Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

I’m trying to get my mind around how the information we’re finding out about expertise matches to the types of problems people face.  Clearly, you want to align your investments appropriately to situations you face.  If you look across the literature on expertise, and the recent writing on how our brains work (c.f. Kahneman’s Thinking Fast and Slow), you see an emerging picture of expertise.  When you combine this with the situations organizations are increasingly facing, you recognize that we need to get more granular about the types of problems we’re facing and the solutions we have on tap.

Starting with the types of problems, there are more than just the problems we know and the ones we don’t.  When you look at the Cynefin model, which characterizes the types of problems we face, we see what types of expertise are helpful.  Beyond work that should be automated, there are formulaic types of complicated problems that can be outsourced or accomplished by skilled or well-supported practitioners.  Then there are the complex problems that require deeper expertise.  Beyond that is the chaotic state where you have to try something to move it into one of the other states, and there are certainly reasons to believe that deep expertise .

So now we look at what’s known about our knowledge.  We’ve known for a while that expertise is slowly accumulated, and becomes deeper in ways that are hard to unpack (hence why you need some detailed approaches to get at their understanding).  What’s also becoming clear is that this ability to make expert judgements, once compiled away, is most effective in quick (not laborious) application, with a caveat.  As Kahneman tells us, this expertise needs to be developed in a field that is “sufficiently regular to be predictable”, and in which the expert gets quick and decisive feedback on whether he did the right or the wrong thing. Otherwise, you need to do the hard yards, the slow thinking that’s effortful and systematic.  Now, if it’s out of your area of expertise but a known problem, you have two choices: either take a well-known (and appropriate) but laborious approach, or hire the appropriate expertise.  If it’s a relatively novel situation, either unique or new, you’ll need a different type of expertise.

We can infer that having a rich suite of models and frameworks helps in circumstances where the right solution isn’t obvious.  The conclusion is clear: advanced experts may not immediately know the solution if the problem is reasonably complex (if so, you can get by with a practitioner), but their deeply developed intuition, based upon experience, and associated approaches to those types of problems will have a higher likelihood of finding a solution.  Particularly if their expertise spans problem-solving in general, and specific expertise in at least some of the involved domains. Experience solving complex problems, and having a deep and broad conceptual background increases the likelihood of a systemic and comprehensive solution.

To think about it another way, this article makes a distinction between puzzles and mysteries. Puzzles have an answer, once you identify the information needed, collect it, and execute against it. This is the ‘Complicated’ part of the Cynefin situation. Mysteries are where you can’t know what will happen, and you have to experiment.  This is the ‘Complex’ or ‘Chaotic’ parts of the model.  You’re better off in the latter two if you’ve got good systems thinking, and a suite of useful models in your quiver.

So, when facing a problem, you have to characterize it: is this a puzzle where someone has an off-the-shelf solution “ah, we know that pain, and we solve it this way”, versus the mystery situation where it’s not clear how things will sort out, and you need a much richer conceptual background to address it. In the former case, you can find vendors or consultants with specific expertise.  In the latter, the implication clearly is that you want someone who’s been thinking and doing this stuff as long as possible.  You want someone who can guide some experiments.

The risk of trying to solve the complex problems with off-the-shelf solutions or DIY is that your answer is likely to be missing a significant component of the situation, and consequently the solution will be partial. You need the right type of expertise for the right type of problem.

As a prelude to a small webinar I’ll be doing next week (though it also serves to tee up the free Best of mLearnCon webinar I’ll be doing for the eLearning Guild next week as well, here’re some deliberately provocative thoughts on mobile:

According to Tomi Ahonen, mobile is the fastest growing industry ever.  But just because everyone has one, what does it mean?  I think the implications are broader, but here I want to talk specifically about work and learning.  I want to suggest that it has the opportunity to totally upend the organization.  How? By broadening our understanding of how we work and learn.

The 70:20:10 framework, while not descriptive, does capture the reality that most of what we learn at work doesn’t come from courses (the ’10′).  Instead, we learn by coaching/mentoring (the ’2o’), and ‘on the job’ (70).  Yet, by and large, the learning units in organizations are only addressing the 10 percent.  They could, and should, be looking at how to support the other 90, but haven’t seen it, yet there’re lots that can be done.

The bigger picture is that digital technology augments our brain.  Our brains are really good at pattern-matching and extracting meaning. They’re also really bad at doing rote things, particularly complex ones.  Fortunately, digital technology is exactly the opposite, so combined we’re far more capable.  This has been true at the desktop, with not only powerful tools, but support wrapped around tools and tasks.  Now it’s also true where- and whenever we are: we can share content, compute capabilities, and communication.  And you should be able to see how that benefits the organization.

