Artificial intelligence - instant gratification but what do we learn?

Photo by Joakim Honkasalo on Unsplash

Artificial intelligence (AI) has become the default centre of attention in education this year with enthusiasts telling us to accept and even welcome it into our teaching and learning whilst sceptics are busy looking for tools that can detect AI-generated texts, videos and images in order to combat the expected wave of cheating. The tech giants are already on the case with Microsoft planning to embed ChatGPT and now Google has announced a launch of their version of the tool. There's big money to be made out there and lots of data to be harvested and distilled. 

Cheating in exams is probably the least of our worries. This eternal battle reminds me of the wonderful Spy versus spy cartoons in Mad magazine where two spies, identical except for one being dressed in white, the other in black, engage in a never-ending tit-for-tat battle using all sorts of secret weapons. Every new secret weapon prompts an even better anti secret-weapon weapon in a parody of the cold war antics of the USA and the USSR. In recent years we've had waves of plagiarism detection tools countered with essay mills where you can buy off-the-shelf essays or pay someong else to write it all for you. Interestingly the biggest vendor of plagiarism detection software Turnitin has announced its own AI-detection software. And so it goes on. It's time to break this war of attrition by changing to other forms of assessment based on personal reflection, interviews and projects. Many teachers have already made this transition. 

A more balanced response to AI in education appears in an article on Slate, You’re Not Going to Like How Colleges Respond to ChatGPT. The authors see the spy versus spy scenario as one orchestrated by the tech companies so that educators will feel forced to invest in AI detection software (you can bet your life that this will need to be updated regularly and create a never-ending income stream).

Whenever fears of technology-aided plagiarism appear in schools and universities, it’s a safe bet that technology-aided plagiarism detection will be pitched as a solution. Almost concurrent with the wave of articles on the chatbot was a slew of articles touting solutions. A Princeton student spent a chunk of his winter break creating GPTZero, an app he claims can detect whether a given piece of writing was done by a human or ChatGPT. Plagiarism-detection leviathan Turnitin is touting its own “A.I.” solutions to confront the burgeoning issue. Even instructors across the country are reportedly catching students submitting essays written by the chatbot. OpenAI itself, in a moment of selling us all both the affliction and the cure, has proposed plagiarism detection or even some form of watermark to notify people of when the tech has been used. Unfortunately, the tool released is, according to the company, “not fully reliable.”

Once again it's a case of whether we should develop new technologies just because we can and then let the world deal with the consequences. Who benefits? Certainly not educators or students but then again nobody asked us.

However, one thing we can be sure of is this: OpenAI is not thinking about educators very much. It has decided to “disrupt” and walk away, with no afterthought about what schools should do with the program.

The texts produced by AI are often impressive - articles with references, instant summaries, creative writing, poetry, programming - but the shortcomings are becoming clearer as people experiment more deeply. Basically it reformulates what it finds on the sources it trawls, including some that would not be considered reliable, and sometimes it simply makes a guess at an answer, as Maha Bali describes in How *Not* To Be Overly Impressed with #ChatGPT. These flaws make it untrustworthy at present but I suspect it will improve very rapidly.

Yes, it's impressive to get an instant blog post or essay but what do you learn from that? Isn't learning all about doing this ourselves: researching other sources, working out connections, following a train of thought and putting it all together in a coherant text? The instant answer teaches you nothing. There are no magic shortcuts to learning as we should have realised by now after so many commercially driven hype cycles around things like smartboards, iPads, MOOCs, virtual reality and so on. The learning process is complex and takes place in your head, irrespective of the gadgets you have available. The Slate article continues:

To outsource idea generation to an A.I. machine is to miss the constant revision that reflection causes in our thinking. Not to mention that the biggest difference between a calculator and ChatGPT is that a calculator doesn’t have to check its answer against the loud chaos of everything toxic and hateful that has ever been posted on the internet.

AI will soon be able to write fact and fiction, compose music, produce art works, write programs, design clothes, automatically translate from one language to another and much more. When all this has been automated what is left for us to do apart from endless consumption? We need to learn how to use AI for our benefit but focus more on our own creative energy and the value of learning for our own development. We must not simply accept technology just because it's there. 

It’s a failure of imagination to think that we must learn to live with an A.I. writing tool just because it was built.

AI is developing fast and I'm struggling to make some kind of sense of it and how it affects education. Please view this post as muddled work in progress.

Artificial intelligence - opening Pandora's box

"Pandora’s Box" (CC BY 2.0) by Mycael

It has been a while since I last wrote here due to life events taking precedence. Meanwhile the world of educational technology has been buzzing about the advent of the AI application ChatGPT. This is a more user-friendly upgrade of GPT that I wrote about back in October, The end of the essay? Ask ChatGPT a question and you'll get a very plausible and often accurate answer, in most languages. There are lots of interesting reviews out there and we're all trying to digest the potential consequences this will have for education. For example have a look at a post by Tony Bates, Playing with ChatGPT: now I’m scared (a little), where he analyses the tool's answers to questions in his own field of expertise. 

Of course the main topic for the media has been how students can use this to cheat without the risk of running foul of anti-plagiarism tools. Why do we always assume the worst in our students? I've seen calls to return to the exam hall with paper and pencil examinations (though some institutions have never left this scenario) and speculation on tools that can detect AI-generated text (it takes a thief to catch a thief I suppose). But these are futile attempts to stop the tide and it is vital that educators and decision makers keep up with the development of AI and find strategies to use it wisely. There are several good articles about how to use ChatGPT in your teaching, for example Ryan Watkins', Update Your Course Syllabus for chatGPT. Tips include asking students to fact check and improve on the tool's answers to questions and using other media for assignments such as mindmaps, podcasts and video at least until AI can generate even those!).

There are of course limitations with ChatGPT. According to a presentation by Torrey Trust, ChatGPT and education, the tool is not actually connected to the internet and cannot access texts and information from later than 2021. I assume that this is a temporary inconvenience and we can count on more advanced versions and competitors very soon. In addition the tool collects data from all its users that can then be shared with third parties (surprise surprise!). So before using this with students you'll bneed to discuss the privacy implications, as well as the implications for their own learning.

Just because the tool produces plausible and accurate answers to a lot of questions it can also pick up biases from texts it analyses and in some cases can provide false or misleading information, even backed up by non-existent sources, as shown in an article by Lucas Ropek in Gizmodo, How to Talk to ChatGPT, the Uncanny New AI-Fueled Chatbot That Makes a Lot of Stuff Up.

