May 5, 2016

A full day of experiential learning in action

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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

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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

Spotlight on online experiential learning at Ryerson University

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Lake Devo is one of several e-learning initiatives at Ryerson University

Lake Devo is one of several e-learning initiatives at Ryerson University

A week or so ago, I had the opportunity to visit the Digital Education Strategies team at the G. Raymond Chang School of Continuing Education at Ryerson University, Toronto.

Ryerson is well known for its DMZ (formerly the Digital Media Zone), one of Canada’s largest business incubators for emerging tech start-ups, but it is by no means the only centre of innovation at Ryerson. As well as being responsible for the design of online learning courses at Ryerson, the Centre for Digital Education Strategies (CDES) has several very interesting e-learning initiatives. 

Online courses

The ‘bread and butter’ work of the CDES is the over 400 online courses, including around 300 degree-credit online and hybrid courses, four part-time degree online and blended programs, 23 fully online certificates, and 22 blended certificates. CDES serves roughly 23,000 online course enrolments a year. Ryerson recently moved from Blackboard to Desire2Learn learning management system to support most of its online courses.

Because of its expertise in online course design, Chang School’s Digital Education Strategies team has been engaged in a number of other innovative e-learning initiatives. The DES team has also built business efficiency tools and interactive learning applications. Each of these deserves a blog post on its own, but in this post I want to give a quick overview of some of the other work of the Centre.

1. Lake Devo

Lake Devo is a virtual learning environment enabling online role-play activity in an educational context. Learners work synchronously, using visual, audio, and text elements to create avatars and interact in online role-play scenarios.

The Lake Devo environment is fully equipped to allow an instructor to set up his/her class as an online collaborative community. He/she may enter students’ information, configure working groups and have the system issue login information to all users.

Lake Devo has been used by a total of ten online instructors, for at least eight different courses, involving over 35 sections of students. Students have developed over 100 different scenarios in Lake Devo (see “Gallery” for examples). 

 2. The Law Practice Program

This unique alternative to traditional articling was established by the Law Society of Upper Canada (LSUC) and Ryerson University to provide new options and flexibility to meet the legal profession’s licensing requirements for law graduates in Ontario.

The program features interactive web-based collaboration tasks that replicate the experience of working in a law firm. This virtual firm activity is combined with expert guidance and mentorship to equip candidates with the skills and competencies required for effective practice. For a promo video, see: https://www.youtube.com/watch?v=eKsu6P3ZUVQ

 3. Serious games

Mental health assessment during a home visit’ is a video-based game in which users practice their skills in a setting that is realistic and allows the user to make clinical choices within a safe environment.

This is another collaborative project involving Ryerson nursing faculty and professors from George Brown College and Centennial College.

4. Professional Development for Online Instructors

 As part of its commitment to offer high quality learning experiences for students, the CDES offers professional development for online instructors. Teaching Adult Learners Online (TALO) is a four-week, hands-on program designed to model effective facilitation techniques, and provide instructors with insight into the learning experiences of online students, while promoting an engaging community of practice.

Drawing on promising practices in online pedagogy and examples from leading open resources such as CU Open, TALO offers a unique experience that is helping to increase online instructor capacity and diversity.

I will do a more complete blog post on each of these initiatives over the next week or so.

Other initiatives

The Centre for Digital Education Strategies is involved in many other e-learning initiatives, including:

  • Providing training on foundations of instructional design principles to Pearson Canada Inc. employees.
  • Free multi-media e-learning modules to help Canadians boost their financial knowledge and plan for their future financial security for the Financial Consumer Agency of Canada (see: http://www.fcac-acfc.gc.ca/Eng/resources/educationalPrograms/financialBasics/Pages/elearning-apprligne.aspx)
  • A project for the Bombay Stock Exchange to design a train-the-trainer program for effective delivery of a hybrid curriculum on intercultural communication skills for the workplace.
  • A partnership with the University of the West Indies provided students in 12 Caribbean countries with access to a high-quality online programming for their Bachelor of Science in Nursing (BScN). 
  • Entrepreneurial mentor training through an online seminar using interactive case studies and role play.

Further information

 More details of the work of the Centre for Digital Education Strategies can be found here: http://ce-online.ryerson.ca/ce/default.aspx?id=3665

More detailed posts on each of the four projects listed above will follow shortly.

