November 18, 2017

Tracking innovations in online learning in Canada

Rue St Jean, Québec City. Temperatures ranged from -17 C to -23 C -without wind chill added

I’ve not been blogging much recently because, frankly, I’ve been too busy, and not on the golf course or ski slopes, either. (Yeah, so what happened to my retirement? Failed again).

Assessing the state of online learning in Canada

I am working on two projects at the moment:

These two projects in fact complement one another nicely, with the first aiming to provide a broad and accurate picture of the extent of online learning in Canada, and the other focusing on the more qualitative aspects of innovation in online learning, and all in time for not only for the 150th anniversary of Confederation in Canada (which was really the creation of a new, independent state in North America) but also ICDE’s World Congress on Online Learning in Toronto in October, whose theme is, guess what, Teaching in a Digital Age (now there’s a co-incidence).

Of course, I’m not doing this on my own. In both projects I am working with a great group of people.

Methodology

My mandate for Contact North is to identify 8-12 cases of innovation in online learning from all of Canada other than Ontario. I started of course in British Columbia, early in January, and last week I visited six post-secondary institutions in four cities in Québec.

To find the cases, I have gone to faculty development workshops where instructors showcase their innovations, or I have contacted instructional designers I know in different institutions to recommend cases. The institutions are chosen to reflect provinces, and universities and colleges within each province.

Each visit involves an interview with the instructor responsible for the innovation, and where possible a demonstration or examples of the innovation. (One great thing about online learning is that it leaves a clear footprint that can be captured).

I then write up a short report, using a set of headings provided by Contact North, and then return that to the instructor to ensure that it is accurate. I then submit the case report to Contact North.

I am not sure whether Contact North will publish all the cases I report on its web site, as I will certainly cover much more than 8-12 cases in the course of this project. However, it is hoped that at least some of the instructors featured will showcase their innovations at the World Congress of Online Learning.

Progress to date

I have conducted interviews (but not finished the reports yet) for the following:

British Columbia

  • the use of an online dialectical map to develop argumentation skills in undergraduate science students (Simon Fraser University – SFU)
  • peer evaluation as a learning and assessment strategy for building teamwork skills in business school programs (SFU)
  • the development of a mobile app for teaching the analysis of soil samples (University of British Columbia)
  • PRAXIS: software to enable real-time, team-based decision-making skills through simulations of real-world emergency situations (Justice Institute of British Columbia)

Québec

  • comodal synchronous teaching, enabling students to choose between attending a live lecture or participating at the same time from home/at a distance (Laval University)
  • synchronous online teaching of the use of learning technologies in a teacher education program (Université du Québec à Trois-Rivières – UQTR)
  • achieving high completion rates in a MOOC on the importance of children’s play (UQTR)
  • a blended course on effective face-to-face teaching for in-service teachers (TÉLUQ)
  • use of iBook Author software for content management for cardiology students and faculty in a teaching hospital (Centre Hospitalier Universitaire de Sherbrooke – Sherbrooke University Hospital: CHUS)
  • a decision-making tool to develop active and coherent learning scenarios that leverage the use of learning technologies (Université de Montréal).
  • Mathema-TIC: francophone open educational resources for teaching mathematics in universities and colleges (Université de Montréal).

These visits would not have been possible without the assistance of France Lafleur, an online instructor from UQTR who not only arranged many of the meetings but also did all the driving. Anyone from outside Québec who has tried to drive across the province in winter, and especially tried to navigate and drive to several parts of Montréal the same day, will understand why this help was invaluable.

Response and reaction

Faculty and instructors often receive a lot of criticism for being resistant to change in their teaching. This project however starts from an opposite position. What are faculty and instructors actually doing in terms of innovation in their teaching? What can we learn from this regarding change and the development of new teaching approaches? What works and what doesn’t?

It is dangerous at this stage to start drawing conclusions. This is not a representative selection of even innovative projects, and the project – in terms of my participation – has just started. The definition of innovation is also imprecise. It’s like trying to describe an elephant to someone who’s never seen one: you might find it difficult to imagine, but you’ll know it when you see it.

