December 16, 2017

Virtual Reality and education: some thoughts

I spent a very interesting evening this week at a Vancouver VR Community event at Mobify‘s headquarters in downtown Vancouver. Mobify is a provider of progressive web apps for e-commerce and has a really cool area for events such as this one, with lots of open spaces.

Vancouver is part of a growing North West Pacific Silicon Valley, and there are now over 500 members of the Vancouver VR community, which indicates how much activity and development are going into VR, at least in this region. 

The event was a mix of show and tell, and an opportunity to play with and experience some VR programs. Most of the applications available to play with at the VR event were typically combat games (including a very realistic one-on-one boxing encounter) but I was more interested in possible educational applications (although the boxing app might come in useful on a dark night on campus).

I particularly enjoyed using Google Blocks, a free software program for developing 3D models, that was being demonstrated by  Scott Banducci who runs a company that hosts VR events (VRtogo). With the headset on and a couple of hand-operated panels that include a colouring palette and tools for moving and stretching objects, it was easy even for a novice such as me to create in a few minutes a really cool 3D model of a plane. There is an excellent introductory video on the Google Blocks web site that explains the process. 

This was my first visit and I hardly knew anyone there (I was the oldest person by at least 40 years). I was hoping to meet someone from one of the many educational institutions in the Vancouver area who might be interested in using VR for teaching and learning but most of the people there not surprisingly were developers or producers of VR. Nevertheless this seems like a great community of practice and I strongly recommend anyone in the Vancouver area interested in the educational use of VR to join. The next event is at Mobify at 6.15 pm on August 22.

In the meantime, here are some of my thoughts about the use of VR, for what they are worth.

  1. VR is not just a fad that will disappear. There are already a large number of commercial applications, mainly in entertainment and public relations, but also increasingly for specific areas of training (more on that below). There is already a lot of excellent, off-the-shelf software for creating VR environments, and the cost of hardware is dropping rapidly (although good quality headsets and other equipment are still probably too expensive for required use by large numbers of students).
  2. What killed earlier two-dimensional VR developments such as Second Life for widespread educational use was the high cost and difficulty of creating the sets and contexts for learning. Thus even if the hardware and software costs for VR are low enough for individual student use, it is the production costs of creating educational contexts and scenarios that are likely to inhibit its use.
  3. Thus most suitable educational applications are likely to be where the cost of alternative or traditional ways of learning are too expensive or too dangerous. In particular, VR would be good for individual, self-learning in contexts where real environments are not easily accessible, or where learners need to cope with strong emotions when making decisions or operating under pressure in real time. Examples might be emergency management, such as shutting down an out-of-control nuclear reactor, or defusing a bomb, or managing a fire on an oil tanker. However, not only will the VR environment have to be realistic, as much attention will need to be paid to creating the specific learning context. The procedure for defusing the bomb and the interaction between learner and the virtual bomb must also be built in to the production. Thus VR may often need to be combined with simulation design and quality media production to be educationally effective, again pushing up the cost. For these reasons, medicine is a likely area for experiment, where traditional training costs are really high or where training is difficult to provide with real patients.
  4. Having said that, we need more experimentation. This is still a relatively new technology, and there may be very simple ways to use it in education that are not costly and meet needs that cannot be easily met in traditional teaching or with other existing technology. For this to happen, though, educators, software developers, and media producers need to come together to play and experiment. The VR Vancouver Community seems to me to be an ideal venue to do this. In the meantime, I can’t wait to see Bad Cookies Pictures VR horror movie when it comes out! Now that will be an immersive experience.

And since originally posting this, I have been directed to the blog post of Ryan Martin, a trainer on Vancouver Island, who has come up with a more comprehensive list of ways to learn through VR, with some excellent links.

If you know of other examples and are willing to share them, I will add the links to this post.

 

What I learned at Drexel University in National Distance Learning Week

A street protester in Philadelphia on election day

A street artist in Philadelphia on election day

Fear and loathing in Philadelphia

On Tuesday and Wednesday last week, I found myself in Philadelphia on U.S. Presidential Election day, and even more importantly, the day after, as the results became known. I was there, not to ‘rig’ the election, as some have rumoured, but to visit one of the leaders in online learning in the USA, Drexel University.