However, there is a bizarre exception to the program’s automated smoothness. The part where things get slightly uncanny (and, in this writer’s opinion, more creepy) is when the chatbot makes mistakes. The reason this is so weird is that instead of just short-circuiting or spitting out an automated response like “Error” or “Please Try Again” when it doesn’t know something, ChatGPT actually makes something up. Often this thing is a rough approximation of the correct answer. This is weird because it’s also what humans tend to do, conversationally. Unsure of how to answer a particular question or address a topic, most people try to bullshit their way out of it. Well, so does ChatGPT.

In some cases it will admit its limitations, for example when asked to make predictions, summarise texts or make personal reflections, but many writers have found it worryingly good at providing flawed answers. The danger is that we trust AI too much and assume it knows everything. Using it in say health care, social work and employment would seem to be asking for trouble.

Then we have the thorny issue of copyright. Who owns the texts produced by AI and how can they be cited? Does the person who wrote the prompt have copyright, or the programmers who devised the tool, or the owner of the company? Jonathan Binns (The impact of AI on copyright law) asked ChatGPT what the impact of AI would be on UK copyright law and got this answer:

It is difficult to predict the exact impact that AI will have on copyright law in the UK. However, it is likely that the use of AI in creative industries, such as music and art, will raise questions about the ownership of works created by AI. There may also be discussions about whether AI itself can hold copyrights for works it creates. It is possible that the UK government will need to update copyright laws to address these issues.

AI is also making a big impact on creative industries like music. ChatGPT and other tools can write song lyrics to order in seconds in the style of any famous artist. Music generator tools are already producing songs, jingles and soundtracks and although they are hardly masterpieces they certainly threaten a lot of people's livelihoods, as described in an article in Billboard, What Happens to Songwriters When AI Can Generate Music? and in a video by Rick Beato, How Auto-Tune DESTROYED Popular Music. The point in Beato's video is that since so much popular music over the last 20 years has been increasingly computer-generated the jump to AI may not be noticed.

All this raises so many questions about the future of education and work and we are only glimpsing the start of AI's development. We have opened Pandora's box and, as in the myth, it will be impossible to close it again. There are many exciting uses but the opportunities for manipulating between fact and fiction are clearly enormous to the point that it may soon be impossible to distinguish between them. What happens when we can't trust anything? I am not confident that we are able to handle the genie we have created.

Every move you make - the rise of bossware

"What are you looking at?" (CC BY 2.0) by Jonas B

Every step you take, every move you make, big data is watching you. An unexpected consequence of the post-pandemic rise in home working seems to be intelligent software known as bossware installed on an employee's computer. This tracks your digital activities during the working day: every click, every link, document, e-mail, message. The software analyses this and awards productivity scores and other stats that bosses can used to assess your performance. This is described in detail in an article from The Guardian, ‘Bossware is coming for almost every worker’: the software you might not realize is watching you.

Each employee gets a daily “productivity score” out of 100 which is sent to a team’s manager and the worker, who will also see their ranking among their peers. The score is calculated by a proprietary algorithm that weighs and aggregates the volume of a worker’s input across all the company’s business applications – email, phones, messaging apps, databases.

In some organisations this is connected to a webcam and microphone so that everything you do is tracked and unproductive behaviour will be reported. In many cases the employees are unaware they even have this software on their devices. This is not a dystopian vision of the future but something that is happening right now in many organisations and is expected to grow. 

There are so many issues with this that it is hard to know where to start. We often place great trust in allegedly intelligent software and assume that it offers hard facts based on solid data with no human judgements involved. Productivity software analyses your level of digital activity but not the quality of what you do. If you send lots of pointless e-mails every hour, write a few simple documents and click on approved web sites regularly you can appear to be a model employee. If you spend time thinking and researching background information before you write you may get black marks. Activity and noise do not equal efficiency and hard work.

The same applies in education where we are increasingly using learning analytics to track and analyse how students study, looking especially at their activity levels in discussion threads and how they progress through recorded lectures, quizzes and calculations. Once again the most active students are not necessarily the ones who learn best. But this simple analysis of working and learning can be very dangerous since it misses the need for silent reflection and rewards spontaneous and visible (or audible) activity.

An article by John Warner in Inside Higher Ed, Utter madness, reflects on the use of bossware on writers and academics who often have long periods of digital inactivity as they try to write an article or prepare a lesson. Warner also brings up the threat of this simplistic approach in assessing students.

Lest we think this is some kind of corporate dystopian nightmare, let me direct your attention to the learning management systems now ubiquitous on college campuses and the way they are often used to track student activity. If young workers are accepting of this kind of surveillance by their employers, it’s only because it’s been normalized much earlier in their lives. And I would also ask how many of you are required to input all of the minutiae of your scholarly lives into some kind of “faculty activity system” and consider how much time this requires, as well as the toll it takes on one’s spirit as the information disappears into the digital ether, never to be heard from again.

The use of remote proctoring software to monitor students doing exams online has raised many alarms around the world. Even if the aim of preventing cheating may be reasonable the cost in terms of intrusion and breach of integrity is too high and many students and teachers have raised strong objections to its use. Video and audio data of your home, your behaviour and appearance is stored by corporations as is every click and keystroke you make during the exam. 

This is a long way from the visions we had of online education and a digital society. We hoped for a connected world allowing global collaboration and free access to information and learning. But sadly the trend today is that digitalisation is leading to more control and suveillance and that there is no opt-out clause. That's why I find it very hard to be enthusiastic about big data, artificial intelligence, learning analytics and suchlike. I see some positive uses but the risk of misuse outweighs them by a long way. Once you start analysing work and life in such a way you destroy any traces of humanity and community. If that type of efficiency is what organisations want then they should probably just employ robots.

A decade of broken dreams and big business

"Rêves brisés (Broken dreams)" (CC BY-NC 2.0) by Claude Robillard

I strongly urge you to read Audrey Watters' review of the past decade in educational technology, The 100 Worst Ed-Tech Debacles of the Decade. It's a catalogue of the buzzwords, hypes, deceptions and snake-oil solutions that have made the educational technology headlines in recent years. Even if the focus is on the US edtech industry, most of the solutions will be familiar to educators everywhere. I have long admired Watters' courage over the years, daring to criticise the hypocrisy and cynicism of the tech industry when most of us were singing its praises and falling for the alluring tales of disruption and free education for all. The past decade has been a journey of broken dreams.

Number one in Watters' list of debacles is anti-school shooter software, the result of the USA's insane attitude to guns and mass shootings. School shootings are now so commonplace that an entire industry has developed to "protect" schools, identify shooters and alert the police. This involves increasingly sophisticated surveillance technology with enormous amounts of student data being gathered by corporations. This industry is hardly visible anywhere else in the world but is a desperately sad indictment of modern society.