And more: it’s adding in something that the desktop didn’t really have: the ability to capture your current context, and to leverage that to your benefit. Your device can know when and where you are, and do things appropriately.

So why is this game-changing?  I want to suggest that the notion of a digital platform that supports us ubiquitously will be the inroad to recognize that the formal learning is not, and cannot, be separate from the work.  If we’re professionals, we’re always working and learning (as my colleague Harold Jarche extols us).  If a new platform comes out that’s ubiquitous yet relatively unsuited for courses, we have a forcing function to start thinking anew about what the role of learning and performance professionals is.  I suggest that there are rich ways we can think about coupling mobile with work.

Why do I suggest that courses on a phone isn’t the ideal solution?  You have to make some distinctions about the platform.  A tablet is just not the same as a pocketable device. It has been hard to get a handle on how they differ, but I think you do need to recognize that they do.  For example, I’ll suggest that you’re not likely to want to take a full course on a pocketable device, however on a tablet that’d be quite feasible.

To take full advantage, you have to consider mobile as a platform, not just a device. It’s a channel for capability to reach across limitations of chronology and geography, and make us more productive. And more.  So, get on board, and get going to more and better performance.

I’m happy to report that the eLearning Guild has just released this year’s mobile learning research report I authored for them (after doing the same last year).  It’s free if you’re already a paid member of the Guild, which has other benefits (e.g. similar free access to other coming research reports, Thought Leader Webinars, etc).  Combining my summary of the ‘state of the industry’ with the results of surveys of the Guild’s membership, it’s a snapshot of the state of mobile learning.

I should admit that there’s a bias in the report, in that the membership of the Guild is largely (though not wholly) corporate, and again largely US based.  I suspect, therefore, that the global picture isn’t fully represented in the report. However, I do hope that the commentary does reflect general principles that are relevant regardless of context, though the fact of the market is that smartphones for instance are more distributed in the developed world than the developing world.

In the report, I make two points:

“What’s clear is that it is time to move beyond the initial experimental stages and start thinking of mobile as a platform for organizational performance. … The time to get on top of mobile is now, as the market has matured to the point where we can see real benefits on a pragmatic basis.”

I believe mobile, as a platform, will have a transformative effect on the learning and performance workplace as it will elsewhere.  As mobile delivers digital augmentation of our capabilities wherever and whenever, no longer just at the desktop, it will bring all the resources onto the table: performance support and social as well as augmenting formal learning.  This is an opportunity for a game-change, where L&D can take responsibility for more benefits to the organization, and as a consequence be viewed more core to the business.

If you’re interested in what’s happening in mobile learning, this report is for you. If you’re active in learning & technology, I reckon eLearning Guild membership makes sense as well.

I was talking today with an organization that has mentoring as a very core feature of their culture, and it got me reflecting on the fantastic luck I’ve had in my career.  Even before working, I had some great teachers, and then many folks have helped shape me through my job experience.

Dick Bergeron was a 12th grade teacher at SPHS who really helped me understand a different path to learning and thinking. He did what I now know to be reciprocal teaching, had us take turns talking about what we were learning from our reading, and discussing it, with him facilitating our reflection.

I got a job while I was in college at UCSD, maintaining the computer records for the office that did tutoring on campus, and Carmel Myers and Ken Majer helped me learn how to be professional (particularly when I screwed up).

Seeing the connection between computers and learning via that job, I designed my own major in college, and with the guidance of Hugh Mehan and Jim Levin learned a lot about what constituted good research. They also lived what great student development was.

In my first job, designing and programming educational computer games for DesignWare, Jim Schuyler and Lesley Czechowicz helped me learn quite a bit about how organizations run and what good management is.

I returned to grad school at UCSD after a summer working with Ken Majer again, and Don Norman patiently helped me rediscover and expand my understanding of research and cognition, particularly the application thereof.  Don is also a great role model for top-notch critical and innovative thinking.  At the Learning Research & Development Center at the University of Pittsburgh, Leona Schauble furthered my understanding of detailed research and development while guiding my post-doctoral fellowship.

At the University of New South Wales, where I took up an academic position, Paul Compton served to model what a wise leader really looks like.  When I stepped away from the University, first Ron Watts at Open Net and then Rim Keris at Access CMC helped me take steps in understanding a strategic approach to business.

Jim Schuyler brought me back to the US, where he again mentored me on team leadership.  He also introduced me to Joe Miller, who has served to really help me understand the next level of organizational strategy.

Since then, my business partners, Charlie Gillette at Knowledge Anywhere and Mohit Bhargava at LearningMate, have helped me learn much about business models and the art of the deal.  And my colleagues in the Internet Time Alliance – Jay Cross, Jane Hart, Harold Jarche, and Charles Jennings – have taught me a lot about working as an independent and together.