However, even with such a small sample, some things are obvious:

  • innovation in online teaching is alive and well in Canadian post-secondary education: there is a lot going on. It was not difficult to identify these 11 cases; I could have easily found many more if I had the time;
  • the one common feature across all the instructors I have interviewed is their enthusiasm and passion for their projects. They are all genuinely excited by what they were doing. Their teaching has been galvanised by their involvement in the innovation; 
  • in some of the cases, there are measured improvements in student learning outcomes, or, more importantly, new ’21st century skills’ such as teamwork, evidence-based argumentation, and knowledge management are being developed as a result of the innovation;
  • although again these are early days for me, there seems to be a widening gap between what is actually happening on the ground and what we read or hear about in the literature and at conferences on innovation in online learning. The innovation I am seeing is often built around simple but effective changes, such as a web-based map, or a slight change of teaching approach, such as opening up a lecture class to students who don’t want to – or can’t – come in to the campus on a particular day. However, these innovations are radically changing the dynamics of classroom teaching;
  • blended learning is breaking out all over the place. Most of these cases involve a mix of classroom and online learning, but there is no standard model – such as flipped classrooms – emerging. They all vary quite considerably from each other; 
  • the innovations are still somewhat isolated although a couple have gone beyond the original instructor and have been adopted by colleagues; however there is usually no institutional strategy or process for evaluating innovations and making sure that they are taken up across a wider range of teaching, although instructional designers working together provide one means for doing this. Evaluation of the innovation though is usually just left to the innovator, with all the risks that this entails in terms of objectivity.

Next steps

I still have at least one more case from another institution in British Columbia to follow up, and I now have a backlog of reports to do. I hope to have these all finished by the end of this month.

I have two more trips to organise. The first will be to the prairie provinces:

  • Alberta, Saskatchewan and Manitoba, which I hope to do in mid-March.

The next will be to the Maritimes,

  • Nova Scotia, New Brunswick, PEI, and Newfoundland, which I will do probably in April or May.

No further cases or institutions have been identified at this moment, and I am definitely open to suggestions in these provinces if you have any. The criterion for choice is as follows:

  • The focus is first and foremost on practice, on actual teaching and learning applications – not policy, funding, planning issues, descriptions of broad services, or broader concerns.
  • The interest is in applications of pedagogy using technology for classroom, blended, and online learning with the emphasis on student learning, engagement, assessment, access, etc. The pedagogy is as important as the technology in terms of innovation.
  • The emphasis is on innovative practices that can be replicated or used by other instructors.
  • We are particularly looking for cases where some form of evaluation of the innovation has been conducted or where there is clear evidence of success.

If you can recommend a case that you think fits well these parameters, please drop me a line at tony.bates@ubc.ca.

In the meantime, look out for the case studies being posted to Contact North’s Pocket of Innovation web site over the next few months. There are also more cases from Ontario being done at the same time.

Is networked learning experiential learning?

Image: © Justin Grimes, The Guardian, 2013

Image: © Justin Grimes, The Guardian, 2013

Campbell, G. (2016) Networked learning as experiential learning Educause Review, Vol. 51 No. 1, January 11

This is an interesting if somewhat high level discussion by the Vice-Provost for Learning Innovation at Virginia Commonwealth University, USA, of the importance of networked learning as experiential learning:

the experience of building and participating within a digitally mediated network of discovery and collaboration is an increasingly necessary foundation for all other forms of experiential learning in a digital age. Moreover, the experience of building and participating within a digitally mediated network of discovery is itself a form of experiential learning, indeed a kind of metaexperiential learning that vividly and concretely teaches the experience of networks themselves.

This article might be useful for those who feel a need for a pedagogical or philosophical justification for networked learning. However, I have two reservations about Campbell’s argument which are closely related:

  • Campbell appears in one part of the article to be arguing students need some kind of academic training to understand the underlying nature of digital networking, but he is not too clear in the article about what that entails or indeed what that underlying nature is, beyond the purely technical;
  • second, I struggled to see what the consequences of the argument are for me as a teacher: what should I be doing to ensure that students are using networked learning as experiential learning? Does this happen automatically?

I think Campbell is arguing that instructors should move away from selecting and packaging information for students, and allow them to build knowledge through digital networks both within and outside the academy. I of course agree with this part of the argument, but the hard part is knowing the best ways to do this so that learners achieve the knowledge and skills they will need.