Many of the phenomena described in the article fall under the following loose categories (though they are all of course interrelated):

Surveillance

Data is indeed the new oil and corporations are now able to refine the raw data of clicks, location tracking, preferences and interaction into business opportunities. Edtech software including learning management systems gather enormous amounts of student data and this can now be monetised. The prospect of using, for example, Amazon's voice assistant Alexa at school should set off alarm bells. Learning analytics seems to be largely focused on tracking and surveillance and all that data has a high commercial value. Instructure's proposed sale to equity firm Thoma Bravo for $2 billion would seem to confirm the potential value of student data. Plagiarism detection tool Turnitin has amassed a vast pool of student assignments that they can sell. The list goes on. Despite attempts, at least in Europe, to tighten laws on the exploitation of personal data we still happily accept those pesky terms and conditions when the pop up on our screens.

Educational mythology 

The Silicon Valley narrative that the traditional education system is inadequate to educate students for the 21st century has been very persuasive. As a result, we hear that the students (so-called digital natives) are driving the change and are already using technology to "hack" the system and learn on their own terms (some may be doing this but claims are highly exaggerated). This disruption narrative claims that edtech is the way forward to meeting the demands of this new generation of students who will be working in jobs that do not exist today (this has always been true - parents in the early 20th century could never have guessed that their children would become car designers, pilots or astronauts). The industry has capitalised on the FOMA (fear of missing out) factor among educational leaders with claims that MOOCs are the future of higher education and that companies like Udacity will become the Uber of education. Many institutions have been easily persuaded to make enormous investments to ensure they are seen as embracing the opportunities of the digital revolution. Sadly there have been unscrupulous actors running a whole industry of fake online universites and fake degrees. Watters' list is full of examples of this narrative and the reckless claims to disrupt education that didn't quite deliver.

Many of the leading names in the tech industry have of course invested in philanthropic initiatives that Watters calls venture philanthropy. There are surely benefits in this but inevitably there is a business case even for philanthropy:

These philanthropists’ visions for the future of education and education technology mirror their own businesses: the child will be the customer. The child’s data will be mined. The child’s education will be personalized.

Free. 

If it's free there's a catch, though even if you pay for it there's still generally a catch. Your data is the price you pay.

...if you’re using a piece of technology that’s free, it’s likely that your personal data is being sold to advertisers or at the very least hoarded as a potential asset (and used, for example, to develop some sort of feature or algorithm).

Free tools are used very successfully by millions of teachers to enhance their teaching, but there is always the danger that the company goes bust or gets bought by a larger company who then try to monetise it. One example of this was the social network platform Ning that was extremely popular among educators in the first half of the decade but was then bought and put behind a paywall.

Miracle cures

There have been so many headlines about how a particular device or method will disrupt/revolutionise education. From MOOCs to clickers to smartboards to virtual reality. They all have merits when applied well but the inflated expectations and sensational headlines have lead to many extremely expensive investments (and nice profits for some) and many shattered dreams.

In addition there are examples of more bizarre methods to monitor students in the form of skin response bracelets, brainwave headbands and the compulsory use of  fitness trackers for campus students (providing of course lots of useful personal data!). These are often based on quasi-scientific theories and rolled out with convincing optimism.

Flops

The list is full of ambitious and hyped solutions that belly-flopped: for example One laptop per child, Google Glass (and many other Google services that have died during the decade) and Amazon Inspire. Flops will always happen in an innovative market so there is now real surprise here but maybe the point is how the hype takes over the narrative and we all get swept along with it.

So where are we heading as we move into the twenties? I can't see the commercialisation of education going away any time soon, rather an intensification of the process from both industry and politics. Free and open education is still possible but the educators must own the platforms and the users must give informed consent to their data being stored and know that they can always demand their data back (a cornerstone of the European GDPR legislation). Maybe it's time to move to open source solutions and revive the idea behind platforms like Wikiuniversity and Wikieducator - they may have been clunky but they were open and non-commercial. Above all we need to be much more aware of media hype and attractive but misleading generalisations. Question everything and learn how and when to switch off.

Smart campus, but who owns the smartness?

"Pynchon Park (2016) - Dominique Gonzalez" (CC BY 2.0) by pedrosimoes7

Learning analytics allows sophisticated analysis of students' activity in the university's various platforms and tools, allowing teachers and administrators to see who is falling behind, what they are having problems with and what types of activities give the best results. At the same time the campus is becoming smarter with the use of IoT (internet of things) technology and facial recognition, allowing automatic attendance registration, smart monitoring of room occupancy, car parks, heating control and even rubbish bins. Add artificial intelligence into this mix and we have the smart campus of tomorrow.

An example of the smart campus movement is Arizona State University, described in an article in EdTech magazine, How Arizona State University Built a Smart Campus. They have developed a campus app that has become almost default for students and staff allowing them to check schedules, grades, exam times, services, cafeteria menus, parking options, room availability and so on. Buildings and other spaces are constantly monitored and data collected about occupation and movement. This enables more efficient use of energy and provides vital data for planning new facilities and changes to existing ones. Major IT companies are pitching sophisticated solutions for campus management as seen in this film.



It's all extremely impressive but I have a couple of reservations.

Firstly, although the smart campus is very convenient and gives students and staff personalised and attractive services at their fingertips, you get the feeling that your every move is registered and stored. If all the data is aggregated all my movements, activities, purchases, studies, test results, hours spent in different spaces and travel will be available for possible analysis. Examples of facial recognition and ubiquitous CCTV monitoring seen in some Chinese schools and colleges in recent months can mean that there is simply nowhere to hide on campus. Your mobile is both the key to all campus facilities and a tracking device. The university therefore has extremely detailed data on everyone on campus and it is virtually impossible to opt out or even switch off. If that data is in the hands of a third party what guarantees are there that they will not sell that data or find ways of profiting from it? There are of course enormous advantages in smart campus solutions but questions about the use of personal data and informed consent must be foremost.

My second reservation is the focus on the physical campus and what sort of smart services all the off-campus online students will be able to access. These students are seldom mentioned in the smart campus narrative and I would like to see new learning spaces that bridge the gap between traditional campus students and online students. There seem to be few limits on the level of investment in the physical campus whilst the online spaces are in comparison extremely low-budget operations.

MOOCs on campus

"PC Tables, Saltire Centre, Glasgow Caled" (CC BY-NC-ND 2.0) by jisc_infonet

Even if the concept of a MOOC is now so blurred and diverse that the acronym has become almost redundant, new twists to the story keep emerging. Instead of challenging the traditional education system as originally proclaimed, the main MOOC platforms are now becoming increasingly mainstream focusing on complementing the traditional system and gaining a foothold in the corporate training market. The news that Coursera are now offering a concept called Coursera for campus seems to represent the closing of the circle as MOOCs become part of the traditional campus set-up.

