25 Years of EdTech: 2018 – Critical Ed Tech

Farväl - Goodbye

[The last in the 25 Years of Ed Tech series]

I’ll do a conclusion and themes post (if I can be arsed) of the 25 Years series, but now we reach the end. For this year, I’ve chosen not a technology, but rather a trend. I see in much of ed tech a divide, particularly at conferences. There is the gung ho, Silicon Valley, technology utopian evangelists. This is a critical reflection free zone, because the whole basis of this industry is on selling perfect solutions (to problems they have concocted). This is where the money is.

In contrast to this is a developing strand of criticality around the role of technology in society and in education in particular. With the impact of social media on politics, Russian bots, (actual) fake news, Cambridge Analytica, and numerous privacy scares, the need for a critical approach is apparent. Being sceptical about tech is no longer a specialist interest. Chris Gilliard has an excellent thread on all the invasive uses of tech, not all educational, but there are educational implementations for most of them.

One prominent strand of such criticality is suspicion about the claims of educational technology in general, and the role of software companies in particular. One of the consequences of ed tech entering the mainstream of education is that it becomes increasingly attractive to companies who wish to enter the education market. Much of the narrative around ed tech is associated with change, which quickly becomes co-opted into broader agendas around commercialisation, commodification and massification of education.

For instance, the Avalanche report argued that systemic change is inevitable because “elements of the traditional university are threatened by the coming avalanche. In Clayton Christensen’s terms, universities are ripe for disruption”. In this view, education, perceived as slow, resistant to change and old-fashioned is seen as ripe for disruption. Increasingly then academic ed tech is reacting against these claims about the role of technology and is questioning the impact on learners, scholarly practice, and its implications. For example, while learning analytics have gained a good deal of positive coverage regarding their ability to aid learners and educators, others have questioned their role in learner agency and monitoring and their ethics.

One of the key voices in ed tech criticality is Neil Selwyn, who argues that engaging with digital impact on education in a critical manner is a key role of educators, stating “the notion of a contemporary educational landscape infused with digital data raises the need for detailed inquiry and critique”. This includes being self-critical, and analysing the assumptions and progress in movements within ed tech. It’s important to distinguish critique as Selwyn sees it, and just being anti-technology. These are not pro and anti technology camps – you can still be enthusiastic about the application of technology in particular contexts. What it does mean is being aware of the broader implications, questioning claims, and advocating (or conducting) research about real impacts.

Ed tech research then has begun to witness a shift from advocacy, which tended to promote the use of new technologies, to a more critical perspective. This is not to say that there is enough critical thought around, and the drive for venture capital still seeks to eradicate it, but this series is about when moments in ed tech became significant. 2018 marks that for a more receptive approach to critical perspectives. If the evangelist and critical approaches represent two distinct groups, then sitting inbetween these two is the group we should all be focused on in ed tech – the practitioners in universities, schools and colleges who want to do the best for their learners. And that seems a fitting place to end the series.

25 Years of Ed Tech: 2017 – blockchain


All clear now? (image from https://www.intheblack.com/articles/2018/03/22/blockchain-future-record-keeping)

Of all the technologies listed in this series, blockchain is perhaps the most perplexing, both in how it works and in why it is even in this list. In 2016 several people independently approached me about blockchain — the distributed, secure ledger for keeping the records that underpin Bitcoin. The question was always the same: “Could we apply this in education somehow?” The imperative seemed to be that blockchain was a cool technology, and therefore there must be an educational application. It could provide a means of recording achievements and bringing together large and small, formal and informal, outputs and recognition.

Viewed in this way, blockchain is attempting to bring together several issues and technologies: e-portfolios, with the aim to provide an individual, portable record of educational achievement; digital badges, with the intention to recognize informal learning; MOOCs and OER, with the desire to offer varied informal learning opportunities; PLEs and personalized learning, with the idea to focus more on the individual than on an institution. A personal, secure, permanent, and portable ledger may well be the ring to bind all these together. However, the history of these technologies should also be a warning for blockchain enthusiasts. With e-portfolios, for instance, even when there is a clear connection to educational practice, adoption can be slow, requiring many other components to fall into place. In 2018 even the relatively conservative and familiar edtech of open textbooks is far from being broadly accepted. Attempting to convince educators that a complex technology might solve a problem they don’t think they have is therefore unlikely to meet with widespread support.