As with all teaching methods, networked learning and/or experiential learning can be done well or badly. I would like to see (a) a more precise description of what networked learning means to Gardner in terms of practice, and (b) some guidelines or principles to support instructors in using networked learning as a form of experiential learning. This needs to go beyond what we know about collaborative learning in online groups, although even the application of what we know about this would be a big step forward for most instructors.

Without a clear analysis of how digital networking results in learning, and how this differs from non-digital networked learning, networked learning runs the risk of being yet another overworked buzzword that really doesn’t help a great deal.

Despite my reservations I encourage you to take a look at this article and see if you can make more sense of it than I have, because I believe that this is a very important development/argument that needs further discussion and critical analysis.

For a more pragmatic take on this topic see:

LaRue, B. and Galindo, S. (2009). ‘Synthesizing Corporate and Higher Education Learning Strategies’. in Rudestam, K. and Schoenholtz-Read, J. (eds.) Handbook of Online Learning: Innovations in  Higher Education and Corporate Training Thousand Oaks, CA: Sage Publications.

 

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



Another perspective on the personalisation of learning online

To see the video recording click on the image

To see the video recording click on the image

I gave a keynote presentation last week at a large educational conference in the Netherlands, Dé Onderwijsdagen’ (Education Days). I was asked to talk about the personalisation of learning. I agreed as I think this is one of many potential advantages of online learning.

However, the personalisation of learning tends to be looked at often through a very narrow lens. I suggest that there are in fact at least seven ways in which online learning can facilitate the personalisation of learning. This is a blog post version of my keynote, which can be seen in full here.

Why personalisation?

Personalisation is one of the buzzwords going around these days in educational circles, like experiential learning or competency-based learning. Sometimes when I look more closely at some of the current buzzwords I end up thinking: ‘Oh, is that what it is? But I’ve always done that – I just haven’t given it that name before.’

However, I think there are good reasons why we should be focusing more on personalisation in post-secondary education:

  • the need to develop a wide range of knowledge and skills in learners for the 21st century;
  • as the system has expanded, so has the diversity of students: in age, language ability, prior learning, and interests;
  • a wider range of modes of delivery for students to choose from (campus, blended, fully online);
  • a wider range of media accessible not only to instructors but also to learners themselves;
  • the need to actively engage a very wide range of preferred learning styles, interests and motivation.

Clearly in such a context one size does not fit all. But with a continuously expanding post-secondary system and more pressures on faculty and instructors, how can we make learning more individualised in a cost-effective manner?

Seven roads to personalisation

I can think of at least seven ways to make learning more personal. In my keynote I discuss the strengths and weaknesess of each of these approaches:.

  • adaptive learning;
  • competency-based learning;
  • virtual personal learning environments;
  • multi-media, multi-mode courses and learning materials;
  • modularisation of courses and learning materials;
  • new qualifications/certification (badges, nanodegrees, etc.);
  • disaggregated services.

There are probably others and I would be interested in your suggestions. However I recommend that you look at the video presentation, as it provides more ‘flesh’ on each of these seven approaches to personalisation.

An overall design approach to personalisation

Personalisation of learning will work best if it is embedded within an overall, coherent learning design, In my keynote I suggest one approach that fully exploits both the potential of online learning and the personalisation of learning:

  • the development of the core skill of knowledge management within a particular subject domain (other skills development could also be included, such as independent learning, research, critical thinking, and 21st century communication)
  • the use of open content by students, guided and supported by the instructor
  • student-generated multi-media content through online project work
  • active online discussion embedded within and across the different student projects
  • assessment through personal e-portfolios and group project assessment.

Such an ‘open’ design allows for greater choice in topics and approaches by learners while still developing the core skills and knowledge needed by our learners in a digital age. Other designs are also of course possible to reach the same kind of overall learning goals.

The role of the instructor though remains crucial, both as a content expert, guiding students and ensuring that they meet the academic needs of the discipline, and in providing feedback and assessment of their learning.

Conclusion

With knowledge continuing to rapidly grow and change, and a wide range of skills as well as knowledge needed in a knowledge-based society, we need new approaches to teaching that address such challenges.

Also because of increased diversity in our students and a wide range of different learning needs, we need to develop more flexible teaching methods and modes of delivery. This will also mean understanding better the differences between media and using them appropriately in our teaching.

Making learning more personal for our students is increasingly important, but it is only one element in new designs for learning. There are in fact many possibilities, limited only by the imagination and vision of teachers and instructors.