The idea is that a university can sign up and gain access to Coursera's library of over 3,600 courses and then integrate them into the curriculum. The MOOCs can be used as course modules or complementary material and they can be integrated into the institution's learning management system, allowing teachers to add their own assignments and course material to the MOOC. The institution can then add examination and award credits for the MOOC. The ability to use a MOOC as a kind of multimedia course book and then add on-site seminars, assignments and assessment is very attractive though of course it comes at a price and is far from the notion of MOOCs as examples of open educational resources. A Spotify for MOOCs basically.

The advantages to the institution are several. Courses and teachers from high profile universities can be integrated into the curriculum and then local support and adaptation to local circumstances can be included as added value. I like this idea and have previously posted about examples of this in more open varieties of MOOCs. The Coursera MOOCs can even be offered as lifelong learning options to a wider learner community, also with added local focus or even with support in the local language (I haven't seen examples of this yet but it would certainly be extremely useful). Institutions can also use the Coursera library to offer a wider choice of optional courses to their students. Customers have also access to Coursera's learning analytics tools to track student engagement and completion rates, though on the other hand this also gives Coursera access to your student data, thus increasing the already vast amount of student data they can process.

If this development means that universities and colleges can widen their curriculum and offer course material from high status universities but at the same time offering extra tuition in the local language, discussing how to apply the course topics to local circumstances, then I like the idea. It's a long way from the original concept of a MOOC and much more about a traditional content delivery concept but if there is the flexibility to add local relevance then it will be interesting to see how it develops. The main concern for me is who owns all the data and how will it be used.

Here's a publicity film from Coursera about their campus solution for Manipal Academy of Higher Education in India.

Learning analytics - is there an off switch?

CC0 Public domain on pxhere

Returning to the theme of learning analytics, I wonder if there will be any way of opting out from being tracked and coached. The potential of learning analytics is in tracking a student's progress, suggesting resources, offering extra practice and constant feedback on assignments as well as monitoring performance. The vision is to have a personal tutor by your side round the clock and provide your human tutor with alerts if your are struggling in some way. The trouble with this is that sometimes you need to be able to switch off the surveillance and just practice in peace. You seldom perform to the best of your ability if you know someone (or something) is watching you.

I recommend you read an article by John Warner in Inside Higher Ed, The Problems of Real-Time Feedback in Teaching Writing. He objects to real-time AI feedback on students' writing on the grounds that it does more harm than good. Too much feedback too often can destroy the creative process and simply leading the students to write in order to satisfy the system. There is a time for providing feedback and there must also be time for trial and error and experimentation without the feeling that you are being observed and assessed.

For example, when learning to play the guitar, it’s useful to have some periods of real-time feedback where a teacher may be able to correct a flaw like a bad hand position, but you also need to go lock yourself in your room and practice, likely making a bunch of unpleasant noises in the process. Imagine trying to do this while being constantly reminded that your noises really are unpleasant.

We all need our own quiet spaces to concentrate, experiment, test, reflect and discuss: a play room, sandbox, hideaway, tree house. You don't want anyone to see or hear your embarrassing mistakes and it's best that many early attempts are discarded and lost without trace. This is one reason why students seldom post in the forums of our learning management systems. They only post when required and soon learn that everything they write there is in the university's system and may be used in evidence against them. As a result they create their own closed communities to discuss coursework, away from all risk of assessment. 

We need to use AI/learning analytics wisely and make sure we allow students the right to escape when they need to. The risk is that we destroy creativity by offering too much support and personalisation.

Writing is thinking, writing is thinking, writing is thinking, and sometimes when we’re working on our thinking, we have to be left alone.

Is edtech simply automating tradition?

CC BY-SA Some rights reserved by ISAPUT on Wikimedia Commons

For a few years the internet was an exciting new space where we thought we could build a better world through innovation, borderless collaboration and a culture of sharing. Today big business reigns supreme and technology is being used for control, surveillance and commercial gain. After several years of speculation and experimentation we are now beginning to see how analytics and artificial intelligence are going to be used in education. As governments become increasingly concerned with accountability, profitability and competition, technology is feeding this drive with statistics.

A post by Mike Crowley, Google, ISTE, and the Death of EdTech, reflects on the recent ISTE conference and sees worrying tendencies that today's edtech industry is increasingly about control rather than creativity. Technology is being used to make traditional practice more efficient rather than fostering real learning.

All week, the ISTE Expo Hall gushed with predictions that Artificial Intelligence will automate the traditional classroom. Auto-grading is now a thing. Marketeers touted emerging tools to help students study smarter, by enabling them to memorise more information faster. Ultimately, though, the Big News, like Google Classroom, is the proliferation of software that allows teachers to monitor and keep students on-task. The lofty ambitions for education were summed up thus. Make tradition more efficient. Stop bored students from cheating on mindless, low-level assessments. Deliver content like Windows 98 is the next big thing. New tools. Old thinking. Systems, not learners.

The tyranny of tradition is extremely hard to escape from. The traditional educational paradigm of learning facts that can be easily tested and categorised is a perfect fit for the smart systems of today. We can use analytics and AI to provide the statistical illusion that students have achieved the learning objectives we set them. But technology can and should be able to do so much more and that's why Crowley states:

Make no mistake about it. EdTech as we currently know it is dead, it’s over. We should retire the phrase right now. If education is to be the target of an industry that has grown increasingly obsessed with standardization, control, automation, and delivery efficiencies, then we must opt out.
Related to this is the use of automated grading of assignments that has been under development for several years now. This involves computer analysis of a written assignment to check for coherence, argumentation, linguistic style, grammar and fluency. An article on NPR, More States Opting To 'Robo-Grade' Student Essays By Computer, examines recent experience of automated grading at several US universities. Many educators are impressed by the accuracy of these tools, often giving similar grades to human examiners and if the computer is unsure it flags for teacher assessment. The potential savings are obvious and very attractive to cash-strapped institutions.

Several states including Utah and Ohio already use automated grading on their standardized tests. Cyndee Carter, assessment development coordinator for the Utah State Board of Education, says the state began very cautiously, at first making sure every machine-graded essay was also read by a real person. But she says the computer scoring has proven "spot-on" and Utah now lets machines be the sole judge of the vast majority of essays. In about 20 percent of cases, she says, when the computer detects something unusual, or is on the fence between two scores, it flags an essay for human review. But all in all, she says the automated scoring system has been a boon for the state, not only for the cost savings, but also because it enables teachers to get test results back in minutes rather than months.

Impressive indeed, but there will always be ways to hack the system and already there are examples of text generators that produce nonsensical texts that satisfy the grading system's preferences. This type of cat-and-mouse game has nothing to do with learning. When the only purpose of writing an assignment is to get a grade then people will simply do whatever it takes to get that grade as easily as possible. If the assignment has real meaning to more people than simply an examiner (or a robot) then the game element disappears. We need to develop methods of assessing student ability based on the impact of their projects on real people. Maybe traditional for-teacher's-eyes-only assignments are the problem.