I’m not going to say much more about the election, except to note that as in the rest of the country, Pennsylvania was deeply split, with cities such as Philadelphia and Pittsburg voting strongly for Clinton, and suburban areas, smaller towns and rural areas voting in sufficiently large enough numbers for Trump to just about win the state and its electoral votes. So the election results have caused a certain amount of fear and loathing in Philadelphia, particularly among the university community.

Why Drexel?

Drexel University is a private, nonprofit university ranked among the top 100 universities in the USA. In 2016 it was ranked the 8th most innovative university in the USA by US News and World Report. It has about 26,000 students.

Drexel University was founded in 1891 as the Drexel Institute of Art, Science and Industry, by Philadelphia financier and philanthropist Anthony J. Drexel. The original mission of the institution was to provide educational opportunities in the “practical arts and sciences” for women and men of all backgrounds. It is famed for its co-op education program and its close links to local industry and businesses, and in the past for its acceptance and encouragement of low income students. However in recent years its focus has changed, partly driven by the perceived need to increase its ranking. Today it has very high student tuition fees and a highly selective admission process.

I was there to visit Drexel University Online (DUO), an internal division within the university that serves those students at Drexel taking online courses and programs.

Drexel Online

Drexel University has more than 7,000 online students from all 50 states and more than 20 countries. It offers 140 fully accredited master’s degrees, bachelor’s degrees and certificate programs in a wide range of disciplines. Nursing in particular has a very strong set of online programs. Drexel was an early pioneer of online learning, offering its first fully online master’s degree in 1996.

Drexel University founded National Distance Learning Week, in conjunction with the United States Distance Learning Association, in 2007, and has won several national awards for institution-wide excellence in online education.

As part of Drexel’s contribution to National Distance Learning Week, I was invited as a guest speaker, to talk about ’21st century knowledge and online learning: re-designing teaching for a digital age.’ While at Drexel, I also took the opportunity to see what Drexel is doing with advanced learning technologies.

Advanced use of technologies at Drexel Online

DUO offers faculty a technology lending library, where faculty can try out new devices and evaluate their potential for teaching. This includes an augmented reality headset that combines a cheap ($10-$15), easily assembled cardboard frame into which a mobile phone can be inserted in front of the eyes, enabling augmented reality programs to be delivered at very low cost to the student (provided they already have a mobile phone).

DUO has also developed a very interesting web site, called VirtuallyInspired.org, which showcases a number of innovations in online learning from institutions across North America and around the world.

Here I will describe briefly just a few of Drexel’s own innovative projects, which I hope will inspire you to look in more detail at the VirtuallyInspired web site.

Tina the Avatar

Tina the Avatar

Tina the Avatar

Tina is an avatar of a 28 year old woman in a virtual world who not only responds to questions asked by students but can also be physically examined and will respond according to how she is being treated. The teaching around Tina is broken down into 10 modules, each of which correlate with a body system that students learn about in class. The program serves not only as reinforcement for the principles taught in the course, but also to develop interpersonal skills needed by clinical professionals. Professors are able to view the type of questions asked by the student and how the student reacts to Tina’s responses. They are then able to give the student advice and make recommendations for interpersonal skill improvement.

Synchronous online teaching

Drexel is experimenting with the use of low-cost (US$450) robots (Kubi) combined with iPads to improve the ‘telepresence’ of students in online webinars. In the classroom where the instructor is located, there is an iPad for each remote student locked into a robot that each student can remotely move around the instructor’s classroom. Using Skype and the camera on the student’s computer, the student’s face appears on the iPad. In this way the instructor can see the faces and hear each individual student via the iPad, and the students at home can also see on their screen not only the instructor but also the iPad images of all the other students in the class. This system is already in use at the Michigan State University.

Using Kubi for telepresence at Michigan State University

Using Kubi for telepresence at Michigan State University

Forensic investigation

Students taking a course on forensic investigation can use a branching video sequence to search for clues at a crime scene. Students can do a virtual walk around and inside a house and are asked to observe and interpret what they see, followed by a debriefing afterwards.

