November 20, 2017

Online learning in 2016: a personal review


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Image: © Institute for Economics and Peace. Canada is ranked seventh most peaceful. We don’t know where it ranks though in terms of online learning.

A personal review

I am not going to do a review of all the developments in online learning in 2016 (for this, see Audrey Watters’ excellent HackEducation Trends). What I am going to do instead is review what I actually wrote about in 2016 in this blog, indicating what to me was of particular interest in online learning during 2016. I have identified 38 posts I wrote in which I have explored in some detail issues that bubbled up (at least for me) in 2016.

1. Tracking online learning

Building a national survey of online learning in Canada (134 hits)

A national survey of university online and distance learning in Canada (1,529 hits)

In the USA, fully online enrollments continue to grow in 2014 (91 hits)

Are you ready for blended learning? (389 hits)

What the Conference Board of Canada thinks about online learning (200 hits)

I indulged my obsession with knowing the extent to which online learning is penetrating post-secondary education with five posts on this topic. In a field undergoing such rapid changes, it is increasingly important to be able to track exactly what is going on. Thus a large part of my professional activity in 2016 has been devoted to establishing, almost from scratch, a national survey of online learning in Canadian post-secondary institutions. I would have written more about this topic, but until the survey has been successfully conducted in 2017, I have preferred to keep a low profile on this issue.

However, during 2016 it did become clear to me, partly as a result of pilot testing of the questionnaire, and partly through visits to universities, that blended learning is not only gaining ground in Canadian post-secondary education at a much faster rate than I had anticipated, but is raising critical questions about what is best done online and what face-to-face, and how to prepare institutions and instructors for what is essentially a revolution in teaching.

This can be best summarized by what I wrote about the Conference Board of Canada’s report:

What is going on is a slowly boiling and considerably variable revolution in higher education that is not easily measured or even captured in individual anecdotes or interviews.

2. Faculty development and training

Getting faculty and instructors into online learning (183 hits)

Initiating instructors to online learning: 10 fundamentals (529 hits)

Online learning for beginners: 10. Ready to go (+ nine other posts on this topic = 4,238 hits)

5 IDEAS for a pedagogy of online learning (708 hits)

This was the area to which I devoted the most space, with ten posts on ‘Online Learning for Beginners’, aimed at instructors resisting or unready for online learning. These ten posts were then edited and published by Contact North as the 10 Fundamentals of Teaching Online.

Two fundamental conclusions: we need not only better organizational strategies to ensure that faculty have the knowledge and training they will need for effective teaching and learning in a digital age, but we also need to develop new teaching strategies and approaches that can exploit the benefits and even more importantly avoid the pitfalls of blended learning and learning technologies. I have been trying to make a contribution in this area, but much more needs to be done.

3. Learning environments

Building an effective learning environment (6,173 hits)

EDEN 2016: Re-imagining Learning Environments (597 hits)

Culture and effective online learning environments (1,260 hits)

Closely linked to developing appropriate pedagogies for a digital age is the concept of designing appropriate learning environments, based on learners’ construction of knowledge and the role of instructors in guiding and fostering knowledge management, independent learning and other 21st century skills.

This approach I argued is a better ‘fit’ for learners in a digital age than thinking in terms of blended, hybrid or fully online learning, and recognizes that not only can technology to be used to design very different kinds of learning environments from school or campus based learning environments, but also that technology is just one component of a much richer learning context.
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4. Experiential learning online

A full day of experiential learning in action (188 hits)

An example of online experiential learning: Ryerson University’s Law Practice Program (383 hits)

Is networked learning experiential learning? (163 hits)

These three posts explored a number of ways in which experiential learning is being done online, as this is a key methodology for developing skills in particular.

5. Open education

Acorns to oaks? British Columbia continues its progress with OERs (185 hits)

Talking numbers about open publishing and online learning (113 hits)

Towards an open pedagogy for online learning (385 hits)

These posts also tracked the development of open publishing and open educational resources, particularly in British Columbia, leading me to conclude that the OER ‘movement’ has far too narrow a concept of open-ness and that in its place we need an open pedagogy into which open educational resources are again just one component, and perhaps not the most significant.

6. Technology applications in online learning

An excellent guide to multimedia course design (659 hits)

Is video a threat to learning management systems? (603 hits)

Some comments on synchronous online learning technologies (231 hits)

Amongst all the hype about augmented reality, learning analytics and the application of artificial intelligence, I found it more useful to look at some of the technologies that are in everyday use in online learning, and how these could best be used.

7. Technology and alienation

Technology and alienation: online learning and labour market needs (319 hits)

Technology and alienation: symptoms, causes and a framework for discussion (512 hits)

Technology, alienation and the role of education: an introduction (375 hits)

Automation or empowerment: online learning at the crossroads (1,571 hits)

Why digital technology is not necessarily the answer to your problem (474 hits)

These were more philosophical pieces, prompted to some extent by the wider concerns of the impact of technology on jobs and how that has influenced Brexit and the Trump phenomena.

Nevertheless this issue is also very relevant to the teaching context. In particular I was challenging the ‘Silicon Valley’ assumption that computers will eventually replace the need for teachers, and in particular the danger of using algorithms in teaching without knowing who wrote the algorithms, what their philosophy of teaching is, and thus what assumptions have been built into the use of data.

