November 18, 2017

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

Webinar recording: How open education will revolutionize higher education

Merlot 2

Last Tuesday I did a Contact North webinar on the above topic. This was the last of five webinars based on my book, Teaching in a Digital Age.

In this webinar, I briefly touched on the following topics that are more extensively covered in Chapter 10 of the book:

  • open textbooks
  • open research and open data
  • OER and MOOCs
  • modularization of learning
  • disaggregation of services
  • new course designs that exploit open educational resources.

My main argument in the webinar is that we are moving to a point where (nearly) all academic and other content will be open, free and easily accessible online. There is no need for subject experts to select and package knowledge for students. Indeed, in a knowledge-based society, we need to teach those skills to students, so that they can continue to learn after graduating. Such a move though radically changes the role of faculty and instructors, and of course demands appropriate changes in course design.

I also raised these two questions throughout the webinar:

  • why are faculty and instructors not making greater use of open resources?
  • what can be done to improve the quality of open educational resources so that they will be used more?

I also ended the webinar by asking participants the following questions:

  1. How could you design your courses to make better use of open resources?
  2. What stops universities from collaborating more in the design and use of open educational resources?
  3. How could open education change the way we offer programs?

A recording of the webinar (56 minutes) can be downloaded here: http://tinyurl.com/zrd6fx6

Disaggregation! Image: © Aaron 'tango' Tan, Flickr, CC Attribution 2.0

Disaggregation!
Image: © Aaron ‘tango’ Tan, Flickr, CC Attribution 2.0

 

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.