One clear use for automated grading systems is to help the students improve their writing skills. The system can provide repeated formative assessment opportunities, helping students to improve the coherence and style of their assignments. They can submit several times during the writing process, something that no teacher could ever have time to deal with, and then submit the final version to the teacher for grading. However a more collaborative approach already used by many teachers is to encourage peer assessment with fellow students providing feedback during the writing process. This method benefits everyone and the students can learn a lot from being actively involved in the assessment process.

The real purpose of technology should be to facilitate human collaboration and learning. I love using digital tools to facilitate creative and collaborative activities and that's where educational technology should be focused. The use of big data in education, however is worrying and we need to be very careful not to be tempted into handing over control of our students to big business.

Terms and conditions apply - what went wrong?

Terms and Conditions by Nick Youngson CC BY-SA 3.0 Alpha Stock Images

"If it's free then you are the product". Yes, we've heard that many times over the years but somehow chose not to take it so seriously. We merrily approved all the terms and conditions that popped up when we signed up for all of our social media networks and tools and kept on clicking. We basically gave Google, Facebook, Twitter and the rest of them the freedom to gather enormous amounts of personal data and sell it to anyone willing to pay for it, whatever their motives. Now with Facebook in the eye of a storm of outrage and Google in similar trouble, we can see what the cost of "free" actually is. Basically most commercial online media that are "free" are also in the business of tracking and selling data to advertisers (read more in Doc Searls Weblog, Facebook’s Cambridge Analytica problems are nothing compared to what’s coming for all of online publishing). At the same time we are so hooked on "free" that it's hard to break away. Try to imagine your digital life without all these commercial giants, especially Google. I'm trying to limit the damage at present by switching platforms (e.g. moving from Chrome to Vivaldi and searching with DuckDuckGo), going through all the security settings and so on, but it feels like I'm hopelessly enmeshed.

So what about education in an age where free has been compromised? So many communities of educators and students are built around Facebook, Google, Twitter etc. Do we close them down and move elsewhere and if so where to go? Some institutions offer safe platforms for staff and student blogs and wikis, as Tony Bates describes in his post Our responsibility in protecting institutional, student and personal data in online learning. There are also still plenty of open source wiki sites and other non-profit services but they lack the glitter and stickiness of the commercial solutions. Many users will no doubt set up new alternative networks and platforms but they involve considerable administration and development and will cost time and resources. Some will try to limit the damage and continue to use the old favourites but being more aware of their limitations (e.g. Siva Vaidhyanathan's article in the New York Times, Don’t Delete Facebook. Do Something About It). Whatever happens we need to revise our practices and attitudes.

One interesting aspect of this mess is raised in an excellent post by Autumn Caines, Platform Literacy in a Time of Mass Gaslighting – Or – That Time I Asked Cambridge Analytica for My Data. She proposes platform literacy as a key skill for the future; the awareness of the power that platforms have and the ability to limit the amount of data that platforms can acquire from you. Personalisation it seems has been the pied piper leading the children to their doom.

Personalization in learning and advertising is enabled by platforms. Just as there are deep problems with personalization of advertising, we will find it is multiplied by tens of thousands when we apply it to learning. Utopian views that ignore the problems of platforms and personalization are only going to end up looking like what we are seeing now with Facebook and CA. The thing that I can’t shake is this feeling that the platform itself is the thing that we need more people to understand.

Platforms gather data and data is the new oil. That crude data can now be distilled and some of the applications are proving to be deadly, threatening democracy itself. Maybe we are now beginning to realise what that often misused term "disruption" really means? Even our learning management systems are powerful platforms that gather data on students' interactions, access to material and performance. This can be used to enhance learning as many experts in learning analytics have demonstrated, but what if the data escapes into the wrong hands? We need to become more aware of the power of platforms and what we can and cannot share on them. 

What if we were really transparent with the data that learning systems have about students and focused on making the student aware of the existence of their data and emphasised their ownership over their data? What if we taught data literacy to the student with their own data?

Innovating pedagogy - new report

CC BY Some rights reserved by Open University (Photo Chris Valentine)

In case you haven't already found it, I'd like to point you in the direction of the latest edition of the Open University's excellent report, Innovating pedagogy 2017. This is the sixth edition of the report and the aim is to provide a pedagogical balance to the annual NMC Horizon reports on trends in educational technology. Each year they identify and describe ten emerging pedagogies that are of course influenced by technology but are relevant to all forms of teaching and learning. Each trend is described with theoretical background and practical examples and, as in the NMC Horizon reports, there are numerous links to reports, articles and examples of these ideas in practice.

This year's report raises the following phenomena:

• Spaced learning - dividing class time into short modules of input, recall and application with social activity breaks in between. 
• Learners making science - citizen science activities gathering data and actively analysing.
• Open textbooks - teachers, and even students, writing and continuously updating course literature openly on the net.
• Navigating post-truth societies - strategies for dealing with false news, biased reporting and propaganda.
• Intergroup empathy - methods for fostering inter-cultural understanding and diversity.
• Immersive learning - using simulations, virtual and augmented reality in education to provide realistic practical experience of situations that are hard to replicate physically.
• Student-led analytics - letting students access their own data to help them set objectives for and monitor their studies.
• Big-data inquiry - learning to harness the power of big data and applying it to solve real problems.
• Learning with internal values - greater freedom for learners to choose own focus areas within the wider curriculum, thus adding internal motivation.
• Humanistic knowledge-building communities - combining the need for learner autonomy, creativity and self-direction with the the need to build the collective knowledge of the community.

What all of these have in common is developing a more rounded and holistic view of education and trying to integrate the sometimes conflicting perspectives of learning for employment, learning for personal development and learning to be an active citizen and part of a wider community. Today there is an increasing focus, especially from governments and industry, on learning for employment and many of the most popular uses of technology in education have been related to this. We use technology to monitor learner progress, test, set grades and facilitate knowledge transfer through recorded lectures and online resources.

The trends in this report offer a human balance to the the current obsession with tangible results and league tables. They stress participation, internal motivation, balance and active involvement. Instead of looking at how universities and schools can use big data and learning analytics to monitor students we should see how students can make use of this data to help them learn. We all need to learn how to harness the power of the data revolution instead of being passive victims. We need to learn to question and filter the information torrent in an informed and scientific way instead of feeling helpless and overwhelmed. Basically we all (teachers and students) need to relearn how to learn in today's new media landscape.

