September 20, 2018

How serious should we be about serious games in online learning?

An excerpt from the video game ‘Therapeutic Communication and Mental Health Assessment’ developed at Ryerson University

In the 2017 national survey of online learning in post-secondary education, and indeed in the Pockets of Innovation project, serious games were hardly mentioned as being used in Canadian universities or colleges. Yet there was evidence from the Chang School Talks in Toronto earlier this month that there is good reason to be taking serious games more seriously in online learning.

What are serious games?

The following definition from the Financial Times Lexicon is as good a definition as any:

Serious games are games designed for a purpose beyond pure entertainment. They use the motivation levers of game design – such as competition, curiosity, collaboration, individual challenge – and game media, including board games through physical representation or video games, through avatars and 3D immersion, to enhance the motivation of participants to engage in complex or boring tasks. Serious games are therefore used in a variety of professional situations such as education, training,  assessment, recruitment, knowledge management, innovation and scientific research. 

So serious games are not solely educational, nor necessarily online, but they can be both.

Why are serious games not used more in online learning?

Well, partly because some see serious games as an oxymoron. How can a game be serious? This may seem trivial, but many game designers fear that a focus on education risks killing the main element of a game, its fun. Similarly, many instructors fear that learning could easily be trivialised through games or that games can cover only a very limited part of what learning should be about – it can’t all be fun. 

Another more pragmatic reason is cost and quality. The best selling video games for instance cost millions of dollars to produce, on a scale similar to mainstream movies. What is the compelling business plan for educational games? And if games are produced cheaply, won’t the quality – in terms of production standards, narrative/plot, visuals, and learner engagement – suffer, thus making them unattractive for learners?

However, probably the main reason is that most educators simply do not know enough about serious games: what exists, how they can be used, nor how to design them. For this reason, the ChangSchoolTalks, organised each year by the School of Continuing Studies at Ryerson University, this year focused on serious games.

The conference

The conference, held on May 3rd in Toronto, consisted of nine key speakers who have had extensive experience with serious games, organised in three themes:

  • higher education
  • health care
  • corporate

The presentations were followed by a panel debate and question and answer session. The speakers were:

This proved to be an amazingly well-selected group of speakers on the topic. In one session run by Sylvester Arnab, he had the audience inventing a game within 30 seconds. Teams of two were given a range of  existing games or game concepts (such as Dictionary or Jeopardy) and a topic (such as international relations) and had up to two minutes to create an educational game. The winning team (in less than 30 seconds) required online students in political sciences to represent a country and suggest how they should respond to selected Tweets from Donald Trump.

I mentioned in an earlier blog that I suffered from such information overload from recent conferences that I had to go and lie down. It was at this conference where that happened! It has taken three weeks for me even to begin fully processing what I learned.

What did I learn?

Probably the most important thing is that there is a whole, vibrant world of serious games outside of education, and at the same time there are many possible and realistic applications for serious games in education, and particularly in online learning. So, yes, we should be taking serious games much more seriously in online learning – but we need to do it carefully and professionally.

The second lesson I learned is that excellent online serious games can be developed without spending ridiculous amounts of money (see some examples below). At the same time, there is a high degree of risk. There is no sure way of predicting in advance that a new game will be successful. Some low-cost simple games can work well; some expensively produced games can easily flop. This means careful testing and feedback during development.

For these and other reasons, research being conducted at Ryerson University and funded by eCampus Ontario is particularly important. Naza Djafarova and colleagues at Ryerson’s Chang School of Continuing Education are conducting research to develop a game design guide to enhance the process by which multidisciplinary teams, engaged in the pre-production stage, approach the design of a serious game. They have developed a process called the Art of Game Design methodology, for multidisciplinary teams involved in the design of serious games, and appraised in participatory workshops.

The Chang School has already developed a few prototype games, including:

  • Lake Devo, 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.
  • Skills Practice: A Home Visit that promotes the application of knowledge and skills related to establishing a therapeutic nurse-client relationship and completing a mental health assessment. Students assume the role of a community health nurse assigned to complete a home visit. Working with nurses and professors from George Brown College, Centennial College this project is working to establish a ‘virtual hospital’ with several serious games focused on maternity issues.

Thus serious games are a relatively high risk, high return activity for online learning. This requires building on best practices in games design, both within and outside education, sharing, and collaboration. However, as we move more and more towards skills development, experiential learning, and problem-solving, serious games will play an increasingly important role in online learning. Best to start now.

