up the ramparts into Edinburgh castle, donned an academic gown, plonked a mortar board on my head, then walked down an aisle behind the skirl of the bagpipes, to present degrees to some remarkable students. It was, again, a beautifully staged event, one they’ll remember all of their lives. So will I.
Unique qualities
My speech this year was on what makes them distinct and special. These students had worked for three years to gain their degrees in Architecture, Graphic Design, Illustration and Photography. They came from many lands: India, the Far East, Middle East and Europe. All had completed their degrees online. Astonishingly, they had never met their tutors until this graduation day. Even more remarkable, year on year, these students consistently outperform their campus-based peers.
Far from being inferior to their corresponding campus-based colleagues, the graduates with these degrees are, I believe, superior. As an employer, and to be honest, as just an objective observer, if they were to turn up at my door, I’d consider them a fantastic, talent pool, eminently hireable. Why? There are traits these graduates have that are confirmed by the fact that they completed a hard-won degree in this way – online.
1. Desire to develop
“Two roads diverged in a wood, and I took the one less travelled”. You’ve heard that Robert Frost line before but these students really did make that choice. Unlike most 18 year-old undergraduates who simply progress, often in lock-step, from school to ‘Uni’, every last one of these people came a bit later to the game. They had to make a leap and actively choose to pay for a degree for personal development, promotion prospects, career change or quite simply for the love of their subject. They had the desire to lift themselves out of their normal lives, change direction and chose to make this leap. That’s brave and admirable.
2. Overcame obstacles
This is no ordinary group of graduates but a mixture of smart people who have jobs, children and responsibilities. They had to juggle the demands of their work, children, partners, friends, tutors and support staff to get to their goal. This overcoming of personal obstacles makes them ready to deal with work-life issues that a fresh-faced student couldn’t imagine.2. Persevered
Motivation, and its offspring perseverance, is guaranteed, as they have had to consistently pick themselves up and drive forward against all the odds. This trait is interesting, one essential in client work, where you have to work through problems, criticisms and setbacks; all the things that client-supplier work entails. Creative work has no end – nothing is ever perfect, judgements often subjective. These learners have lived through this for three years, under expert tutelage and pushed themselves, time and time again, towards a series of deadlines and the ultimate goal – their degree. At only 8% , the drop-out rate is wondrous.
3. Project managed
Project work, and these fields are almost wholly a series of projects, require good project management skills. In working through virtual studios to submit work, go through many iterations where online tutors provide efficient and effective constructive feedback and quite simply manage their valuable and limited time, is to manage projects and that, by definition, means project management skills.
5. Communicated
Anyone whose work is largely online will know how sensitive one has to be when body language and other cues are absent. Taking a brief online, delivering project work and assessments online, as well as taking constructive feedback, demands communications skills that are badly needed in our world. These are new skills they had to develop over and above the standards competences of their craft. So much of the work they do, and now do at a higher level, will require strong but sensitive online communications skills. They clearly have this in abundance.
6. Self-aware and self-driven
An often ignored, but well researched aspect of good learning is self-awareness or ‘metacognition’, the ability to become aware, knowledgeable and reflect on your own learning. This, in turn, allows you to efficiently manage your own learning. This is what Higher Education aspires to, giving students the ability to become autonomous learners. Having seen the way these online students learn, the support they receive and the results, you can see how these graduates are brilliant, autonomous learners.
7. Digital doers
A digital degree is in some ways more relevant to 21st century life and work. Work, especially in the jobs where these students excel, is largely digital, even if it does eventually end up as a book cover, poster, product or building. The tools they use are digital, their work is managed digitally and delivery is digital. I’ve seen the work produced by all of these graduates, both 2D and 3D, how else but online – it was well worth the effort.
Note that I haven’t even mentioned competence. I mean competence in terms of their craft, skills and expertise in their chosen fields. This I take as a given. What matters, for me, is what they had to deal with and develop along the way, all of those extra qualities that education should impart and amplify.
Unique degrees
The degrees are awarded by the University of Hertfordshire and delivered by the Interactive Design Institute. What makes these degrees unique is that have three intakes a year, deliver exemplary digital content, provide high quality constructive feedback from tutors through virtual studios, as well as strong pastoral support. All of this led to these degrees and this method of delivery being the first to be approved by the QAA.