Image: Applift

Image: Applift

8. Learning analytics

Learning analytics and learning design at the UK Open University (90 hits)

Examining ethical and privacy issues surrounding learning analytics (321 hits)

Continuing more or less the same theme of analysing the downside as well as the upside of technology in education, these two posts looked at how some institutions, and the UK Open University in particular, are being thoughtful about the implications of learning analytics, and building in policies for protecting privacy and gaining student ‘social license’ for the use of analytics.

9. Assessment

Developing a next generation online learning assessment system (532 hits)

This is an area where much more work needs to be done. If we are to develop new or better pedagogies for a digital age, we will also need better assessment methods. Unfortunately the focus once again appears to be more on the tools of assessment, such as online proctoring, where large gains have been made in 2016, but which still focus on proctoring traditional assessment procedures such as time-restricted exams, multiple choice tests and essay writing. What we need are new methods of assessment that focus on measuring the types of knowledge and skills that are needed in a digital age.

For instance, e-portfolios have held a lot of promise for a long time, but are still being used and evaluated at a painfully slow rate. They do offer though one method for assessment that reflects much better the needs of assessing 21st century knowledge and skills. However we need more imagination and creativity in developing new assessment methods for measuring the knowledge and skills needed for a digital age.

That was the year that was

Well, it was 2016 from the perspective of someone no longer teaching online or managing online learning:

  • How far off am I, from your perspective?
  • What were the most significant developments for you in online learning in 2016?
  • What did I miss that you think should have been included? Perhaps I can focus on this next year.

I have one more post looking at 2016 to come, but that will be more personal, looking at my whole range of online learning activities in 2016.

In the meantime have a great seasonal break and I will be back in touch some time in the new year.

Building a national survey of online learning in Canada

Image: Canada Explore

Image: Canada Explore

The players

Since April I have been leading a small team that has been trying to build from scratch a national survey of online learning in Canadian post-secondary institutions.

For many years the Babson Survey Research Group has been tracking the growth of online learning in higher education in the USA. With the U.S. Federal Department of Education now collecting this data through its annual IPEDS survey, Jeff Seaman of Babson has been working with Russ Poulin of WCET to help interpret the IPEDS data.

Through the intervention of Tricia Donovan, the director of eCampus Alberta, Jeff and Russ approached me to see if I would be willing to get a Canadian national survey off the ground. I guess I was chosen because through my blog I had been strongly critical of the lack of such data in Canada. (Warning to bloggers: be careful what you ask for as you may end up doing it yourself.)

As a Research Associate with Contact North, I approached its President, Maxim Jean-Louis, for his support. He immediately offered $10,000 towards the cost of the survey. This was a crucial contribution as it enabled me to sound out possible consultants for the project, because Babson had found that the most important contributor to success was ensuring close communication and co-operation with the institutions themselves before the survey was even designed.

The Contact North funding enabled me to approach Dr. Ross Paul, formerly President of two Canadian universities and more importantly, as the author of “Leadership Under Fire”, a book about the role of university presidents in Canada, he was extremely well connected with and knowledgeable about the whole Canadian university sector.

Maxim Jean-Louis also put me in touch with Brian Desbiens, a former college president and also a former chair of the Canadian College Presidents Network, another consultant with an immensely impressive network in the Canadian college sector.

Finally it was immediately clear to us that we needed someone with knowledge and expertise in the francophone sector, and through the assistance of REFAD, the francophone distance education network, Denis Mayer, a former Associate Vice President of Student Services at Laurentian University, also joined the team.

So we now had a steering group for the survey:

  • Tony Bates (lead researcher)
  • Ross Paul (universities)
  • Brian Desbiens (colleges)
  • Denis Mayer (francophone)
  • Tricia Donovan (provincial government agencies)
  • Jeff Seaman (survey design and implementation)
  • Russ Poulin (US liaison)

The process

Our first task was to ensure that we had support, or at least not opposition, from the institutions, about 80 universities and over 200 publicly funded colleges. Fortunately in Canada there are almost no private universities and there is a clear distinction between provincially funded and supported colleges and private career and language schools. Our survey is focused then solely on the public system of post-secondary education, consisting of just over 2 million students.

One challenge is that there is no overall federal responsibility for the delivery of post-secondary education in Canada. This means that there are 10 provinces with 10 slightly different systems of post-secondary education. In addition there are anglophone, francophone and bilingual institutions.

Nevertheless there are two key national organisations, Universities Canada (UC), and Colleges and Institutes Canada (CICAN), that between them cover most of the institutions, so one of our first tasks was to brief them and gain their support in communicating with the institutions. Also there are several francophone organisations that represent the interests of francophone universities and colleges, and the unique system in Québec of CEGEPs, publicly funded pre-university colleges that offer a pre-university qualification that is necessary for admission to Québec’s universities (except for mature students). Secondary school and undergraduate degrees are both one year shorter in Quebec as a result.

These initial contacts with the national or regional organisations enabled us to identify the population base for the survey: the list of institutions to be covered. This enabled the consultants to e-mail directly the provosts and VPs Academic of every institution for their support and participation in the study.