These are just a few of the several innovations that Drexel is experimenting with. Others include the use of video simulations in law and nursing, dealing with critical incidents in practice.

Innovation and operations

Drexel University is to be congratulated for two reasons: it has an extensive, ongoing online program that delivers a wide range of courses on a daily basis to over 7,000 students. For most of these courses, the challenges are common to all online post-secondary programs: ensuring that the programs are of high quality and that students succeed. This means applying well known best practices and procedures, using standard tools such as a learning management system, and ensuring that students are well supported by instructors.

At the same time, DUO is investing some of its energy and resources to investigating new ways of designing and delivering online teaching. This means finding like-minded faculty partners who can see the potential of new technologies and who are willing to put in the time and effort to do something different. The challenge here is to evaluate each innovation, to integrate such innovations into regular teaching, and then to ensure the diffusion of successful innovations into a wider range of courses and programs.

Getting the right balance between on-going operations and innovation is a challenge but one that Drexel Online seems more than able to handle.

And lastly, I cannot express enough my appreciation for the kindness and attention paid to me by Susan Aldridge, the Director of DUO, and all her staff during my visit. Elections may come and go, but American hospitality continues for ever.

A full day of experiential learning in action

Marie Bountrogianni, Dean of Chang School, opening the ChangSchoolTalks, 2016

Marie Bountrogianni, Dean of the Chang School of Continuing Education, Ryerson, opening the ChangSchoolTalks, 2016

On Wednesday, February 17, the Chang School of Continuing Studies, Ryerson University, Toronto, put on an impressive one day conference, called ChangSchoolTalks, focused on experiential learning.

The day was organized into the following activities:

  • opening keynote
  • main ‘stage’ talks, of 10-15 minutes in length
  • master classes of 45 minutes length
  • brain dates: one-on-one mentoring on specific topics
  • exhibition.

Opening keynote

Don Tapscott was the opening keynote speaker, who talked about rethinking learning for the networked age. For those who know Tapscott’s work, he covered familiar ground, claiming that higher education must respond to four key leadership challenges/ strategies:

  • the technology revolution, in particular the power of networks and distributed knowledge (‘global intelligence’)
  • the Net Generation, who are ‘wired to think differently’
  • the economic revolution, the move from an industrial to a knowledge-based society
  • the social revolution, including an increasingly unequal distribution of wealth.

He referred in passing to his forthcoming book, ‘The Blockchain Revolution, How the Technology Behind Bitcoin is Changing Money, Business and the World‘, but did not really tie it in to the world of higher education during his talk.

Although I don’t disagree with many of the points he was making about the need for universities to change, I didn’t really leave with anything that I didn’t know already, although others may have found it new and refreshing.

Stage talks

Stage talks were plenary sessions. For me, this was the best part of the day, in terms of what I learned. There were five excellent speakers who used their limited time (10-15 minutes) expertly:

  • Arlene Dickinson, an entrepreneur famous as one of the dragons on the TV program ‘Dragons’ Den’, who talked about leadership
  • James Paul Gee, from Arizona State University, who talked about how participants in multiplayer games collaborated and strategized to solve problems within the games. (I would like to have asked if there was evidence of these problem-solving strategies being successfully transferred outside games, into other kinds of learning environment, but I didn’t get the chance)
  • Steve Gedeon, Associate Professor of Entrepreneurship and Strategy at Ryerson University, who talked about the pedagogy of entrepreneurship. This talk appealed to me the most, because Gedeon argued somewhat convincingly that the pedagogy of entrepreneurship (e.g. Lean Startup approaches to learning) could be applied to many other disciplines
  • Michelle Weise, from the University of Southern New Hampshire, which is one of the fastest growing universities with one of the largest online programs in the USA. She talked about competency-based education. I have mixed feelings myself about competency-based learning, and it was interesting to hear her arguments for it.
  • Marie Bountrogianni, the Dean of the Chang School at Ryerson, was the master of ceremonies, linking all the talks together.

What I liked particularly was the wide range of approaches and topics, with each one well delivered and clearly described in a very short time.