I’m not saying that campus graduates don’t have these skills but I do think that the students I meet here, year after year, have a far higher probability of possessing and having developed these qualities. In my eyes, it makes them the sort of people that are a credit to their partners, families, employers and, most of all, to themselves.

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Tuesday, November 04, 2014

Employers see strong potential in MOOCs - new research

Excellent study on ‘The Employer Potential of MOOCs’ with 103 employers surveyed, followed up with deep-dive interviews of 20, on the use of MOOCs for:
1. Recruitment
2. Hiring
3. Personal development
This builds on the Duke study earlier in 2014 that showed employers welcomed MOOCs.
MOOCs for employment
I wasn’t surprised at the relatively low awareness of MOOCs by employers at 31%, as they’ve been marketed primarily at Higher Education and education in general. This is also why I’m non-plussed about the data that shows the majority of MOOCers being highly educated. This is typical of the early adoption profile for new disruptive technology-driven initiatives, Indeed, research from the University of Pennsylvania shows that more than two-thirds of MOOCers identify themselves as employees. Only13% take MOOCs towards a degree but 44% take them to gain specific skills to do their job better, a further 17% take MOOCs to gain specific skills to get a job (Christensen et al., 2013). It should come as no surprise, therefore that the MOOC suppliers have turned towards the professional market for revenues.
1. Recruitment
Most employers still use traditional methods of recruitment but the majority of those surveyed do now use LinkedIn. Once they had heard of MOOCs and understood what they were, they were positive about their use in recruitment (59%). Two sectors in particular were keen on the idea of using MOOCs for hiring; Technology (67%) & Manufacturing (79%). Engineers and developers were of particular interest. The least receptive were Retail and Finance.
2. Hiring
Nearly two-thirds (64%) viewed MOOCs in hiring positively, with those who had heard of MOOCs scoring even higher at 72%. Even in organisations that saw no role for MOOCs in recruiting, 53% saw them positively or very positively for hiring. None of the respondents saw MOOCs very negatively, with only 1 seeing them as negative.
HR staff saw the added value in MOOCs, compared to traditional qualifications as showing the following ‘plus factors’:
  • Motivation
  • Dedication
  • Willingness to develop themselves
  • Doing more for themselves
  • Drive & ambition
Business and Communications organisations were the most positive (87%), with Education (78%), Technology (75%), Public administration (75%), then Manufacturing, Finance and Retail all at 75%. Health organisations were the least receptive at 56%.
3. Personal development
Despite MOOCs being the new kids on the block, 7% were already using MOOCs for personal development, an additional 5% had considered them and 71% could see their organization using them. Those who had heard of MOOCs were universally positive about their use in personal development. Only 3% were negative.
Desired MOOC content fell into three areas:
1. Soft skills in developing management, leadership, dealing with customers, account management
2. Basic computer skills
3. Highly specialized training such as software development
The positive features of MOOC taking were identified as:
  • giving employees the ability to engage in their own development
  • goal setting
  • increase self-motivation
  • refresher course
  • stay up to date
  • advance in their careers
An interesting approach by some, who were already using MOOCs, is to cluster employees into cohorts as they start the MOOC. This increases mutual support, company specific sharing and motivation to finish.
Another big plus for employers was that they could be seen as an ‘employer of choice’ attracting and retaining the best candidates by offering an approach that is contemporary and fits the expectations of younger employees.
The authors note that “the potential for employers’ use of MOOCs is strong”. I’d say, given the relative newness of MOOCs and the lack of awareness among employers of MOOCs, the evidence is overwhelming. The fact that they are free, flexible and accessible is a big plus in times of budget squeezes. But the one statement I found compelling was, that when it comes to personal development, “I don’t think you can have too many options to take and choose from”.