At the same time, the Steering Committee was engaged in a series of discussions around the design of the questionnaires. We had the advantage of the prior work of the Babson Survey Research Group in the USA, but the questionnaires had to be adapted to the unique Canadian post-secondary education system. At the same time we are anxious to ensure that we can make international comparisons. It became quickly clear that we will need several different versions of the questionnaire, as follows:

  •  anglophone universities
  • anglophone colleges
  • francophone universities
  • CEGEPS
  • francophone colleges (outside Québec).

Core questions would be the same across all versions, but others would reflect the unique nature of each institution (e.g. what qualifications were offered partly or wholly online).

To get early feedback on the questionnaire design, two consultants attended the CIRPA conference of Canadian institutional researchers and held a special session devoted to feedback on the initial questionnaire design and especially in the definitions of fully online and blended/hybrid learning.

The first full versions of the questionnaires have now been designed. We have identified 10 universities and eight colleges across all 10 provinces who have volunteered to give feedback on the pilot questionnaire, and they have been asked to reply by the end of December. We are planning one more round of piloting after that, and hope to have the final version of the questionnaire distributed to all the universities and colleges in March.

In order to keep the questionnaire as short as possible, we are collecting as much key data about the institutions, such as their size, from other sources. For instance, the Canadian Virtual University has provided data on distance education enrolments for its dozen or so member institutions that go back to 2001. In the end, we will have an extensive and comprehensive database of Canadian post-secondary educational institutions, and of their activities in online learning.

I am working with Jeff Seaman on the design of the questionnaire analysis, and we will use the Babson Survey Research Group’s data entry and analysis facilities to process the questionnaire data. We envisage one overall, national report in English and French and a number of smaller reports focused on specific sectors, including a specially written report on the francophone sector. These will be published in the summer of 2017, and the results will be presented at the ICDE’s World Congress on Online Learning in Toronto in October.

Lastly, we will not be identifying any individual institution, unless they expressly request to be identified, but we do aim to make the data open and accessible to other researchers. We hope to locate the data with one or more of the organizations representing the institutions.

Funding

The Babson surveys in the USA benefited from financial support from the Sloan Foundation and also from a number of private sponsors, such as publishers.  Funding frankly has been the biggest challenge so far for the Canadian survey.

We decided to divide the funding requirements into three stages. The first stage would be to acquire funds to develop the institutional support needed, build the database, and design and pilot the questionnaire. The second stage of funding would be to cover the costs of the data collection, data entry, data analysis, report writing and dissemination, as well as having sufficient funds to start the development of the following year’s survey. The third phase would be to cover long-term and regular funding for future annual surveys.

We have successfully completed the first phase of fund raising, thanks to the help of Contact North and the provincial eCampuses (BCcampus, eCampus Alberta, Campus Manitoba and eCampus Ontario). This has raised $45,000.

We are still seeking funding for the second phase. We estimate that we will need somewhere around $100,000 to complete the second phase, and for the third phase we will need to raise about $125,000 a year.

We have submitted requests for second stage funding to eCampus Ontario’s Research and Innovation Fund and to a Canadian foundation, and we are waiting to hear from them. The Canadian arm of a major publisher has also expressed an interest in supporting the survey. However, we are now at the point where we urgently need to secure firm funding for the second stage.

What we need

The project is now at a critical point in its development. We have secured the support of the institutions, we are ready to pilot the questionnaire, and we are building the institutional database. However, we still need the following:

  • money to cover the costs of the actual survey and report writing (in both English and French)
  • feedback on the definitions of online learning, whether we have the right questions, and whether institutions can actually provide the data requested; the piloting will provide this feedback
  • all institutions, large and small, whether they have strong or no online programs at all, to complete the questionnaire.

The benefits

If we are successful in completing the study, we hope that we will have achieved the following:

  • established a reliable snapshot of the state of online learning across Canada in post-secondary education
  • created a comprehensive, national database of Canadian post-secondary educational institutions that could be used for further research purposes
  • provided a baseline for future studies of online learning, so trends can be tracked
  • identified the areas where online learning is growing or declining
  • identified some of the key issues that institutions are facing regarding online learning
  • enabled institutions to see how they compare with other institutions in Canada in terms of their online learning development
  • enabled Canada to compare itself with developments in online learning in other countries.

Your help

Although we are still pursuing a number of possible sources of funding, if you have ideas of where or how to secure the the second and third stages of funding, please contact me at tony.bates@ubc.ca.

In particular, I urge Canadian readers of this blog to give their support within their institution to ensure that we get as good a response as possible to completing the questionnaire so that we have a reliable and comprehensive survey.

Any other comments about the value of the survey or the strategy we are following will also of course be welcome.

In the meantime, watch this space for further developments.

References

Paul, R. (2011) Leadership Under Fire: The Challenging Role of the Canadian University President Montreal & Kingston: McGill-Queen’s University Press, pp. 333

 

EDEN 2016: Re-imagining Learning Environments

Pesti Vigadó, where the conference dinner was held

Pesti Vigadó Concert Hall, where the conference dinner was held

The EDEN conference

I have just attended the annual conference of the European Distance and E-Learning Network in Budapest, Hungary.

EDEN is one of my favourite conferences because it always has a lot of interesting people attending and it is a quick way for me to stay abreast of what is happening in European online and distance learning. I provide here an overall report on the conference, but I will do a couple of other more detailed posts on the sessions I found particularly interesting.