Assessing the dangers of AI applications in education

Image: CaspionReport

Lynch, J. (2017) How AI will destroy education, buZZrobot, 13 November

I’m a bit slow catching up on this (I have a large backlog of articles and books to review), but this is the best critique I have seen of the potential dangers of AI applications in education.

Don’t be put off by the title – it’s not totally anti-AI but thoughtfully criticises some of the current thinking about AI applications in education.

It’s worth reading in full (an 8 minute read) but here’s a quick summary to encourage you to have the full meal rather than a snack, with my bits of flavouring on top:

Measuring the wrong things

Most data collected about student learning is indirect, inauthentic, lacking demonstrable reliability or validity, and reflecting unrealistic retention timelines. And current examples of AIEd often rely on these poor proxies for learning, using data that is easily collectable rather than educationally meaningful.

Yes, but don’t educators do that too?

(re)Discovering bad ways to teach

AIEd solutions frequently incorporate false and/or unsupported educational ideas reflecting the biases of their developers….If AIEd is going to benefit education, it will require strengthening the connection between AI developers and experts in the learning sciences. Otherwise, AIEd will simply ‘discover’ new ways to teach poorly and perpetuate erroneous ideas about teaching and learning.

I hope the good folks at MIT are reading this because this is exactly what happened with their early MOOCs.

Prioritising adaptivity over quality

The ubiquity of poor quality content means AIEd technologies often simply recommend the ‘best’ piece of (crappy) content or identify students at risk of failing a (crappy) online course early in the semester….Improving and evaluating the quality of instructional content is neither easy nor cheap, it also isn’t something any AIEd solution is going to do. 

This comes down to the criteria that AI uses to make recommendations. This means replacing criteria such as the number of hits, or likes, with more educational criteria, such as clarity and reliability. Not easy but not impossible. And we still need to improve the quality of content, whether we use AI or not.

Swapping affect for efficiency

Maybe one day AIEd will be capable of effectively identifying and nurturing student emotions during learning, but until then we must be careful not to offload educational tasks that, on the surface, may appear menial or routine, but critically depend on emotion and meaningful human connections to be optimally beneficial.

AI advocates often argue that they are not trying to replace teachers but to make their life easier or more efficient. Don’t believe them: the key driver of AI applications is cost-reduction, which means reducing the number of teachers, as this is the main cost in education. In fact, the key lesson from all AI developments is that we will need to pay increased attention to the affective and emotional aspects of life in a robot-heavy society, so teachers will become even more important. 

Comment

One problem with being old is that you keep seeing the same old hype going round and round. I remember the same arguments back in the 1980s over artificial intelligence. Millions of dollars went into AI research at the time, including into educational applications, with absolutely no payoff.

There have been some significant developments in AI since then, in particular pattern recognition, access to and analysis of big data sets, and formalized decision-making within limited boundaries. The trick though is to recognise exactly what kind of applications these new AI developments are good for, and what they cannot do well. In other words, the context in which AI is used matters and needs to be taken account of. Thus the importance of Lynch’s comment about involving learning scientists/educators in the design of AI applications in education.

I believe there will be some useful applications of AI in education, but only if there is continuing dialogue between AI developers and ‘learning scientists’/educators as new developments in AI become available. But that will require being very clear about the purpose of AI applications in education and being wide awake to the unintended consequences.

Scary tales of online learning and educational technology

The Centre for Digital Media, Vancouver BC

The Centre for Digital Media, Vancouver BC

The Educational Technology Users Group (ETUG) of British Columbia held an appropriately Halloween-themed get together today called ‘The Little Workshop of Horrors’ at which participants were encouraged to share tales of failure and horror stories in the use of learning technologies.

This seemed to me a somewhat risky strategy but it actually worked really well. First the workshop was held in ‘the Hangar’, a large, covered space in (or rather beside) the Centre for Digital Media, a shared building used by UBC, Simon Fraser University, BCIT and the Emily Carr University of Art and Design. The Centre itself is a good example of collaboration and sharing in developing media-based programs, such as its Master of Digital Media. The Hangar lent itself to a somewhat spooky atmosphere, enhanced by a DJ who often accompanied presenters with ghoulish music.