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Saturday, October 18, 2014

7 digital vaccines used in Ebola crisis

Even developed countries, with state-of-the-art facilities such as the US, have experienced infected health workers. On the ground in Africa, rumours abound, one being the ‘salt-cure’ where taking large doses of salt was seen as a cure, resulting in cases of hospitalisation. Traditional animistic views of medicine have also seen people turn away from the treatment they need. There’s even political scare stories around conspiracies by government and foreign powers, where the virus is seen as a deliberate extermination tactic. At it’s most extreme Ebola-denial has taken root in Liberia, where some deny the very existence of the virus. So education, at this point, may be the most important digital vaccine against the spread of the disease.
The advantage of digital apps is their mobile delivery on platforms such as Twitter and Whatsapp, that are already being used in situ. With web-based learning, people can receive their education and training at a distance as well as avoiding potentailly hazardous group sessions. This is not to say that practical learning by doing is unnecessary, only that much of the blend can be delivered online, using images, video and audio. At the moment there is no cure or vaccine, so digital apps and education may be the best vaccines we’ve got.
1. Ebola & Whatsapp
What’s Whatsapp got to do with Ebola? Trusted information provided free by the BBC, a respected brand in Africa, is now available on Whatsapp. Peter Horricks of the BBC is right when he states the simple but obvious fact that “Information will literally save lives.” It’s accessible, it works and it’s free. If you subscribe, you get three pushed messages a day in a number of media including audio and images, as literacy is an issue. Wisely, they are also delivering the messages in English and French, which matters, as some of the countries where the outbreaks are at their worst are French speaking. Indeed, the majority of the bordering countries around the outbreak are French speaking. 
2. Ebola App
The free Ebola Prevention Mobile Application is available on the Android Play store. There is also as an SMS-based application available on CloudSMS. It has four features:
Affected Area Mapping
App shows you your location in relation to affected areas around you on map, And gives you preventive measures to help you prevent this deadly disease
Ebola Hot zone detection
The App tells you from time to time if your current location has been affected by Ebola Virus Disease Outbreak
Preventive Measures
When you are in an Ebola affected area, The App notifies you and gives you preventive measures based on the proximity of your current location to affected areas
Latest Info
Up to date Information on Ebola around you and from all over your region
Another great dimension to this story is the fact that it is being developed in West Africa by Innovative Technologies for Development Foundation (IT4D) a Nigerian Based Not for Profit organization, that was behind, a crowd sourced platform for ordinary people to prevent election rigging in Nigerian Elections.The Ebola app work coordinated by Akinmade Akintoye, CTO of CloudWare Technologies.
3. Podcasts
Audio is the forgotten medium in learning, but in areas where literacy is a problem and you want to deliver authoritative voices on an important topic, it can be a powerful medium. Radio is still an important information channel in Africa. The BBC have already delivered a series of free podcasts, twice a week, debunking the myths along with other topics. So far the podcasts have covered the testimony from Sierra Leonean Ebola survivor, Yusif Koroma, the first person to have survived at the new treatment centre in Freetown's Connaught Hospital. It provides a rare insight into coping with the virus and recovering from it. In another they look at the importance of clear and accurate information which can help minimise the spread of the virus.
4. Ebola MOOC
A more formal approach is taken by the free MOOC Understanding the Ebola Virus and HowYou Can Avoid It, by the Irish organisation Alison. With over 10,000 completions, which can be taken on a range of devices, even mobiles, it provides a valuable educational experience. As Mike Feerick of Alison says "If new information is discovered about Ebola, or how to treat or avoid it, we can instantly relay it to a huge number of learners worldwide." A MOOC is a great way to get formal courses out, as they’re scalable, free and updatable. This is not possible through traditional educational institutions. There’s already a French version, with Arabic in the pipeline.
5. Healthmap app (data & algorithms)
This app was credited with identifying the Ebola outbreak before the WHO. Remarkably, the first signs of fever were tracked in the forested areas of Guinea on March 19. They contacted the WHO, who got their first report many days later. The Boston Children’s Hospital Team behind the app, use algorithms to find and filter thousands of social media, news and government sites. It is this unique use of big data and algorithmic selection that is coming to the fore in disease outbreak reporting and prevention.