There were just under 300 participants. My overall impression is that online and open learning are well and strong in Europe, and is now widespread. When I first started to come to EDEN conferences in the early 1990s, there were only two or three main players, but this year there were contributions from almost every European country. With the growth of online and open learning, there are many new people each year joining the field, coming from very diverse backgrounds. EDEN provides a pan-European opportunity to enable newcomers to learn about some of the basic principles and prior research and knowledge in the field, as well as allowing for the sharing of experience and networking, and reporting new trends and developments in online and open learning.

I was the opening keynote speaker, and talked about building effective learning environments, based on my chapter in Teaching in a Digital Age. I also gave the wrap-up to the conference, on which this post is based.

A concert at the Liszt Academy of Music

A concert at the Liszt Academy of Music

Policy, planning and management

This year there was a welcome number of contributions that focused on policy and management of online, open and distance learning.

Yves Punie of the European Commission’s Joint Research Centre’s Institute for Prospective Technological Skills reported that 70 million Europeans lacked basic literacy and numeracy skills, 24% had no upper secondary education and 45% have insufficient digital literacy skills, although 90% of jobs in Europe will require some sort of ICT skills. The Institute has developed a list of key digital competencies. He noted that while 21% of universities in Europe are now offering MOOCs, most have no overall strategy for open education.

George Ubachs of the European Association of Distance Teaching Universities in his presentation on The Changing Pedagogical Landscape offered an interesting vision for universities that emphasised:

  • personalized teaching and learning
  • small scale, intensive education
  • rich learning environments
  • open-ness and flexibility
  • networked education and mobility

Leslie Wilson of the European University Association commented that:

MOOCs have forced Vice Chancellors to focus on teaching and learning

This is probably a true if sad statement.

I was particularly impressed by Melissa Highton’s report on the open learning strategy of Edinburgh University. It is a highly ranked, old research university in Scotland that has aligned its approach to open education to the university’s core mission. She said:

Not being open is a risk and not being open costs us money.

Laureate University is a global private, for-profit university with over one million enrolments, and with campuses in Europe as well as North America. The leadership at Laureate has decided that the whole system will move from largely face-to-face teaching to blended learning. Alan Noghiu described the strategy that is being used and the challenges the organization is facing in implementing the strategy.

Finally, Alan Tait reported on a study by the International Council for Distance Education (ICDE) on student success factors, which identified the following as critical to student success:

  • pre-study information, advice, guidance and admission;
  • curriculum or programme design that matches the needs of students;
  • intervention at key points and in response to student need;
  • assessment to support learning as well as to judge achievement;
  • individualised and personalised systems of support to students;
  • information and logistical systems that communicate between all relevant participants in the system;
  • overall managing for student success.

This seems to me to be a list that proponents of MOOCs should bear in mind, as well as those offering more formal qualifications at a distance.

The use of multimedia and emerging technologies

Susan Aldridge of Drexel University presented some very interesting examples of educational uses of virtual reality, augmented reality, serious games and holography, including examples used in forensic investigation, meteorology, and medicine. One of the augmented reality tools she demonstrated, Aurasma, is free.

Danny Arati of Intel mentioned the University of Nottingham’s The Periodic Table of Videos, where each element in the period table has a short video about it.

The Periodic Table of Videos, University of Nottingham

The Periodic Table of Videos, University of Nottingham

MOOCs and online learning

I was surprised at how much importance European institutions are still giving to MOOCs. There were by far more papers on MOOCs than on credit-based online learning or even blended learning. Even the Oxford debate this year was on the following motion:

We Should Focus in the Short Term More on MOOCs than on OER

I was relieved when the motion was resoundingly defeated, although I am still a little disheartened that open education is still mainly focused on MOOCs and OERs, rather than on the broader concept of open textbooks, open research, and open data. It was noted that MOOCs are a product while open education is a movement, and it is important not to lose the idea that open education is as much about social justice and equity as it is about technology, as was pointed out by one of the participants, Ronald McIntyre.

Learning analytics

There was an excellent workshop organised by Sally Reynolds and Dai Griffiths from the European Commission funded LACE project: Learning Analytics Community Exchange. The workshop focused on privacy and ethics issues that arise from the use of learning analytics.

This is such an important topic that I will do a full blog post on it later. In the meantime, if you are interested in this topic, see the LACE report: Is Privacy a Show-stopper for Learning Analytics? A Review of Current Issues and their Solutions.

The foyer of the Gresham Hotel

The foyer of the Gresham Hotel

Bits and Pieces

There were several other interesting activities at the conference that are worth reporting:

Pre-conference workshop for young scholars. This was an interesting forum where editors of three of the journals in the field discussed with young (or more accurately, new) scholars how to get published.

Book and wine session This informal late evening session provided an opportunity for participants to share their reviews of interesting books. This is an event that could be expanded to cover both ‘classics’ in the field, as well as books on new developments.

Posters There were about a dozen posters. Again, I would like to see more posters at conferences such as this. A well designed poster can be read in a couple of minutes and impart as much if not more information than a 20 minute oral presentation, and can be seen by everyone at the conference, unlike a presentation at a parallel session, some of which, such as the horrible ‘speed-dating’ sessions, resembled having a fire hose of information turned on you – or am I just a visual learner?