If blockchain is to realize any success, it will need to work almost unnoticed; it will succeed only if people don’t know they’re using blockchain. Nevertheless, many who propose blockchain display a definite evangelist’s zeal. It is perhaps the nirvana of technological solutionism – a technology that no-one really understands, doing something they can’t quite unpack for reasons they don’t fathom. They desire its adoption as an end goal in itself, rather than as an appropriate solution to a specific problem. If I had the time I’d keep a blockchain tumblr for ridiculous proposals for blockchain solutions. I think the most important aspect of blockchain might be to keep an eye on how it gets used without our knowledge, and what the implications for that are. If anyone tries to sell your VC/Principal a blockchain solution make sure someone tech-smart is in that room.

In the meantime, if you need to blag blockchain knowledge in a meeting, just take a leaf out of this advert’s book and end every sentence with “thanks to the blockchain solution.”

25 Years of Ed Tech: 2016 – The return of AI

robots

[Continuing the 25 Years of Ed Tech series]

I covered this in 1993’s entry, that Artificial intelligence was the focus of attention in education in the 1980s and 1990s with the possible development of intelligent tutoring systems. The initial enthusiasm for these systems waned somewhat, when they failed to deliver on their promise. For example, in their influential 1985 paper, Anderson, Boyle and Reiser detailed intelligent tutoring systems for geometry and the programming language LISP. They confidently predicted that “Cognitive psychology, artificial intelligence, and computer technology have advanced to the point where it is feasible to build computer systems that are as effective as intelligent human tutors”. Yet, by 1997 Anderson was amongst authors lamenting that “intelligent tutoring has had relatively little impact on education and training in the world.” In their analysis they hit upon something which seems obvious, and yet continues to echo through educational technology, namely that the ed tech (in this case intelligent tutoring systems but it might equally apply to MOOCs, say) are not developed according to educational perspectives. They stated that “the creative vision of intelligent computer tutors has largely arisen among artificial intelligence researchers rather than education specialists. Researchers recognized that intelligent tutoring systems are a rich and important natural environment in which to deploy and improve Al algorithms… the bottom line is that intelligent tutoring systems are generally evaluated according to artificial intelligence criteria …rather than with respect to a cost/benefit analysis educational effectiveness.” In short, they are developed and evaluated by people who like the technology, but don’t really know or appreciate the educational context. In this snapshot we have much of the history of ed tech.

Interest in AI faded as interest in the web and related technologies increased, but it has resurfaced in the past five years or so. What has changed over this intervening period is the power of computation. Much if what we classify as AI now is just massive number crunching. That’s not cheating – maybe that’s what we do as humans anyway.

But perhaps more significant than the technological issues are the ethical ones we now face. As Audrey Watters contends, AI is ideological. Neil Selwyn makes a pretty good case for why AI won’t succeed in education, which can be summarised as “education is fundamentally a human enterprise”. However, the concern about AI is not that it won’t deliver on the promise held forth by its advocates but, rather, that someday it will. Or rather that it will in the eyes of policy makers. And then the assumptions embedded in code will shape how education is realized, and if learners don’t fit that conceptual model, they will find themselves outside of the area in which compassion will allow a human to alter or intervene. Perhaps the greatest contribution of AI will be to make us realize how important people truly are in the education system.

25 Years of EdTech: 2015 – Digital Badges

[Continuing the 25 Years of Ed Tech series]

Providing digital badges for achievements that can be verified and linked to evidence started with Mozilla’s open badge infrastructure in 2011. They were an idea that had been floating around for a while – that you could earn informal accreditation for online activity. What the Mozilla work provided was a technical infrastructure, so badges could be linked through to evidence and verified. Badges could be awarded for assessment (passing a quiz), but more interestingly for community action, such as contributing to an online forum.

Like many other edtech developments, digital badges had an initial flurry of interest from devotees but then settled into a pattern of more laborious long-term acceptance. They represent a combination of key challenges for educational technology:

  • realizing easy-to-use, scalable technology – the Mozilla specification provides this, and tools such as Credly make creating and distributing badges reasonably straightforward;
  • developing social awareness that gives them currency – badges may be fun, but for them to gain value they need to be recognised by employers and society more widely;
  • and providing the policy and support structures that make them valuable – we have complicated systems and quality control processes around formal recognition. If employers are to start valuing badges then similar structures may need to be in place to give confidence in their value. And then the question may become, what is the point of them if they’re indistinguishable from formal credit?