Master Classes

These were two sets of six to seven parallel 45 minute sessions covering the following topics:

  • robot subjugation for beginners (Alex Ferworn)
  • building an effective learning environment (me)
  • building pathways through online competency-based education (Michelle Weise)
  • handling reputation and shame in the social world (Boyd Neil)
  • collaboration and creativity: a challenge in design thinking (Michael Carter)
  • data visualization: what does your business look like? (Michael Martin)
  • big data: a roadmap to be a data scientist (Ayse Bener)
  • a discussion in learning in games (James Paul Gee)
  • the 5Cs of a bustling peer-learning community (Christine Renaud)
  • gamifying learning experiences (Jeremy Friedberg)
  • introductory economics revisited (Eric Kam)
  • ethos as a brand builder and driver for business (Deb Belinsky)
  • if they build it…co-creation as education (Vincent Hui)

As always with parallel sessions, there was always a clash. Because I was giving one, I could go to only one other. However, the list of titles gives some idea of the diversity of ideas and topics covered.

I will say a little bit more about my master class in a separate blog post.

Brain dates

Software made available to the ChangSchoolTalks by the company E-180 enabled participants to book online a one-on-one face-to-face session with a personal mentor, i.e. with anyone attending the conference who had expertise that you would like to access. This was somewhat restricted by a very full agenda for the day, but turned out nevertheless to be very popular.

Exhibition

There was also a small but very interesting set of exhibitors, covering displays of virtual reality, smart materials ,an augmented reality sandbox, a 3D robot labyrinth, 3D printing, and serious gaming.

Comment

The ChangSchoolTalks was a particularly effective showcase for the interests and work being done at Ryerson University.

I came away from the day with my head absolutely buzzing. I was subjected to a torrent of fascinating ideas and developments. What I liked particularly was the diversity of topics, not all of which were specifically educational, but which nevertheless are significant for the future of education.

I would have like a little more time for informal networking, more time for questions and discussion with the ‘stage’ speakers, but there is a lot to be said for the fire hose theory of learning! I learned so much in such a short time, but really need to follow up on most of the topics.

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

Using 2D virtual reality for online role playing

Lake Devo friendship 2

Koechli, L. and Glynn, M. (2014) Diving into Lake Devo: Modes of Representation and Means of Interaction and Reflection in Online Role-Play IRRODL, Vol. 15, No.4

Djafarova, N., Abramowitz, and Bountrogianni, M. (2014) Lake Devo – creation, collaboration and reflection through a customizable online role-play environment Online Learning Consortium, 2014

Introduction

This is the second of a series of blogs spotlighting the work of the Chang School of Continuing Education, Ryerson University, Toronto, in developing innovative online learning initiatives. The first post provided a broad overview of the online learning initiatives at Ryerson.

Lake Devo

Lake Devo was designed by the Centre for Digital Education Strategies at The G. Raymond Chang School of Continuing Education in 2009 to support online role-play activity in an educational context. Lake Devo is essentially a simplified virtual reality tool that is easy to use by both instructors and students.

Learners work synchronously, using visual, audio, and text elements to create avatars and interact in online role-play scenarios. Role-play activity is captured and published as a 2-D “movie” that a group of learners may review, discuss, debate and analyze in Lake Devo’s self-contained debrief area. Lake Devo’s chat tool allows users to check in with each other “out of role” while they are using the tool.

Examples of work produced by learners in Lake Devo can be seen here.

My interest in Lake Devo is that it is a relatively simple way for learners to construct role playing activities for developing a range of skills. The two papers listed above provide a full description of the project. I have worked with the project team to produce this summary.

Why Lake Devo?

Lake Devo was designed for several reasons:

  • instructors found that role-playing using a text-based learning management system was limiting;
  • many instructors lacked familiarity with other possible tools such as 3D virtual worlds;
  • instructors could not commit the time required to learn and integrate most standard 3D virtual worlds into their teaching.

The Lake Devo website was designed to provide an infrastructure for online role-play activities, while allowing for flexibility so that it could be used across disciplines, as well as in multiple delivery formats (e.g., fully online, hybrid, class-room).

Lake Devo is named after an outdoor pond outside the Chang Building in Toronto used by Ryerson students for skating in the winter. The pond was funded in part by the Devonian Foundation of Calgary, hence its nickname by students.