The report is fascinating reading but, like all such reports, is simply an indication of possible future developments. In a year's time things could look very different and who knows what new phenomenon can come out of the blue. What the last few years have taught us all is that predicting the future has never been so difficult. If you want to read more about this report have a look at these two: Martin Weller's blog post, Innovating Pedagogy 2017 and an article in 

Times Higher Education, Post-truth teaching: coming to a lecture theatre near you?

Reference
Ferguson, R., Barzilai, S., Ben-Zvi, D., Chinn, C.A., Herodotou, C., Hod, Y., Kali, Y., Kukulska-Hulme, A., Kupermintz, H., McAndrew, P., Rienties, B., Sagy, O., Scanlon, E., Sharples, M., Weller, M., & Whitelock, D. (2017). Innovating Pedagogy 2017: Open University Innovation Report 6. Milton Keynes: The Open University, UK.

Roadmaps for online learning

"Navigator" (CC BY 2.0) by Tabsinthe

There is no shortage of trend reports and guides on the future of online learning but sadly too few institutions who are using them as a base for their strategic planning. The challenges ahead for higher education are complex and require new approaches and innovative solutions in a sector that is so deeply rooted in tradition and history. This tradition coupled with the high level of respect and credibility that university qualifications still command makes it all too easy to think that a business-as-usual strategy is the safest course to plot.

The Canadian educational technology support organisation Contact North published earlier this year an excellent trend overview entitled The future of online learning. This describes the increased complexity of today's educational landscape with new actors, models and credentials jostling for attention and challenging the traditional setup. At the same time universities are under increasing financial and regulatory pressure to be more efficient, result-oriented and accountable with a wider than ever range of students with high expectations in terms of personalisation, flexibility and work relevance. The report examines what this means for higher education institutions and notes that a new ecosystem is developing to cater for a much more diversified and demanding target group. The gold standard of the university degree will be challenged and augmented by new types of credentials including micro-credentials like badges. Short and flexible programmes with strong links to workplace experience will allow many to combine work and study without the need to spend several years on campus. This will demand new methods for assessment, recognition of prior learning and the development of new forms of quality assurance. This doesn't mean that the traditional university model is going to be overthrown but it does mean that there will be more alternative paths to learning.

Source: UOC eLearn Center, Witthaus, Padilla, Guàrdia and Campillo (2016, p.6). 

An example of how to use these trends and feed them into a university's strategic development is seen in the results of the FUTURA (Future of University Teaching: Update and a Roadmap for Advancement) project. This describes the process of applying trends in online learning to teaching practice and university strategy at Universitat Oberta de Catalunya (UOC); read more in an article from the UOC's eLearn Center, IDEAS: a new framework for next generation pedagogy.

FUTURA identified pedagogical trends and innovations globally, and analysed related institutional examples. The FUTURA report proposes a framework for describing current and emerging practice in teaching in online higher education under the acronym, IDEAS.

The IDEAS model (explained in the image on the right) provides a sound basis for re-examining pedagogical development at any university and reinforces most of the conclusions of Contact North's analysis. Everything described here is already taking place but mostly in a fragmented way through projects or innovative faculty with few institutions developing a comprehensive strategy. I suspect that the prime movers are distance education universities since their focus is online but campus universities ignore this at their peril.

These alternative paths are already attracting an increasing number of school leavers who are becoming less likely to head straight to university campus. A new article in eCampus News, Could these 3 burgeoning nontraditional pathways be a boon for traditional institutions? describes how many American students are trying one or a combination of the following before considering campus:

• a gap year or two with internships and self-directed learning
• online studies via open courses
• getting hard skills by practical experience

“College costs keep growing and student debt is over one trillion dollars,” explained Richard Wang, CEO at Coding Dojo in a statement. “These alternative education options can help keep student debt under control, while providing individuals with real-world experience and skills employers are looking for in job candidates.”

Trends are becoming reality though not always in a revolutionary and disruptive way. New opportunities and pathways emerge often largely unnoticed until they reach a level that cannot be ignored. I have previously likened these changes to a glacier; the landscape is being radically changed but the changes and the pace of change are not always evident to those who are standing on the glacier itself. Only when the glacier melts will we see the full extent of the change. Those institutions who realise they are on a glacier and start changing now will be able to meet the challenges ahead. The most dangerous option is business as usual, thinking that the ground under our feet is solid.

Teaching with robots

"Electric Neuron" (CC BY-NC-ND 2.0) by philosophy_rebel

The potential of big data and learning analytics to radically change our approach to learning and education is moving from the trend reports to practical applications. An article in the Wall Street Journal, Imagine Discovering That Your Teaching Assistant Really Is a Robot, describes how a class at Georgia Tech got prompt and useful feedback in discussion forums from a teaching assistant called Jill Watson and noone realised that she was a robot until the professor revealed the truth at the end of the course. Students post an awful lot of questions and ideas during a course and even if teaching assistants are hired to help with feedback it's hard to keep up. Most student posts require fairly simple responses, often about deadlines, assignment criteria or asking for confirmation that they are on the right track. The motivational effect of getting prompt replies is well documented and today's artificial intelligence can provide this round the clock.

“Our TAs are getting bogged down answering routine questions,” said Mr. Goel, noting that students in the class typically post 10,000 messages a semester.
Mr. Goel estimates that within a year, Ms. Watson will be able to answer 40% of all the students’ questions, freeing the humans to tackle more complex technical or philosophical inquiries such as, “How do you define intelligence?”

Jill had been rigorously programmed by analysing questions and answers in course forums and was programmed only to respond to questions that "she" had a 97% certainty of an appropriate answer. More advanced questions were left to humans. The only hint that Jill wasn't quite like other teaching assistants was that she was so prompt in answering and never seemed to sleep. The students were all positive about the machine responses and many were convinced that Jill was a highly competent PhD student. The robot assistant was convincing though it would be interesting if students would have been equally positive if they had known from the start that they would have a robot facilitator. Of course we prefer human assistance and we all have experience of less advanced and extremely limited chatbots on commercial websites but the alternative for the students in this case could be much less feedback and longer waits for information.

Artificial intelligence is already taking over many mundane and time-consuming tasks in education. Automated feedback on written assignments has also been tested with positive results (see my post from a couple of years ago) and much more advanced applications are in the pipeline as learning analytics matures. Machine translation and speech-text-speech applications are improving and becoming more reliable. Add these elements to the MOOC model and we get scaleable, personalised, collaborative and flexible education where teacher and machine support complement each other This doesn't mean that we'll all learn solely through digital devices and it doesn't replace face-to-face meetings and interaction (arguments I only hear from tech skeptics). It means that we can widen the reach of education and offer alternative paths, integrating education with work and enabling people to learn without uprooting themselves to a university campus (unless you really want to do that). 