Given that so many new people are moving into online and open learning all the time, much more needs to be done at conferences such as this to encourage sessions where prior knowledge and best practices are brought to the attention of new participants.

Conclusions

Overall, this was another excellent conference from EDEN in a wonderful location (it is the first time I have been immersed into Turkish baths). The next one will be next year in Jönköping, southern Sweden.

Art Nouveau stained glass windows at the Hotel Gellert

Art Nouveau stained glass windows at the Hotel Gellert

All photos: Tony Bates

Technology and alienation: symptoms, causes and a framework for discussion

Edvard Munch's The Scream (public domain) Location: National Gallery, Norway

Edvard Munch’s The Scream (public domain)
Location: National Gallery, Norway

This is the second post on the topic of technology, alienation and the role of education, with a particular focus on the consequences for teaching and learning. The first post was a general introduction to the topic. This post focuses on how technology can lead to alienation, and provides a framework for discussing the possibility of technology alienation in online learning and how to deal with it.

What do I mean by ‘alienation’?

Alienation is a term that has been around for some time. Karl Marx described alienation as the perception by people that they are becoming increasingly unable to control the social forces that shape their lives. Ultimately, highly alienated workers come to lose the sense that they can control any aspect of their lives, whether at work or at home, and become highly self-estranged. Such people are profoundly discontent, prone to alcohol and drug abuse, mental illness, violence, and the support of extreme social and political movements (Macionis and Plummer, 2012). Although Marx had an industrial society in mind, the definition works equally well to describe some of the negative effects of a digital society, as we shall see.

Causes

There are of course many different but related causes of alienation today:

  • the increasing inequality in wealth and in particular the perception by unemployed or low paid workers that they are being ‘passed by’ or not included in the wealth-generating economy. The feeling is particularly strong among workers who previously had well paid jobs (or expectations of well paid jobs) in manufacturing but have seen those jobs disappear in their lifetime. However, there are now also growing numbers of well educated younger people struggling to find well paid work while at the same time carrying a large debt as a result of increasingly expensive higher education;
  • one reason for the loss of manufacturing jobs is the effect of globalization: jobs going abroad to countries where the cost of labour is lower;
  • dysfunctional political systems are another factor, where people feel that they have little or no control over decisions made by government, that government is controlled by those with power and money, and political power is used to protect the ‘elites’;
  • lastly, and the main consideration in these posts, the role of technology, which operates in a number of ways that create alienation:
    • the most immediate is its role in replacing workers, originally in manufacturing, but now increasingly in service or even professional areas of work, including education;
    • a more subtle but nevertheless very powerful way in which technology leads to alienation is in controlling what we do, and in particular removing choice or decision-making from individuals. I will give some examples later;
    • lastly, many people are feeling increasingly exploited by technology companies collecting personal data and using it for commercial purposes or even to deny services such as insurance; in particular, the benefits to the end-user of technology seem very small compared to the large profits made by the companies that provide the services.

Symptoms

Here are some examples of how technology leads to alienation.

There have been several cases where intimate images of people have been posted on the Internet, without permission, and yet it has been impossible for the victims to get the images removed, at least until well after the damage has been done. The Erin Andrews case is the most recent, and the suicide of the 15 year old Amanda Todd is another example. These are extreme cases, but illustrate the perception that we have less and less control over social media and its potentially negative impact on their lives.

Sometimes the alienation comes from decisions made by engineers that pre-empt or deny human decision-making. I have always driven BMWs. Even when I had little money, I would buy a second hand BMW, mainly because of its superb engineering. However, I am driven crazy by my latest purchase. The ignition switches off automatically when I stop the car and automatically switches on again when I take my foot off the brake. One day I drove into my garage. I had stopped the car, and turned round to get something off the back seat. I took my foot off the brake and the car lurched forward and hit the freezer we have in the garage. If I had been on the street and done that, I could well have hit another car or even a pedestrian. The car also automatically locks the passenger doors. I have parked the car and started to walk away only to see my passengers pounding on the window to get out. I could cite nearly a hundred instances from this one car of decisions made by engineers that I don’t want made for me. In most cases (but not all) these default conditions can be changed, but that requires going through a 600 page printed manual. Furthermore these ‘features’ all cost money to install, money I would rather not pay if I had a choice.

We are just starting to see similar decisions by engineers creeping into online learning. One of the most popular uses of data analytics is to identify students ‘at risk’ of non-completion. As with the features in a car, there are potential benefits in this. However, the danger is that decisions based on correlations of other students’ previous behaviour with course completion may end up denying access to a program for a student considered ‘at risk’ but who may nevertheless might well succeed. In particular it could negatively profile black students in the USA, aboriginal students in Canada, or students from low income families.

A framework for discussion

I am dealing here with a highly emotive issue, and one where there will be many different and often contradictory perspectives. Let’s start with the ‘moral’ or ‘value’ issues. I start from the position that alienation is to be avoided if at all possible. It leads to destructive forces. In education in particular, alienation is the opposite of engagement, and for me, engagement is critical for student success. On the other hand, if people are really suffering, then alienation may well be a necessary starting point on the road to change or revolution. So it is difficult to adopt an objective stance to this topic. I want therefore to focus the discussion around the following issues:

  • what are the main developments in online learning that are occurring or will occur over the next few years?
  • who are the main drivers of change in this area?
  • what is the main value proposition? Why is this area being promoted? Who stands to benefit most from this development?
  • what are the risks or what is the downside of these developments? In particular, what is the risk that such developments may actually increase alienation in learners?