An experiential and constructivist rationale

Lake Devo was designed to meet the following goals:

  1. Provide experience with the knowledge construction process.
  2. Provide experience in and appreciation for multiple perspectives.
  3. Embed learning in realistic and relevant contexts.
  4. Encourage ownership and voice in the learning process.
  5. Embed learning in social experience.
  6. Encourage the use of multiple modes of representation.
  7. Encourage self-awareness of the knowledge construction process.

The project team set out to develop an environment that offered a middle ground between text-only online role-play environments and highly complex 3D virtual environments. They deliberately chose not to design a fully realistic world in which to interact, but rather an environment for role-play dialogue that would offer added channels of expression to support interpersonal communication, as well as an integrated debrief area. In other words, Lake Devo was developed to be a minimalist virtual world that was relatively easy to use while retaining the key characteristics of role playing. In particular it offers:

  • Simple visual and audio modes of representation such as avatars, background images, and sound effects
  • An integrated debrief area that includes a shareable, multimedia artifact, and a forum for discussion

Creating a role play exercise in Lake Devo

There are several steps or stages in developing a role play exercise in Lake Devo:

  • an instructor works out the learning goals and process by which students will use Lake Devo to meet these goals;
  • a ‘community’ must be created, usually a class of students; their names are entered into a database;
  • groups of students within the ‘community’ are either randomly assigned or specified by the instructor;
  • a group leader is identified;
  • learners are issued passwords to access their project;
  • each group member creates a visual representation, or avatar, of his or her role-play character using the Character Creation tool, which allows customization from a menu of physical attributes such as skin tone, hair colour and style, clothing colour, and facial features, from a library of images;
  • the group agrees on a time to meet synchronously online to role-play;
  • the group members participate as their avatars in a spontaneous dialogue by typing in their comments, which forms a “script.” Text during the scripting can be entered as speech, thought, or action;
  • learners may select sounds from a built-in library to insert in the script;.
  • a Backstage Group Chat area assists learners in planning the role-play and discussing logistics as the role-play unfolds;
  • the role-play dialogue is automatically saved, but each learner may edit his or her character’s dialogue after the live role-play activity;
  • once a group has finalized their role-play, they publish it to their Lake Devo Community list in the form of a 2D narrative movie;
  • the movie format allows all to participate in the debriefing, which occurs in a discussion area below each movie.

In most cases, a Lake Devo exercise is a graded, sometimes culminating, project that takes place in the latter half of a course, with a number of weeks allowed for scenario development, planning and, ultimately, the synchronous role play activity and debrief.

What has it been used for?

Lake Devo has been used by instructors and students in the following areas:

  • Interdisciplinary Studies,
  • Retail Management,
  • Fundraising Management,
  • Early Childhood Studies,
  • Food Security,
  • Entrepreneurial Mentoring.

Lake Devo has been used by a total of ten online instructors, for at least eight different courses, involving over 35 sections of students. Instructors have also been involved in user testing for the environment, as well as in demonstrations of the environment for fellow faculty.

Cost

The Lake Devo system was designed internally by staff from the Centre for Digital Education Strategies at Ryerson. It is available for use by instructors and/or students at no cost.

Students and instructors require no special software or equipment to make use of the Lake Devo environment. Internet access and creative ideas for role-play scenarios are all that is needed.

There are some minor ongoing maintenance costs for the Digital Education Strategies Unit. With respect to the use of the site, the main cost then is the up-front instructor time to design their own Lake Devo learning activities.

Feedback

Student reaction has been collected and feedback overall has been positive. In particular both instructors and students have found it easy to use.

While student satisfaction with the features of the environment has remained consistent, the Digital Education Strategies team has adopted a continuous improvement approach to the design of the environment and has fully revised the environment over the past 5 years, in keeping with student feedback. Examples of student responses can be found in the graphic below.

Lake Devo student response 2

Further information

Instructors from other institutions may use Lake Devo. They can request access through the site by completing the “sign up for an account” form on the web site.

For further information please contact either maureen.glynn@ryerson.ca or lkoechli@ryerson.ca