6. Ebola Project App (Twitter)
Armil Smailhodzic’s of West Kentucky University developed an app that draws on Twitter data to identify outbreaks and news on Ebola. This app takes a different approach, in that it only tracks Twitter data. Interestingly, they found that, although people in rural Africa are suspicious of Government and outside agencies, they do Tweet. The trick was to filter Tweets from actual sources out from Tweets that just talk about those countries and sources. The app provides maps along with a Twitter feed on prevention and reports.
7. Facebook
Indirectly, all of you Facebookers have contributed to Ebola prevention, as Mark Zuckerberg has donated $25 million to the cause.  The Gates Foundation have chipped in $50 million and Paul Allen another $12 million. Between them, they have contributed more than China, Russia, S America, Australasia and the Middle East put together. This matters, as raw money matters and Governments have been known to make promises, then take the money fromother budgets or not pay up. 
Other informative, authoritative and helpful online resources include Wikipedia, WHO and the CDC. Far from being an uninformative mess, the web provides a remarkably consistent set of resources and tools that play a significant role in prevention and control. What I like about these efforts, is the delivery is often in at least two languages, although it’s all very well to do English and French, local language production may also be necessary. This is already realised on local TV broadcasts, but surely the budget could be found to apply it to the other media, especially podcasts. Sensitivity to literacy issues has also been shown through the use of different media. I’ve taken the MOOC and looked at the other apps. It was quick and easy. This is solid stuff, well designed, well written with appropriate media and a variety of delivery channels, many to mobile. The fact that its scalable, accessible and free, with the ability to update in the light of new information, is a godsend.