Of these challenges, only the first relates directly to technology; the more substantial ones relate to awareness and legitimacy. For example, if employers or institutions come to widely accept and value digital badges, then they will gain credence with learners, creating a virtuous circle. There is some movement in this area, particularly with regard to staff development within organizations and often linked with MOOCs. Perhaps more interesting is what happens when educators design for badges, breaking courses down into smaller chunks with associated recognition, and when communities of practice give badges value. Linked with eportfolios, and transferable credit, then badges can provide a way of surfacing the generic skills inherent in much of formal education. Currently, their use is at an indeterminate stage — neither a failed enterprise nor the mainstream adoption once envisaged, but I suspect we’ll see steady growth around specific enterprises.

25 Years of EdTech: 2014 – Learning analytics

[Continuing the 25 Years of Ed Tech series]

Data, data, data. It’s the new oil and the new driver of capitalism, war, politics. So inevitably its role in education would come to the fore. Interest in analytics is driven by the increased amount of time that students spend in online learning environments, particularly LMSs and MOOCs. Although not a direct consequence, there is a definite synergy and similarity between MOOCs and analytics. Both brought new people into education technology, particularly from the computer science field. I think we can be a bit snooty about this, what are all these hard core empiricists suddenly doing in our touchy-feely domain? But if the knowledge exchange is reciprocal, then this evolving nature of ed tech can be one of its strengths. The reservations arise when it is less of a mutual knowledge sharing and more an aggressive take-over.

The positive side of learning analytics is that for distance education in particular, it provides the equivalent of responding to discreet signals in the face-to-face environment: the puzzled expression, the yawn, or the whispering between students looking for clarity. Every good face-to-face educator will respond to these signals and adjust their behaviour. In an online environment, these cues are absent, and analytics provides some proxy for these. If an educator sees that students are repeatedly going back to a resource, that might indicate a similar need to adapt that resource, offer further advice, etc.

The downsides are that learning analytics can reduce students to data and that ownership over the data becomes a commodity in itself. Let’s face it, the use of analytics has only just begun, and the danger is that instead of analytics supporting education, analytics becomes education. The edtech field needs to avoid the mistakes of data capitalism; it should embed learner agency and ethics in the use of data, and it should deploy that data sparingly.

One of the benefits of thinking about analytics might be simply better communication to students. Navigating the peculiar, often idiosyncratic world of higher education with its rules and regulations can be daunting and confusing. By considering useful dashboards for instance, the complexity of this is surfaced. In this study, simply telling students what degree they were on course for was deemed remarkably useful. It transpires that calculating this for yourself is remarkably difficult, which highlights itself how HEIs can do a lot to simplify and expose their workings for students.

25 years of EdTech: 2013 – Open Textbooks

[Continuing the 25 Years of Ed Tech series]

If MOOCs were the glamorous side of open education, all breathless headlines and predictions, open textbooks were the practical, even dowdy, application. An extension of the OER movement, and particularly pertinent in the United States and Canada, open textbooks provided openly licensed versions of bespoke written textbooks, free for the digital version. The cost of textbooks provided an initial motivation for adoption, but it is the potential of adaption that makes them interesting. Open textbooks are sometimes criticised for being an unimaginative application of the possibilities of open. But they also offer a clear example of several aspects which need to align for ed tech adoption in higher ed.

Firstly, they set out to establish a solid evidence base. They did not just rely on altruism, and statements of belief. The Open Ed group in particular demonstrated that open textbooks were of high quality, and had a positive impact on students. This evidence base makes it difficult for them to be dismissed by commercial interests.

Secondly, through funding from the likes of Hewlett, some professional, long term providers were established who could produce reliable quality. These books looked as good as anything that you bought, they weren’t some quirky DIY effort.

Thirdly, the switching of costs from purchase to production established a viable economic model that is applicable for other open approaches. They could not be dismissed as unsustainable.