Audrey’s Monsters

The workshop got off to an excellent start with a brilliant keynote from Audrey Watters on the Monsters of Educational Technology (The link will take you to her book on the subject). She identified a range of monsters (the examples are partly Audrey’s, partly mine):

  • Frankenstein’s monster that went wrong because its (hir?) master failed to provide it (em?) with love or social company (teaching machines?): in Audrey’s word’s ‘a misbegotten creature of a misbegotten science’,
  • vampires that suck the blood of students, e.g. by using their personal data (learning analytics?),
  • zombies, i.e. technologies or ed tech ideas that rise and die then rise again (e.g. technology will remove the need for schools, an idea that goes back to the early 1900s),
  • giants that become obsolete and die (Skinner, Merrill)
  • the Blob, which grows bigger and bigger and invades every nook and cranny (MOOCs?)
  • and the dragons, are the libertarian, free-market, Silicon-valley types that preach the ‘destruction’ and ‘re-invention’ of education.

Audrey Watters’ larger point is that if we are not careful, educational technology easily turns itself into a monster that drives out all humanity in the teaching and learning process. We need to be on constant watch, and, whenever we can, we need to take control away from large technology corporations whose ultimate purpose is not educational.

Not only was it a great, on topic, presentation, but it was also such a pleasure to meet at last Audrey in person, as I am a huge fan of her blog.

He was a monster, not because he was a machine, but because he wasn't loved

Confessions

Then came the confessional, at which a series of speakers confessed their sins – or rather, classic failures – about educational technology, often in very funny ways. What was interesting though about most of the tales was that although there was a disaster, in most cases out of the disaster came a lot of good things. (As one speaker said, ‘Success is failing many times without losing your optimism’; or ‘ A sailor gets to know the sea only after he has waded ashore.’).

One presenter reported going to a university to ‘sell’ Blackboard but was so nervous that her presentation was so bad they ended up going with Canvas (you see what I mean about some good coming out of these disasters!) Another described how over 20 years she has been trying to move faculty into more interactive and engaging technology than learning management systems, yet here she is still spending most of her time supporting faculty using an LMS.

One talked about spending years trying to promote IMS-based learning objects, only to find that Google’s search engine made meta-data identification redundant. Revealingly, he felt he knew at the time that the meta-data approach to learning objects was too complex to work, but he had to do it because that was the only way he could get funding. More than one speaker noted that Canada in the past has spent millions of dollars on programs that focused heavily on software solutions (anyone remember EduSource?) but almost nothing on evaluating the educational applications of technology or on research on new or even old pedagogies.

Another spoke about the demise of a new university, the Technical University of British Columbia, that was a purpose-built, new university deliberately built around an “integrated learning” approach, combining heavy use of on-line learning with mixed face-to-face course structures – in 1999. However, by 2002 it had only about 800 FTEs, and a new incoming provincial government, desperate to save money and eager to diminish the previous government’s legacy, closed the university and transferred the students (but not the programs) to Simon Fraser University. Nevertheless, the legacy did live on, with many of the learning technology staff moving later into senior positions within the Canadian higher education system.

I see instructional designers, educational technologists or learning ecology consultants (which was a new title for me) as the Marine Corps of the educational world. They have seen many battles and have (mostly) survived. They have even learned how to occasionally win battles. That’s the kind of wisdom of which academic leaders and faculty and instructors should make much better use.

One participant had such a bad experience at Simon Fraser University that she thinks of it as 'the haunted house on the hill.'

One participant had such a bad ed tech experience at Simon Fraser University that she thinks of it as ‘the haunted house on the hill.’

Happy Halloween, everyone!

Online learning for beginners: 5. When should I use online learning?

Knowledge-based industries include entertainment, such as video games design

Most subject disciplines now require students to know how technology influences their field of study

This is the fifth of a series of a dozen blog posts aimed at those new to online learning or thinking of possibly doing it. The other four are:

This question ‘When should I use online learning?’ is difficult to answer in a short post because there are many possible reasons, and as always in education, the answers are absolutely dependent on the specific context in which you are working, but the reasons can be classified under three main headings: academic, market, and policy/administrative.

Academic reasons

These boil down to relevancy and the changing nature of knowledge in a digital age.

Curriculum requirements

Technology is affecting the content of curriculum in nearly all subject disciplines. It is increasingly difficult to think of an academic area that is not undergoing profound changes as a result of information and communications technologies (ICTs). For instance, any business program now needs to look at the impact of social media and the Internet on marketing and on the delivery of goods. How are ICTs going to change financial investments and advising? In science and engineering, to what extent would animation, simulations or the use of virtual reality enable better understanding of three-dimensional phenomena, equations or formulae? In humanities and fine arts, to what extent are ICTs changing the way we express ourselves? How do we ensure our students are digitally literate and responsible? How do we prepare our students for a world controlled by massive technology companies who track our every movement and expression? It is difficult to think how these issues can be addressed without students themselves going online to study such issues.