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Thursday, October 02, 2014

10 things that algorithms can do that teachers can't

Algorithms trump data
Love them or hate them, you use them and algorithms are here to stay. Algorithmic power drives Google, Facebook, Amazon, Netflix and many other online services, including many more professional services you use, such as communications, finance, health, transport and so on. There is some confusion here, as data is being touted as the next big thing but data is dead in the water if not interpreted and then used to change something. If data is the new oil, algorithmic power is the new turbo-charged engine.
What role for algorithms in learning?
So far the most promising use of educational data is through algorithms. Yet algorithms are faceless and anonymous, hidden from view. As a user, you will usually be unaware of the role they play in your life. Like icebergs, their power lies hidden beneath the surface, with only the user interface visible above the waterline. So let’s make them a little more visible.
It’s like using a satnav in your car. It knows where you’ve come from, where you’re going and how to get you back when you go off course. It may even know when you need a rest and whether you’re comfortable with driving on the motorway or would be best routed through other roads. Satnavs are massively algorithmic, and personalised, as is adaptive, algorithmic teaching. In a learning journey, something similar can be implemented, where ensembles of algorithms can analyse data about the student and content, leading to real-time improvements in both. Note that they can do this in real time and also learn as they go, matching the most appropriate content to the student at any given time. This can lead to quicker course completion, lower drop-out rates, higher attainment and lower costs.
How do they work?
(You can skip this if you have no interest in the background maths.)
Bayes theorem
In 1763 a posthumously published essay by the Reverend Thomas Bayes, presented a single theorem that updated a probability when presented with new evidence. This gives you the ability to continue to update probabilities in the light of new evidence, new predictors and so on, all into a single new probability.
In learning, this allows an algorithmic system to continue to update predictions and recommendations for students and content configuration over time. Interestingly, this often reduces the probability as intuition, through cognitive bias, often exaggerates probabilities, through inadequate analysis.
In addition to the use of Bayesian data analysis is the use of a Bayesian network. This is a model that has ‘known’ and ‘unknown’ probabilities from, say student data, behaviour and performance. The network has nodes with variables (known and unknown) and algorithms can both make decisions and even learn within these networks. It’s basically the application of Bayes theorem to solve complex problems, such as the optimal path for personalised learning. The network will therefore recommend the optimal content going forward.
Enter another important name Andrey Markov, a Russian mathematician who introduced the Markov network. Whereas a Bayesian network is directed and not cyclic, a Markov network is undirected and can be cyclic. Markov models can be used to determine what the learner gets as they attempt a course based on previous behaviours. You may be unaware, for example, that these techniques are already used to present you with a different web page from others from major providers.
Quite separately, Corbett introduced a Bayesian knowledge-tracing algorithm, directly into the learning field, which is more directly associated with data mining, from, for example, learning management systems, which produce large amounts of data about learner behaviour. This can be used to come to a conclusion and make a decision about what is needed next. Note that all of these approaches (and there are many more) are very different from rule-based adaptive systems. The difference between these systems is explained well in this paper by Jim Thompson.
We should note that this field has 250 years of mathematical thinking behind it and has an enormous amount of mathematical complexity. Nevertheless, having born fruit in other online contexts there is every reason to think it will bear fruit in learning. Learning algorithms can, through algorithms. embody evidence-based learning theory, to increase the productivity of the teaching. But what really drives algorithmic, adaptive learning are the advantages they afford to the learner:
1. Gender, race, colour, accent, social background
Algorithms are blind to the sort of social biases (gender, race, colour, age, ethnicity, religion, accent, social background) we commonly see, not only in society through sexism, racism and snobbery but also in teaching where social biases are not uncommon. In education, it is useful to distinguish between subtle and blatant biases, in that the teacher may be perceived to be unbiased and not be aware of their own biases. We know, for example, that gender bias has a strong effect on subject choice and that both gender and race affect teacher feedback. Algorithms can be free of such social biases.
2. Free from cognitive biases
Cognitive biases around ability versus effort, made clear by the likes of Carol Dweck on fixed versus growth mindsets, clearly affect teacher and learner behaviour leading to self-fulfilling predictions on student attainment. Considerable bias in marking and grades has also been evidenced. There may also be ingrained theories and practices that are out of date and now disproven, such as learning styles, that heavily influence teaching. Algorithms, build on sound theory and practice, can, over time, based on actual evidence, try to eliminate such biases.
3. Never get tired, ill, irritable or disillusioned
To teach is human and teacher performance is therefore variable. That is not a criticism of teachers but an observation about human nature and behaviour. Algorithm behaviour is only variable in the sense that it uses variables. Algorithms are at the top of their game (albeit limited) 24/7/365. Of course, one could argue that the affective, emotional side of learning is not always provided by algorithmic learning. That is true but good design can ensure that it is a feature of delivery. Even here, algorithmic techniques around gesture recognition, attention and emotion are being researched and built.
4. Algorithms can do things that brains cannot
Seems like a bold claim, but the number of variables, and sheer formulaic power of an ensemble of algorithms, in many areas, is well beyond the capability of the brain. In addition, the data feeds and data mining opportunities, as well as consistent and correct delivery of content may also be beyond the capability of many teachers. The problem is that most teaching is not one-to-one and therefore those tacit skills are difficult to apply to classes of learners, the norm in educational and training institutions. For the moment there are many tacit skills in teachers that algorithms have not captured. That has to be recognised but that is not a reason for stopping, only a reason for driving forward.
5. Personalises the speed of learning
A group of learners can be represented by a distribution curve. Yet suppose we use a system that is sensitive not just to the bulk of learners but also the leading and trailing tail? Algorithms treat the learners as an individual and personalise the learning journey for that learner. You are, essentially streaming into streams of one. The consequence is the right route for each individual that leads to learning at the speed of ability at any given time. The promise is that learners get through courses quicker.
6. Prevents catastrophic failure & drop-out
Slower learners do not get left behind or suffer catastrophic failure, often in a final summative exam when it is too late, because the system brings them along at a speed that suits them. This can lower drop-out, something that has critical personal, social and financial consequences.
7. Personal reporting
Such systems can produce reports that really do match personal attainment, through personal feedback for the learner than informs their motivation and progress through a course. Rather than standard feedback and remedial loops, the learner can feel as though they really are being tutored, as the feedback is detailed and the learning journey finessed to their personal needs.
8. They learn
Teachers learn, though many would question the efficacy of INSET days or current models of rushed or absent CPD. Algorithmic systems also learn. It is a mathematical feature of machine learning that the system gets better the more students that take the course. We must be careful about exaggerated claims in this area but it is an area of intense research and development.
9. Course improvement
Courses are often repeated, without a great deal of reflection on their weaknesses, even inaccuracies. Many studies of textbooks have shown that they are strewn with mistakes. Adaptive, algorithmic systems can be designed to automatically identify erroneous questions ,weak spots, good resources even optimal paths through a network of learning possibilities. One further possibility is in courses that are semi-porous, where learners use an external resource, say a Wikipedia page or video, and find it useful, thereby raising its ranking in the network of available options for future learners.
10. Massively scalable
Humans are not scalable but algorithms are massively scalable. We have already seen how Google, Facebook, Amazon, Netflix, retailers and many other services use algorithmic power to help you make better decisions and these operate at the level of billions of users. In other words there is no real limit to their scalability. If we can apply that personalisation of learning on a massive scale, education could break free of its heavy cost burden.
The algorithmic, adaptive approach to learning promises to provide things that live teachers cannot and could never deliver. All of the above is being realised through organisations like CogBooks, who have built adaptive, algorithmic systems. This is important, as we cannot get fixated by the oft repeated mantra that face-to-face teaching is always a necessary condition for learning - it is not. Neither should we simply stop at the point of seeing technology as merely something to be used by a teacher in a classroom. It can, but it can be more than this. This approach to technology-based learning could be a massive breakthrough in terms of learning outcomes for millions of learners. It already operates in the learning sphere, through search, perhaps the most profound pedagogic change we have seen in the last century. For me, it is only a matter of when it will be used in more formal learning environments.