These three elements lay the foundation for their adoption and overcome many of the reservations or objections raised. Now the challenge is from this base to start doing the really interesting stuff. As with LMSs, open textbooks offer an easy route to adoption. Exploration around open pedagogy, co-creation with students, and diversification of the curriculum all point to a potentially rich, open, edtech ecosystem—with open textbooks at the centre. However, the possible drawback is that like LMSs, open textbooks may not become a stepping-stone on the way to a more innovative, varied teaching approach but, rather, may become an end point in themselves.

What I like about open textbooks is they don’t seek to remove the human element from education. Make education more affordable, flexible, accessible but still essentially human. Maybe that’s why they don’t attract the attention of venture capitalists.

Recognising our own expertise

During the recent OU Crisis, one of the things I moaned about was the lack of faith senior management seemed to have in the expertise of their own staff. We brought in consultants, and hired people outside of higher ed, to tell us how to be a better open university. I know my institution is not alone in this, and it portrays perhaps an insecurity about our own knowledge.

So, having moaned about it, my bluff has been called. I’ve been asked to lead a set of internal OU seminars, highlighting expertise we have and focussing on how it can be applied practically. I have a vagueish set of principles for the series:

  • Based on combination of external research and work at the OU
  • Discussion based, no predetermined solutions
  • Not linked to any specific workstream, strategic priority, etc.
  • Input from all OU staff welcome
  • Focus on practical application within the OU, which could be realised within a reasonable time frame.
  • Interactive (maybe fun even?)

I feel it’s rooted in the practical approach to ed tech. I’m starting the series off with a seminar based on the OOFAT work as a way of thinking about our own strategy, on Tuesday 17 July at 11am-12pm in Hub Theatre. If you’re OU staff, please come along. We plan to either record or stream it, so hopefully available to all.

I would also like to hear if others have run similar type of sessions or programmes at their institutions, if there were particular approaches they would recommend (or recommend to avoid)?

25 Years of EdTech – 2012: MOOCs


(we used David Kernohan’s image a lot back in the day and this is Michael Branson Smith’s animated version)

[Continuing the 25 Years of Ed Tech series]

Inevitably, in this series 2012 had to be allocated to MOOCs, when it was so breathlessly anointed “The Year of the MOOC“. In many ways the MOOC phenomenon can be viewed as the combination of several preceding technologies: some of the open approach of OER, the application of video, the experimentation of connectivism, and the revolutionary hype of web 2.0. Clay Shirky mistakenly proclaimed that MOOCs were the internet happening to education. If he’d been paying attention, he would have seen that this had been happening for some time. Rather, MOOCs were Silicon Valley happening to education. Once Stanford Professor Sebastian Thrun’s course had attracted over 100,000 learners and almost as many headlines, the venture capitalist investment flooded in.

Much has been written about MOOCs, more than I can do justice to here. They are a case study still in the making. The raised profile of open education and online learning caused by MOOCs may be beneficial in the long run, but the MOOC hype (only ten global providers of higher education by 2022?) may be equally detrimental. The edtech field needs to learn how to balance these developments. Millions of learners accessing high-quality material online is a positive, but the rush by colleges and universities to enter into prohibitive contracts, outsource expertise, and undermine their own staff has long-term consequences as well.

With MOOC companies still trying to find business models, the hype of revolutionising higher ed has often become something more muted such as “we do nice corporate training“. And it is still an industry that relies on higher education, so the alliance between the two needs to be mutually beneficial, less it go down the antagonistic model of academic publishing. Grizzled old educational technologists such as myself who hold memories of their hand coded HTML websites dear might bemoan the Year Zero mentality of MOOC entrants (“we’ve invented online learning, say thank you!”), it is also the case that when it works well, universities have gained a lot of experience in developing online courses and dealing with the needs of online learners, which had stalled in many places.

And I’ll forever be grateful to MOOCs for the sheer number of blog posts they generated.

PS – if you want a SPOILER for the remaining years, I was asked to turn this series into a 20 Years of Ed Tech article for Educause Review (who are celebrating their 20th anniversary).