I will look at each of the following developments in the next series of blog posts within this framework, developments in online learning that have great promise but at the same time could, if not carefully managed, end up increasing alienation:

  • competency-based learning;
  • personalised and adaptive learning;
  • learning analytics;
  • online assessment methods (badges, machine marking, e-proctoring, e-portfolios, etc.);
  • unbundling of educational services

I will then end this series of posts with a discussion of ‘defensive’ strategies for learners and educators to deal with the negative impact of technology in a digital age.

References

Macionis, J. and Plummer, K. (2012) Sociology: A Global Introduction Don Mills ON: Pearson Education

Automation or empowerment: online learning at the crossroads

Image: Applift

Image: AppLift, 2015

You are probably, like me, getting tired of the different predictions for 2016. So I’m not going to do my usual look forward for the year for individual developments in online learning. Instead, I want to raise a fundamental question about which direction online learning should be heading in the future, because the next year could turn out to be very significant in determining the future of online learning.

The key question we face is whether online learning should aim to replace teachers and instructors through automation, or whether technology should be used to empower not only teachers but also learners. Of course, the answer will always be a mix of both, but getting the balance right is critical.

An old but increasingly important question

This question, automation or human empowerment, is not new. It was raised by B.F. Skinner (1968) when he developed teaching machines in the early 1960s. He thought teaching machines would eventually replace teachers. On the other hand, Seymour Papert (1980) wanted computing to empower learners, not to teach them directly. In the early 1980s Papert got children to write computer code to improve the way they think and to solve problems. Papert was strongly influenced by Jean Piaget’s theory of cognitive development, and in particular that children constructed rather than absorbed knowledge.

In the 1980s, as personal computers became more common, computer-assisted learning (CAL or CAD) became popular, using computer-marked tests and early forms of adaptive learning. Also in the 1980s the first developments in artificial intelligence were applied, in the form of intelligent math tutoring. Great predictions were made then, as now, about the potential of AI to replace teachers.

Then along came the Internet. Following my first introduction to the Internet in a friend’s basement in Vancouver, I published an article in the first edition of the Journal of Distance Education, entitled ‘Computer-assisted learning or communications: which way for IT in distance education?’ (1986). In this paper I argued that the real value of the Internet and computing was to enable asynchronous interaction and communication between teacher and learners, and between learners themselves, rather than as teaching machines. This push towards a more constructivist approach to the use of computing in education was encapsulated in Mason and Kaye’s book, Mindweave (1989). Linda Harasim has since argued that online collaborative learning is an important theory of learning in its own right (Harasim, 2012).

In the 1990s, David Noble of York University attacked online learning in particular for turning universities into ‘Digital Diploma Mills’:

‘universities are not only undergoing a technological transformation. Beneath that change, and camouflaged by it, lies another: the commercialization of higher education.’

Noble (1998) argued that

‘high technology, at these universities, is often used not to ……improve teaching and research, but to replace the visions and voices of less-prestigious faculty with the second-hand and reified product of academic “superstars”.

However, contrary to Noble’s warnings, for fifteen years most university online courses followed more the route of interaction and communication between teachers and students than computer-assisted learning or video lectures, and Noble’s arguments were easily dismissed or forgotten.

Then along came lecture capture and with it, in 2011, Massive Open Online Courses (xMOOCs) from Coursera, Udacity and edX, driven by elite, highly selective universities, with their claims of making the best professors in the world available to everyone for free. Noble’s nightmare suddenly became very real. At the same time, these MOOCs have resulted in much more interest in big data, learning analytics, a revival of adaptive learning, and claims that artificial intelligence will revolutionize education, since automation is essential for managing such massive courses.

Thus we are now seeing a big swing back to the automation of learning, driven by powerful computing developments, Silicon Valley start-up thinking, and a sustained political push from those that want to commercialize education (more on this later). Underlying these developments is a fundamental conflict of philosophies and pedagogies, with automation being driven by an objectivist/behaviourist view of the world, compared with the constructivist approaches of online collaborative learning.

In other words, there are increasingly stark choices to be made about the future of online learning. Indeed, it is almost too late – I fear the forces of automation are winning – which is why 2016 will be such a pivotal year in this debate.

Automation and the commercialization of education

These developments in technology are being accompanied by a big push in the United States, China, India and other countries towards the commercialization of online learning. In other words, education is being seen increasingly as a commodity that can be bought and sold. This is not through the previous and largely discredited digital diploma mills of the for-profit online universities such as the University of Phoenix that David Noble feared, but rather through the encouragement and support of commercial computer companies moving into the education field, companies such as Coursera, Lynda.com and Udacity.

Audrey Watters and EdSurge both produced lists of EdTech ‘deals’ in 2015 totalling between $1-$2 billion. Yes, that’s right, that’s $1-$2 billion in investment in private ed tech companies in the USA (and China) in one year alone. At the same time, entrepreneurs are struggling to develop sustainable business models for ed tech investment, because with education funded publicly, a ‘true’ market is restricted. Politicians, entrepreneurs and policy makers on the right in the USA increasingly see a move to automation as a way of reducing government expenditure on education, and one means by which to ‘free up the market’.