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Friday, September 26, 2014

MOOC physics students outperform campus students

Prof Dave Pritchard
This guy teaches both a campus and MOOC course on physics. He is no amateur, a world-class researcher in atomic physics, winner of four major research prizes and three students who won Nobel prizes. When he compared their learning gains, he was astonished at the results. “I had hoped that because they (campus cohort) went to our classes, they would learn a lot more”.
Given the many positive announcements from vendors and negative reactions from academics about MOOCs, there is a remarkable lack of research on learning outcomes. Why this lack of interest? Well one feature of academic research is that it rarely looks at itself, for fear of what it will find. The lecture is the stand-out example. Despite many decades of research showing that lectures, and hterefore the professional job title ‘lecturers’, make little pedagogic sense, most academics will dive into the trenches of irrational indignity in their defence. But reson will prevail and on MOOCs we are now seeing some wonderful research by the likes of MIT and the University of Edinburgh.
Standout study
One standout study by MIT compares campus with MOOC students on the same course. It tackles the key issue; do students learn using MOOCs and how does this compare to the much more expensive campus course? If it is true that students learn more or as much on a MOOC, then the cost differential is such that it makes absolute sense to use MOOCs for these courses. This is a solution to the ballooning costs in HE. Even of the students learn less, there is still a strong argument for using MOOCs in terms of costs. Far too many researchers ignore this key issue – the massive reduction in cost.
Enter this study on Physics. It is a introductory, review course on mechanics with an emphasis on strategic problem solving. It starts with straight line motion through to momentum, mechanical energy, rotational motion, angular momentum and harmonic oscillation. The interesting addition is the content on problem solving that requires several different concepts and approaches leading to a single solution.
1000 students who completed the MOOC (Certificates of Completion) were compared with their similarly scored counterparts on the campus course. The relative progress across all groups was roughly equal across all groups. Identical pre- and post-tests were given to assess learning gains.
What surprised the researchers was that the online students did as well as the campus students, and this is the interesting part – regardless of previous academic experience, whether they had a PhD, Masters, Bachelors or high-school diploma. In fact, the MOOC generated “slightly more conceptual learning than a conventionally taught on-campus course”. But there was a further piece of analysis that was even more surprising. When comparing MOOC students with MIT campus students , even though the campus students had received a lot of extra input and instruction, the relative results were the same with “no evidence of positive, weekly relative improvement of our on-campus students compared with our online students”.

This is the only study of its type that I know but would be pleased to hear about more if they focus on learning outcomes. At last we are beginning to see some sensible research that cuts through both the hype and defensive posturing. Good, level-headed academics and institutions are doing what should have been done years ago – researched the learning and cost outcomes. The researchers are now going on to look at what caused the learning. This is good work and long overdue.

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