Book review: Teaching and Learning in Digital Worlds

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Workspace in the EVEA3D platform

Workspace in the EVEA3D platform

Gisbert, T. and Bullen, M. (2015) Teaching and Learning in Digital Worlds: Strategies and Issues in Higher Education Tarragona Spain: Publicacions Universitat Rovira i Virgili (pdf version available online for 2.84 Euros).

What the book is about

From the Introduction

[The book] examines the teaching and learning process in 3D virtual learning environments from both the theoretical and practical points of view. It is divided into four sections:

  • the first section discusses education in the 21st century from the perspective of learners in a digital society and examines the basic competences students need to respond to the personal and professional challenges they are likely to face. It also explores the issue of quality…..
  • the second section focuses on the educational and teaching strategies higher education professionals must take into account when developing educational processes in technology environments…in such environments simulation will be our best teaching strategy and evaluation our greatest challenge.
  • the third section explores the use of 3D virtual environments in education in general and in higher education in particular….
  • The fourth section examines the range of experiences we consider to be good practice when applying 3D technological environments to the teaching of competences at secondary and tertiary levels of education both nationally and internationally.

However, this doesn’t quite capture for me what the book is really about, so I will discuss a little more closely below some of the themes addressed by individual chapters.

As a point of clarification, I will use the term ‘immersive environments’ as a shorthand to describe simulations, games and virtual reality, a point I will come back to in my comments at the end of this post.

Who wrote it

The book is edited by Mercè Gisbert of the Universitat Rovira i Virgili in Catalonia, Spain, and Canadian Mark Bullen, formerly of the University of British Columbia and the Commonwealth of Learning. However, the majority of chapters are based on a study (Simul@) funded by the Spanish Ministry of Education and coordinated by Universitat Rovira i Virgili, but involving universities in Spain, Germany, and Portugal, thus providing a valuable insight into the thinking about immersive environments for education in Europe.

Full disclosure: I wrote a short prologue for the book.

Themes covered in the book

Rather than a chapter-by-chapter summary, I have selected certain themes that re-occur through the book.

1. Digital learners

There is a lot of discussion in the book about the nature of digital learners and their ‘readiness’ for learning through digital technologies. In particular, Bullen and Morgan summarise the conflicting views and the research around digital natives and digital immigrants, and provide a more ‘nuanced’ profile of categories of digital learners.  Martinez and Espinal in their chapter provide a detailed description of digital competence and how to assess it. Throughout the book there is emphasis on the need to ensure that learners have the necessary ‘digital competences’ to benefit fully from the use of immersive technologies for learning purposes (although the same applies to teachers, of course). For instance, de Oliveira et al., in their chapter, identify various components of digital competences.

2. Competences

One of the strengths of the book is that several authors make the point that the main educational value of immersive learning environments is for the development of ‘general competences’ such as learning to learn, teamwork, communication, problem solving and decision-making. Astigarraga provides a very good overview of the definition, identification and evaluation of competences, and Isus et al. develop this further with a chapter on evaluating the competences of teamwork and self-management. Larraz and Esteve devote their whole chapter to evaluating digital competence in immersive environments. These chapters will be valuable for anyone interested in competency-based learning, whether or not using immersive learning environments.

3. Key educational principles and affordances of immersive technologies

Another strength of the book is that several authors related the features of immersive environments to possible educational affordances, and the educational principles needed to exploit such affordances. Camacho and Esteve-Gonzáles have a list of 14 educational reasons for using immersive environments for learning and Cervera and Cela-Ranilla have collated from the general research literature about 15 key pedagogical principles ‘to be observed during learning processes’ when using immersive technologies for learning purposes.

4. Planning and implementing virtual learning environments

Towards the end of the book there are several chapters focusing on more practical issues. Marqués et al. describe the planning and implementation of a virtual world built in Sloodle, which combines OpenSim with Moodle, for educating both physical education and business management students. Estevez-González et al. take this further with a chapter on the tools used in Sloodle and the necessary steps needed to integrate OpenSim and Moodle. Lastly, Cela-Ranilla and Estevez-Gonzàlez provide an educational rationale for the design of the project. Garcia and Martin set out a design methodology for an immersive learning environment.

5. Experiences and good practices

The book ends with five chapters that describe actual applications of immersive learning environments, including PolyU developed at Hong Kong Polytechnic University (hotel and tourism management), a review of applications in economics and business courses, the use of an educational platform Virt-UAM developed at Universidad Autònoma de Madrid, and applications in law and psychology, and lastly a review of applications in secondary/high school education.