25 Years of EdTech: 2011 – PLE

Personal Learning Environments (PLEs) were an outcome of the proliferation of services that suddenly became available following the web 2.0 boom. Learners and educators began to gather a set of tools to realize a number of functions. In edtech, the conversation turned to whether these tools could be somehow “glued” together in terms of data. We got quite excited about the idea of eduglu, which might be a bit embarrassing now. Instead of talking about one LMS provided to all students, we were discussing how each learner had their own particular blend of tools. Yet beyond a plethora of spoke diagrams, with each showing a different collection of icons, the PLE concept didn’t really develop after its peak in 2011. In 2014 I asked why we didn’t talk about PLEs anymore, and offered the following reasons:

  • It’s become commonplace, so drawing the distinction between your set of tools and an institutional learning environment isn’t necessary. It’s a bit like saying “my phone is mobile!”
  • It’s become absorbed, so it is seen as an extension of the LMS, or rather the LMS is just one other part of it. We don’t differentiate between tools for different settings because the boundaries between personal and professional have been blurred.
  • There has been a shakedown in the market, so actually we’ve all settled on the same few tools: Twitter, YouTube, WordPress, Slideshare, plus some other specific ones. My PLE looks pretty much like your PLE, so it’s not really a Personal one anymore. Just like with the early days of search engines, we don’t talk about whether you prefer Lycos or Webcrawler now, we just Google it.
  • It wasn’t a useful term or approach. There were projects that attempted to get data passed between LMSs and PLE tools, or to set these up for people, and in the end people just opted for some tools they found useful, and didn’t feel the need to go further.

These still seem reasonable, particularly the reduction in variety of tools. The problem was that passing along data was not a trivial task, and we soon became wary about applications that shared data (although perhaps not wary enough, given recent news regarding Cambridge Analytica). Also, providing a uniform offering and support for learners was difficult when they were all using different tools. The focus shifted from a personalized set of tools to a personalized set of resources, and in recent years this has become the goal of personalization. But that is a whole different story. I miss the excitement of having a favourite url shortener though.

25 Years of EdTech: 2010 – Connectivism

Untitled

[Continuing the 25 Years of Ed Tech series]

The early enthusiasm for e-learning saw a number of pedagogies resurrected or adopted to meet the new potential of the digital, networked context. Constructivism, problem-based learning, and resource-based learning all saw renewed interest as educators sought to harness the possibility of abundant content and networked learners.

Yet connectivism, as proposed by George Siemens and Stephen Downes in 2004–2005, could lay claim to being the first internet-native learning theory. Siemens defined connectivism as “the integration of principles explored by chaos, network, and complexity and self-organization theories. Learning is a process that occurs within nebulous environments of shifting core elements—not entirely under the control of the individual.”

Further investigating the possibility of networked learning led to the creation of the early MOOCs, including influential open courses by Downes and Siemens in 2008 and 2009. Pinning down exactly what connectivism was could be difficult, George stressed it was not a pedagogy, but rather it could be viewed as a set of principles:

  • Learning and knowledge rests in diversity of opinions.
  • Learning is a process of connecting specialized nodes or information sources
  • Learning may reside in non-human appliances
  • Capacity to know more is more critical than what is currently known
  • Nurturing and maintaining connections is needed to facilitate continual learning.
  • Ability to see connections between fields, ideas, and concepts is a core skill.
  • Currency (accurate, up-to-date knowledge) is the intent of all connectivist learning activities.
  • Decision-making is itself a learning process. Choosing what to learn and the meaning of incoming information is seen through the lens of a shifting reality. While there is a right answer now, it may be wrong tomorrow due to alterations in the information climate affecting the decision.

What was significant about connectivism was that it represented an attempt to rethink how learning is best realized given the new realities of a digital, networked, open environment, as opposed to forcing technology into the service of existing practices. This has been surprisingly rare since – Dave Cormier and others have ventured rhizomatic learning, I don’t think I ever explored the concept of a pedagogy of abundance fully, and there is now some development around the idea of open pedagogy, but in general it feels that we have stopped noticing the possibilities of networked technology. For example, while connectivism provided the basis for MOOCs, the approach they eventually adopted was far removed from this and fairly conservative. Perhaps when the internet was new, we noticed these differences more starkly, but now it is the norm, the contrast doesn’t raise as many questions. Even if it’s not connectivism per se, we should continually revisit the impetus to examine the learning possibilities that led to its formulation.

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