Another development that threatens the public education model is the move by very rich entrepreneurs such as the Gates, the Hewletts and the Zuckerbergs to move their massive personal wealth into ‘charitable’ foundations or corporations and use this money for their pet ‘educational’ initiatives that also have indirect benefits for their businesses. Ian McGugan (2015) in the Globe and Mail newspaper estimates that the Chan Zuckerberg Initiative is worth potentially $45 billion, and one of its purposes is to promote the personalization of learning (another name hi-jacked by computer scientists; it’s a more human way of describing adaptive learning). Since one way Facebook makes its money is by selling personal data, forgive my suspicions that the Zuckerberg initiative is a not-so-obvious way of collecting data on future high earners. At the same time, the Chang Zuckerberg initiative enables the Zuckerberg’s to avoid paying tax on their profits from Facebook. Instead then of paying taxes that could be used to support public education, these immensely rich foundations enable a few entrepreneurs to set the agenda for how computing will be used in education.

Why not?

Technology is disrupting nearly every other business and profession, so why not education? Higher education in particular requires a huge amount of money, mostly raised through taxes and tuition fees, and it is difficult to tie results directly to investment. Surely we should be looking at ways in which technology can change higher education so that it is more accessible, more affordable and more effective in developing the knowledge and skills required in today’s and tomorrow’s society?

Absolutely. It is not so much the need for change that I am challenging, but the means by which this change is being promoted. In essence, a move to automated learning, while saving costs, will not improve the learning that matters, and particularly the outcomes needed in a digital age, namely, the high level intellectual skills of critical thinking, innovation, entrepreneurship, problem-solving , high-level multimedia communication, and above all, effective knowledge management.

To understand why automated approaches to learning are inappropriate to the needs of the 21st century we need to look particularly at the tools and methods being proposed.

The problems with automating learning

The main challenge for computer-directed learning such as information transmission and management through Internet-distributed video lectures, computer-marked assessments, adaptive learning, learning analytics, and artificial intelligence is that they are based on a model of learning that has limited applications. Behaviourism works well in assisting rote memory and basic levels of comprehension, but does not enable or facilitate deep learning, critical thinking and the other skills that are essential for learners in a digital age.

R. and D. Susskind (2015) in particular argue that there is a new age in artificial intelligence and adaptive learning driven primarily by what they call the brute force of more powerful computing. Why AI failed so dramatically in the 1980s, they argue, was because computer scientists tried to mimic the way that humans think, and computers then did not have the capacity to handle information in the way they do now. When however we use the power of today’s computing, it can solve previously intractable problems through analysis of massive amounts of data in ways that humans had not considered.

There are several problems with this argument. The first is that the Susskinds are correct in that computers operate differently from humans. Computers are mechanical and work basically on a binary operating system. Humans are biological and operate in a far more sophisticated way, capable of language creation as well as language interpretation, and use intuition as well as deductive thinking. Emotion as well as memory drives human behaviour, including learning. Furthermore humans are social animals, and depend heavily on social contact with other humans for learning. In essence humans learn differently from the way machine automation operates.

Unfortunately, computer scientists frequently ignore or are unaware of the research into human learning. In particular they are unaware that learning is largely developmental and constructed, and instead impose an old and less appropriate method of teaching based on behaviourism and an objectivist epistemology. If though we want to develop the skills and knowledge needed in a digital age, we need a more constructivist approach to learning.

Supporters of automation also make another mistake in over-estimating or misunderstanding how AI and learning analytics operate in education. These tools reflect a highly objectivist approach to teaching, where procedures can be analysed and systematised in advance. However, although we know a great deal about learning in general, we still know very little about how thinking and decision-making operate biologically in individual cases. At the same time, although brain research is promising to unlock some of these secrets, most brain scientists argue that while we are beginning to understand the relationship between brain activity and very specific forms of behaviour, there is a huge distance to travel before we can explain how these mechanisms affect learning in general or how an individual learns in particular. There are too many variables (such as emotion, memory, perception, communication, as well as neural activity) at play to find an isomorphic fit between the firing of neurons and computer ‘intelligence’.

The danger then with automation is that we drive humans to learn in ways that best suit how machines operate, and thus deny humans the potential of developing the higher levels of thinking that make humans different from machines. For instance, humans are better than machines at dealing with volatile, uncertain, complex and ambiguous situations, which is where we find ourselves in today’s society.

Lastly, both AI and adaptive learning depend on algorithms that predict or direct human behaviour. These algorithms though are not transparent to the end users. To give an example, learning analytics are being used to identify students at high risk of failure, based on correlations of previous behaviour online by previous students. However, for an individual, should a software program be making the decision as to whether that person is suitable for higher education or a particular course? If so, should that person know the grounds on which they are considered unsuitable and be able to challenge the algorithm or at least the principles on which that algorithm is based? Who makes the decision about these algorithms – a computer scientist using correlated data, or an educator concerned with equitable access? The more we try to automate learning, the greater the danger of unintended consequences, and the more need for educators rather than computer scientists to control the decision-making.