Critique

First, this is a very welcome and timely publication for several reasons:

  • it sets out very clearly the pedagogical rationale for the use of immersive learning environments;
  • it links immersive technologies very strongly to the development of competences;
  • it provides practical advice on the planning and implementation of immersive learning environments;
  • it provides a welcome European perspective on the topic.

From a personal perspective, it complements very nicely my own open, online textbook, Teaching in a Digital Age, where, because of space and time issues, I was unable to give this topic the treatment it deserves. Although not an open textbook, it is very accessible, available online for less than three euros ($3-4).

Given the book is mostly written by people for whom English is a second language, the chapters are clearly and well written, mostly free of the European English associated with European Commission projects.

Nevertheless, the European Commission has adopted the term competence rather than competency, which really irritates me, and this term is used throughout the book, when what the authors are really talking about are skills. Competent is an adjective meaning a minimal capacity to do something; incompetent is more frequently used in English English, and it is used to describe inadequacy. What we are really talking about here are skills, not competence. Skills have no limit, while competence tends to be categorical: you either have it or you don’t, which is why competency-based learning often requires 100% pass-rates. But skills such as problem-solving can get better and better, and that’s what we should be striving for in higher education, not a minimal pass requirement.

The editors have done a good job in ensuring that there is a coherence and progression between the different chapters, always a challenge in a multiple-authored book. However, I would have liked a summary chapter from the editors that pulled all the threads together, and also some more information about the authors.

The books strength and its weakness is the academic nature of the book, with more focus on theory, competences and affordances, and less on the actual technology design issues, although to be fair these start to appear at the back of the book. I would have liked to have seen more integration in the writing throughout the book between theory and practice.

The main omission is any discussion of costs in planning and developing immersive learning environments, which are time demanding of both learners and teachers. There are clear economies of scale that need to be employed to justify the high cost of initial design. If a virtual world and allied teaching strategies can be shared across several courses or even disciplines, the cost becomes more acceptable. There is also a high cost for students in terms of the time needed to master the technology and its educational applications if they only get one course in a virtual world. So it is a pity that there was so little discussion of costs and time in the book, and about the transfer of innovation into mainstream practice, which are significant challenges for the wider adoption of immersive technologies in education.

Nevertheless, this is a book I would highly recommend to all concerned about the implications of technology for learning design. Virtual learning environments hold great promise. We need more concerted efforts in higher education to use immersive learning environments, and this book is an essential guide.

Investments in game-based learning and learning technology continues to grow

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Growth in learning technology investment 2

Banville, L. (2015) Reports Highlight Strong Growth and Investor Interest in China, U.S. Game-based Learning Games and Learning, May 31

This is an interesting report that summarizes three major market research reports about investment in game-based learning particularly, and learning technologies in general.

It covers recent reports from the following three market research organizations:

Main results:

  • worldwide sales of game-based learning products hit $1.7 billion in 2013 (Ambient)
  • future growth in game-based learning products is expected to grow between 7%-16% per annum
  • global private investment in learning technologies generally topped $2.4 billion in 2014 (Ambient)
  • consumers are the top buyers of edugame packaged content, particularly in the early childhood market (Ambient)
  • the emergence of easy-to-use mobile game-building tools supports the cultural shift towards game-creation as an educational experience (Ambient).

One driving factor in the most recent growth has been investment in mobile learning companies in China.

Comment

Ambient Insight in particular has been extremely accurate in identifying investment trends in learning technologies.

Mobile learning and game-based learning look to be the main bets for commercial growth, followed by learning analytics.

The big question is though whether these investments will drive change in education, or whether the education market will reject one or more of these developments, either because they are too costly or difficult to implement (e.g. very high training costs to get teachers or learners to use them well) or because such technologies do not meet the actual learning needs of students.

Another question is whether the level of investment in any single educational game will be large enough to bring about major changes in learning. The danger is of spreading investment too thinly across too many games to have a major impact, focusing on low levels of learning such as memorization, rather than developing critical thinking or problem solving skills. Ambient Insight’s comment that easy-to-use mobile game-building tools are increasing suggests though that this will be an exciting area that is ripe for growth – and for research and evaluation. I just hope that educators and learners will be as involved as software developers in designing such educational games.