Skills development

Also, the skills that our students will need to develop in a digital age will often best be achieved through the use of ICTs. In Chapter 1.2 of Teaching in a Digital Age, I give more detailed examples of such skills. Many of these skills are not only best developed by, but may not even be possible without, students spending an extensive period studying online.

However, I want to focus on two ‘core’ 21st century skills: independent learning and knowledge management. In a knowledge-based society, students will need to go on learning throughout life and outside the formal academic curriculum. Jobs are constantly changing as the knowledge base changes, and even our social lives are increasingly dominated by technological change. Independent learning – or self-learning – is a skill that itself can be taught. Online learning in particular requires self-discipline and independent learning, because the instructor is often not physically ‘there’. Thus gradually introducing learners to online learning can help build their independent learning skills.

Perhaps the overarching ’21st century skill’ though is knowledge management: how to find, analyse, evaluate, apply and communicate knowledge, especially when much of this knowledge is Internet-based or located, and constantly undergoing change. Students then need many opportunities to practice such skills, and online learning often provides a means by which this can be done in a cost-effective manner.

Whether we like it or not, an understanding and management of the use of ICTs is becoming critical in almost any subject area. Students will need to go online to study such phenomena, and to practice core 21st century skills. To do this students will need to spend much more time than at present studying online. (Again, though, we need to ensure that the balance between online and face-to-face time is also properly managed.)

Market reasons

Not only is knowledge undergoing rapid change, so are demographics. In most economically advanced societies, the population is aging. Over time, this will mean fewer younger students coming straight from high school, and more lifelong learners, perhaps already with post-secondary qualifications, but wanting to upgrade or move to a new profession or job and hence needing new knowledge and skills.

Also, with mass education, our students are increasingly diverse, in culture, languages and prior knowledge. One size of teaching does not fit all. We need ways then to individualise our programs. In particular, there are many pedagogical problems with very large lecture classes. They do not meet the needs of an increasingly diverse student population. Online learning is one way to allow students to work at different speeds, and to individualise the learning with online options enabling some choice in topics or level of study.

The changing population base offers opportunities as well as challenges. For instance, your area of research may be too specialised to offer a whole course or program within your current catchment area, but by going online you can attract enough students nationally or globally to make the effort worthwhile. These will be new students bringing in extra tuition revenues that can cover the full costs of an online masters degree, for instance. At the same time, online learning will enable critically important areas of academic development to reach a wider audience, helping create new labour markets and expand new areas of research.

Policy/administrative

We all know the situation where a President or Vice Chancellor has gone to a conference and come back ‘converted’. Suddenly the whole ship is expected to make an abrupt right turn and head off in a new direction. Unfortunately, online learning often leads to enthusiastic converts. MOOCs are a classic example of how a few elite universities suddenly got the attention of university leaders, who all charged off in the same direction.

Nevertheless, there can also be good policy reasons for institutional leadership wanting to move more to blended or flexible learning, for instance. One is to improve the quality of teaching and learning (breaking up large lecture classes is one example); another reason is to expand the reach of the university or college beyond its traditional base, for demographic and economic reasons; a third is to provide more flexibility for full-time students who are often working up to 15 hours a week to pay for their studies.

These policy shifts provide an excellent opportunity then to meet some of the academic rationales mentioned earlier. It is much easier to move into online learning if there is institutional support for this. This will include often extra money for release time for faculty to develop online courses, extra support in the way of instructional and media design, and even better chances of promotion or tenure.

Implications

  1. It can be seen that while market and policy reasons may be forcing you towards online learning, there are also excellent and valid academic reasons for moving in this direction.
  2. However, the extent to which online learning is a solution will depend very much on the particular context in which it will be used. It is essential that you think through carefully where it best fits within your own teaching context: blended learning for undergraduate students; masters programs for working professionals; skills development for applied learning; or all of these?
  3. Online learning is not going to go away. It will play a larger role in teaching in even the most campus-based institutions. Most of all, your students can benefit immensely from online learning, but only if it is done well.

Follow-up

Chapter 1, Fundamental Change in Education, of Teaching in a Digital Age, is basically a broader rationale for the use of online learning

Chapters 3 and 4 look at ways to individualise learning; see in particular:

Up next

‘How do I start?’

Your turn

If you have comments, questions or plain disagree, please use the comment box below.

 

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

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

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

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

What do I mean by ‘alienation’?

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

Causes

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

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

Symptoms

Here are some examples of how technology leads to alienation.

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

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

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

A framework for discussion

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

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

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

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

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

References

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