The way forward

In the past, I used to think of computer scientists as colleagues and friends in designing and delivering online learning. I am now increasingly seeing at least some of them as the enemy. This is largely to do with the hubris of Silicon Valley, which believes that computer scientists can solve any problem without knowing anything about the problem itself. MOOCs based on recorded lectures are a perfect example of this, being developed primarily by a few computer scientists from Stanford (and unfortunately blindly copied by many people in universities who should have known better.)

We need to start with the problem, which is how do we prepare learners for the knowledge and skills they will need in today’s society. I have argued (Bates, 2015) that we need to develop, in very large numbers of people, high level intellectual and practical skills that require the construction and development of knowledge, and that enable learners to find, analyse, evaluate and apply knowledge appropriately.

This requires a constructivist approach to learning which cannot be appropriately automated, as it depends on high quality interaction between knowledge experts and learners. There are many ways to accomplish this, and technology can play a leading role, by enabling easy access to knowledge, providing opportunities for practice in experientially-based learning environments, linking communities of scholars and learners together, providing open access to unlimited learning resources, and above all by enabling students to use technology to access, organise and demonstrate their knowledge appropriately.

These activities and approaches do not easily lend themselves to massive economies of scale through automation, although they do enable more effective outcomes and possibly some smaller economies of scale. Automation can be helpful in developing some of the foundations of learning, such as basic comprehension or language acquisition. But at the heart of developing the knowledge and skills needed in today’s society, the role of a human teacher, instructor or guide will remain absolutely essential. Certainly, the roles of teachers and instructors will need to change quite dramatically, teacher training and faculty development will be critical for success, and we need to use technology to enable students to take more responsibility for their own learning, but it is a dangerous illusion to believe that automation is the solution to learning in the 21st century.

Protecting the future

There are several practical steps that need to be taken to prevent the automation of teaching.

  1. Educators – and in particular university presidents and senior civil servants with responsibility for education – need to speak out clearly about the dangers of automation, and the technology alternatives available that still exploit its potential and will lead to greater cost-effectiveness. This is not an argument against the use of technology in education, but the need to use it wisely so we get the kind of educated population we need in the 21st century.
  2. Computer scientists need to show more respect to educators and be less arrogant. This means working collaboratively with educators, and treating them as equals.
  3. We – teachers and educational technologists – need to apply in our own work and disseminate better to those outside education what we already know about effective learning and teaching.
  4. Faculty and teachers need to develop compelling technology alternatives to automation that focus on the skills and knowledge needed in a digital age, such as:
    • experiential learning through virtual reality (e.g. Loyalist College’s training of border service agents)
    • networking learners online with working professionals, to solve real world problems (e.g. by developing a program similar to McMaster’s integrated science program for online/blended delivery)
    • building strong communities of practice through connectivist MOOCs (e.g. on climate change or mental health) to solve global problems
    • empowering students to use social media to research and demonstrate their knowledge through multimedia e-portfolios (e.g. UBC’s ETEC 522)
    • designing openly accessible high quality, student-activated simulations and games but designed and monitored by experts in the subject area.
  5. Governments need to put as much money into research into learning and educational technology as they do into innovation in industry. Without better and more defensible theories of learning suitable for a digital age, we are open to any quack or opportunist who believes he or she has the best snake oil. More importantly, with better theory and knowledge of learning disseminated and applied appropriately, we can have a much more competitive workforce and a more just society.
  6. We need to educate our politicians about the dangers of commercialization in education through the automation of learning and fight for a more equal society where the financial returns on technology applications are more equally shared.
  7. Become edupunks and take back the web from powerful commercial interests by using open source, low cost, easy to use tools in education that protect our privacy and enable learners and teachers to control how they are used.

That should keep you busy in 2016.

Your views are of course welcome – unless you are a bot.

References

Bates, A. (1986) Computer assisted learning or communications: which way for information technology in distance education? Journal of Distance Education Vol. 1, No. 1

Bates, A. (2015) Teaching in a Digital Age Victoria BC: BCcampus

Harasim, L. (2012) Learning Theory and Online Technologies New York/London: Routledge

Mason, R. and Kaye, A (Eds).(1989)  Mindweave: communication, computers and distance education. Oxford: Pergamon

McGugan, I. (2015)Why the Zuckerberg donation is not a bundle of joy, Globe and Mail, December 2

Noble, D. (1998) Digital Diploma Mills, Monthly Review http://monthlyreview.org/product/digital_diploma_mills/

Papert, S. (1980) Mindstorms: Children, Computers and Powerful Ideas New York: Basic Books

Skinner, B. (1968)  The Technology of Teaching, 1968 New York: Appleton-Century-Crofts

Susskind, R. and Susskind, D. (2015) The Future of the Professions: How Technology will Change the Work of Human Experts Oxford UK: Oxford University Press

Watters, A. (2015) The Business of EdTech, Hack Edu, undated http://2015trends.hackeducation.com/business.html

Winters, M. (2015) Christmas Bonus! US Edtech Sets Record With $1.85 Billion Raised in 2015 EdSurge, December 21 https://www.edsurge.com/news/2015-12-21-christmas-bonus-us-edtech-sets-record-with-1-85-billion-raised-in-2015