MOOCs going mainstream? Reflections from eMOOCs 2016

University of Graz

Social learning, secure online examination, new pathways to credentials, unbundling and the application of learning analytics. These are some of the main themes of lat week's eMOOCs 2016 conference in Graz, Austria, that I attended together with MOOC practitioners mostly from Europe but some from further afield. Earlier conferences attracted many policy makers and managers but now the focus was very much on sharing experience and moving MOOCs to a new level. The overall tone of the conference was that MOOCs are beginning to mature and the earlier criticisms of instructivist pedagogy, low completion rates and hyped glossiness are now being addressed. Many MOOCs now offer virtual proctoring to enable MOOCs for credits, micro-credentials though badges are improving learner motivation and the focus is now on social learning rather than self-study. The business models of the main consortia are built around a freemium model with only access to course material available for free and a host of layered value-added options available at a price.

The conference featured two inspirational keynote speakers, Anant Agarwal (Professor at MIT and CEO of EdX) and Pierre Dillenbourg (Professor at EPFL Lausanne), and the rest of the time was devoted to practitioner experience, research findings and workshops. Agarwal gave an infectiously enthusiastic presentation of the EdX consortium's progress and future direction, stressing the need for MOOCs to break the sonic barrier of credits. This demands of course increased accountability. MOOCs should be as good if not better than traditional courses and this is achieved by innovative solutions, virtual proctored exams, social learning, project teams, tutoring and teacher grading in combination with peer assessment and guided studies that have become a hallmark of the genre. Verified certificates have increased course completion rates to around 60% whilst more advanced verification and course packages have given even higher rates.

Conference begins

Offering MOOCs as a stepping stone to campus studies is already in place, notably the Global Freshman Academy initiative between EdX and Arizona State University. This involves replacing the freshman year with MOOCs with open admissions. When you sit the course exams you only pay for credit if you pass. Admission to campus studies from year two is available for those who pass their year one courses and pay for the credits, what Agarwal referred to as inverted admissions. The big question here is whether more universities will accept this concept and give learners access to year two of a degree programme on the basis of credits gained from other universities' MOOCs, even with proctored examination. A similar concept is that of micromasters, bundles of MOOCs with tutoring, project work and proctored examination, which are being developed in cooperation with major companies (see also for example Coursera's specializations concept and  project-based courses). These micromasters can be counted as half of a regular masters degree thus allowing learners to complete their masters degree at half the normal price. The partner companies are on board but it remains to be seen whether this approach will gain acceptance throughout the higher education sector and widespread employer recognition.

The frequently voiced concerns about the credibility and security of online examinations may well be addressed by the practice of virtual proctoring through companies such as Software secure and Proctor U. These companies have centres where virtual proctors monitor thousands of online examinations using webcam, microphone and screen surveillance. Student computers are locked down and only allow the examination application and the webcam will register any activities like checking a mobile under the table. The software registers all exceptional behaviour and movements both on screen and in the room and these can later be investigated if there is any suspicion of cheating. This is already in practice in MOOCs for credit as well as in regular for-credit online courses though as far as I could gather had not really been tested extensively in Europe. I can imagine that European universities will be unwilling to risk such extensive surveillance data being stored outside the EU but I'm sure there will be a solution. The claim is that this technology will make online examinations at least as secure as traditional on-site exams (ie. not completely cheat-proof but probably good enough).

The conference closed with a thought-provoking speech by Pierre Dillenbourg who called on European universities to agree on how to recognize each others' MOOCs and open the way for real virtual mobility through a kind of virtual Erasmus programme. He argued that we already have the key ingredients in place; we have a common academic currency in terms of the Bologna agreement and ECTS, we have publicly funded universities giving around 4000 potential testing centres and we have cultural diversity so why can’t we offer credits for MOOCs? He urged universities and university associations to start discussing this and there were several representatives in the hall who immediately agreed to investigate further. The conference Twitter feed immediately informed us that there is already a cooperation in place between a few universities for exactly this sort of virtual mobility called Opening universities for virtual mobility.

My one concern with all this is that that the potential of MOOCs to truly open up education is being tamed and adapted to fit nicely into the traditional model. The focus now seems to be on the value-added layers and the promise of examination and credits. The wider potential of open networked learning I believe will be the task of non-traditional educational organisations rather than the higher education sector.

There were of course many other extremely interesting presentations and discussions and I may well return to them in a later post as I may do about my own contribution.

Download the full proceedings of the conference.

Horizon Report 2015

It's tough to make predictions, especially about the future, as the great baseball player and coach Yogi Berra is reputed to have said. However every year at the start of February New Media Consortium unveil the influential NMC Horizon Report on technology trends influencing higher education. Each year the eagerly awaited report features six trends, technologies and challenges and divides them according to an estimated time to implementation. This year's report has the following line-up:

Trends
Short-term: increased use of blended learning, redesigning learning spaces
Mid-term: measuring learning, proliferation of open educational resources
Long-term: advancing cultures of change and innovation, increasing cross-institution collaboration

Challenges
Solvable: blending formal and informal learning, improving digital literacy
Difficult: personalised learning, teaching complex thinking
Wicked: rewards for teaching, competing models of education

Technologies
Short-term: flipped classroom, bring your own device
Mid-term: makerspace, wearable technology
Long-term: internet of things, adaptive learning technologies

Most of these trends are no surprise to anyone involved in e-learning and regular readers of the report recognize some issues that have been on the list for many years, always just around the corner but never quite going mainstream. Concepts like flipped classroom, blended learning and open educational resources do not seem particularly new but I think the justification for including them is that they will finally move from being pioneer projects to full acceptance. The influence of the digital revolution on education does not move in a predictable linear progression but comes in fits and starts with a number of Gartner hype cycles all intertwining with each other. As a result trends that seem to be on the near horizon suddenly appear further away and other ones can suddenly appear right in the foreground from nowhere. A bit like quantum physics ...

However for me the report has two very important roles. Firstly it's a solid report that can be used to influence decision-makers, outlining clearly the key challenges for universities in the next 5-10 years without being too unwieldy. It can be read in under an hour and provides a good foundation for strategic discussions. Secondly I appreciate all the references to current projects and initiatives in each of the fields covered. Each year I discover real pearls in these lists that can be used to inspire others. I haven't clicked on all the links yet (and maybe never will) but here are some excellent take-aways from this year's report:

• Competency-Based Education Network - A network of 33 US universities working in the growing field of competency-based education - recognising workplace skills and combining academic and professional education. 
• Code of practice for learning analytics (JISC) - As the field of learning analytics finally begins to mature many institutions are concerned about student data being in the hands of commercial interests. This handbook from JISC provides a sound foundation on the legal and ethical questions involved.
• Blended Synchronous Learning Handbook - Result of a recent Australian project investigating how web-conferencing and virtual worlds can be used to unite campus and online students.
• Learning Space Rating System - The development of flexible and creative physical learning spaces is very much in focus as many universities consider redesigning their campus. This is a set of criteria for assessing how well your classrooms facilitate active learning activities.
• ePortfolios & Open Badges Maturity Matrix - Result of a recent European project (www.europortfolio.org) that provides criteria for assessing the maturity and validity of inplementing e-portfolois and badges in an institution.

The trends and challenges are of course essential reading but it's the practical examples that make it worthwhile. 

NMC Horizon Report 2015, Higher education edition.

Photo: CC BY Some rights reserved. Johnson, L., Adams Becker, S., Estrada, V., and Freeman, A. (2015). NMC Horizon Report: 2015 Higher Education Edition. Austin, Texas: The New Media Consortium

Are MOOCs really about rebranding?

  by derekGavey on Flickr

What's the difference between a MOOC and a regular online for-credit course? That's the question asked by David Wiley in a post entitled Koller, Thicke, and Noble: The “Blurred Lines” Between Traditional Online Courses and MOOCs. Most people would answer that scalability is the key feature of a MOOC with tens of thousands of participants signing up for the most popular courses. However there have been many massive online courses even before the four-letter acronym was invented, for example the popular summer math refresher course, Sommarmatte (site in Swedish), run by several Swedish universities for many years. Here hundreds of high school graduates refresh their math skills helped by student mentors in the sort of peer learning that many MOOCs are working with. So if scalability is nothing new what then is so special about MOOCs?

Wiley presents a long list of common features between MOOCs and online courses and concludes that the main difference is the type of platform:

The more I think about it, there seems to be only one practical difference between MOOCs and traditional online courses – the platform they are offered on. Online courses are offered via Blackboard and Canvas, while MOOCs are offered via Coursera and EdX.

In the traditional online course the focus is on the university and its faculty and the choice of platform is largely irrelevant for the students. In a MOOC, however. the platform has star billing.

In a traditional online course, the lead brand is the institution, followed by the faculty member, with little or no consideration for the LMS the course is offered in. (Have you ever seen an ad for a traditional online course that touted (or even mentioned) which LMS the course was offered in?)

By contrast, with MOOCs the lead brand is the LMS – you’re taking a course on Coursera! It happens to be offered by MIT. And there is probably a list of “Course Staff” buried at the bottom of the About the Course page.

Is the MOOC movement really about rebranding education? I don't see higher education being swallowed up by MOOC consortia but there are certainly concerns about who owns what and how the major consortia will be able to use their vast amounts of student data for future learning analytics applications. I don't see the present MOOC consortia as a threat and there is clearly an interest in the courses they provide. However, as I have written in several previous posts, there must be alternative paths available. It's perfectly possible for a university to go it alone and offer an open and scalable variant of an existing online course. Whether they label that as a MOOC or not is irrelevant, it's the openness that matters. Wiley sees the adoption of open licensing and the resultant sharing, reuse and adaptation of learning resources as the alternative path forward allowing greater access and improving quality through co-creation and peer review of resources and methods. MOOCs in their present form are simply one of many variations in online education. How we interpret the word open is the key issue to investigate in 2015.

Paths to openness

  by hockadilly on Flickr

Martin Weller's new book The battle for open provides an excellent overview of the role of openness in higher education today. It charts the development of the main strands of openness (open access, MOOCs, open educational resources and open scholarship) and suggests that although the MOOC boom has made people more aware of the opportunities of open online education it is a false dawn. Interpretations of openness vary greatly and most MOOCs choose to only focus on free access but maintain full copyright on the material. Major investments of venture capital underpin the mainstream MOOC movement and many academics are concerned about the commercialisation of higher education.

One might therefore expect this to be a time of celebration for the advocates of openness. Having fought so long for their message to be heard, they are now being actively courted by senior management for their experience and views on various open strategies. Open approaches are featured in the mainstream media. Millions of people are enhancing their learning through open resources and open courses. Put bluntly, it looks as though openness has won. And yet you would be hard pushed to find any signs of celebration amongst those original advocates. They are despondent about the reinterpretation of openness to mean ‘free’ or ‘online’ without some of the reuse liberties they had envisaged. Concerns are expressed about the commercial interests that are now using openness as a marketing tool. Doubts are raised regarding the benefits of some open models for developing nations or learners who require support. At this very moment of victory it seems that the narrative around openness is being usurped by others, and the consequences of this may not be very open at all.

Weller points to the Silicon Valley narrative that education is broken and that commercial solutions will reinvent the sector. It's an attractive and media-friendly argument that has won many supporters and I'll admit that I've been won over by many of the articles and videos that have gone viral in recent years. The image of a hopelessly outdated system based on dull lectures and exam halls and failing to exploit digital technology may have some truth in it but is still a sweeping generalisation that fails to acknowledge the advances made in online higher education in the past 15 years. The MOOC concept was after all developed by university faculty and researchers as pedagogical innovation, Silicon Valley latched on and adapted the idea several years later.

So with the spotlight still focused on mainstream MOOCs some of the really interesting develoments have been taking place in the shade. If we are at a crossroads in the development of openness with one road leading to commercialisation we also need to see an alternative route where resources and tools are shared openly with permission to reuse and remix. One possible avenue could be the new initiative Unizin which is a consortium of American universities whose aim is to take control of their own infrastructure, resources and tools and offer a non-commercial cloud-based platform for higher education, outside the influence of commercial actors. Many fear that by linking up with major corporations and venture capital sponsored MOOC consortia higher education may be selling its soul to big business. Unizin wants to create a common cloud repository for educational resources that can be freely shared. The main driving force behind this is the potential of learning analytics and if student data is kept within the educational domain then it can be analysed for educational purposes.

Our goals and purpose in endorsing Unizin are simple: As professors and members of the academy, we want to support faculty and universities by ensuring that universities and their faculty stay in control of the content, data, relationships, and reputations that we create. As we look at the rapidly emerging infrastructure that enables digital learning, we want to bias things in the direction of open standards, interoperability, and scale. Unizin is about tipping the table in favor of the academy by collectively owning (buying, developing, and connecting) the essential infrastructure that enables digital learning on our campuses and beyond.

In a similar vein the Finnish government has announced plans for a national cloud-based educational platform called EduCloud (information in Finnish only at present) which aims to house a national repository of open educational resources as well as common tools and services. There is no doubt that commercial actors will continue to offer innovative solutions for education but the path to true openness lies in the educational sector taking charge of their resources and services. But this path is not about each institution building its own solution but in national and international cooperation. Maybe this will be a major theme for 2015.