These are the ones where I had an extended period of time with, but many other folks have served as models and provided assistance: Ellen Wagner and Marcia Conner are two that come to mind, and many more I’m forgetting, as well as many friends who’ve shared good times (and bad).  Naturally, my parents had a wee bit of influence as well.  And I’ve been doubly fortunate that many of these folks have remained in touch.

There certainly is an art to mentoring, though it can be developed, and I reckon there’re also some skills to being a good mentee.  I hope I’ve been able to do some of the former, and not do the latter too badly.

I certainly still have lots to learn, but I’m exceptionally grateful to these folks.  Many kudos to them, but of course all faults of the end product remain with the author ;).  I think increasingly we can and should be continually mentoring those we care about, and mutually mentoring each other.  Here’s to learning!

I was contacted for a research project, and asked a series of questions. Thought I’d document the answers here, too.

Q0. How many years have you been designing educational games?

Q1. Please walk us through your process for creating an educational game from concept to implementation. Please use one of your games as an example.

A long answer is the only option (it’s a big process).  Using a design framework of Analysis, Specification, Implementation, and Evaluation:

Analysis

For any educational task, you have to start by looking at what your design objective is: you need to document what folks should be able to do that they can’t do now. I argue that this is most importantly going to manifest as an ability to make better decisions, ones that the learner doesn’t reliably make now.  It’s complicated, because SMEs don’t always have access to how they do what they do, and you have to work hard.  This isn’t unusual to learning design, except perhaps the focus on skills.

Then, you need to know how folks go wrong; what are the reliable misconceptions. People don’t tend to make random mistakes (though there is some randomness in our architecture), but instead make mistakes based upon some wrong models.

You also need to know the consequences of those mistakes, as well as the consequence of the right answer. Decisions tend to travel in packs, and if you make this one wrong, you’re then likely to face that other one. You need to know what these are.  (And the probabilities associated with them).

In addition, you need to know the settings in which these decisions occur, as many as possible.

And you need to know what makes this task inherently interesting (it is).  Here’s where the SME is your friend, because they’re so passionate about this they’ve made it the subject of their expertise, find out what makes them find it interesting.

Specification

With this information, you address those aligned elements from effective education practice and engaging experiences.    You need to find a storyline that integrates what makes the task interesting with the settings in which the decisions occur.  I like a heuristic I heard from Henry Jenkins: “find a role the player would like to be in”. Exaggeration is a great tool here: e.g. you’d likely rather be working on the ambassador’s daughter than just another patient.

You need to make those misconceptions seductive to get challenge. You don’t want them getting it right unless they really know their stuff.

You need to handle adjusting the difficulty level up at an appropriate rate; you might have complications that don’t start until after they’ve mastered the interface.

You need to specify characters, dialog, rules that describe the relationships, variables that code the state of the game, a visual (and auditory) look and feel.  The UI expressed to the learner, and more.

You’ll need to specify what the ‘perspective’ of the player is in relation to the character.

Overall, you need to nail meaningfulness, novelty, and the cycle of action and feedback to really get this right.

Finally, you need to specify the metrics you’ll use to evaluate your creation. What will be the usability goals, educational outcomes, and engagement metrics that will define you’re done?

Implementation & Evaluation

I’m a design guy, so I don’t talk so much about implementation, and evaluation follows the above.  That said…

The tools change constantly, and it will vary by size and scope. The main thing here is that you will have to tune.  As Will Wright said, “tuning is 9/10ths of the work”.  Now that’s for a commercially viable game, but really, that’s a substantial realization compared to how complex the programming and media production is.

Tuning requires regular evaluation.  You’ll want to prototype in as low a fidelity as you can, so it’s easier to change.  Prototype, test, lather, rinse, repeat.  (Have ever 3 words ever sold more unnecessary product in human history?)

There’s much more, but this is a good first cut.

Q2. Describe your greatest success, challenge, failure.

My greatest success, at least the most personally rewarding in terms of feeling like making a contribution, is definitely the Quest game. When you’re making a game that can save kids’ lives, you’ve got to feel good about it. On no budget (we eventually got a little money to hire my honors student for a summer, and then some philanthropic money to do a real graphic treatment), we developed a game that helped kids who grow up without parents experience a bit of what it’s like to survive on your own (goal: talk to your counselors).  Interestingly, I subsequently got it ported to the web as a student project (as soon as I heard about CGI’s, the first web standard to support maintaining ‘state’, I realized it could run as a web game), and it still runs! As far as I know, BTW, it’s the first web-based serious game ever.

My greatest challenge was another game you can still play on the web.  We’d developed a ‘linear scenario’ game on project management for non-project-managers, and they liked it so much they then asked for a game to accompany it.  But we’d already accomplished the learning!  Still, we did it.  I made the game about just managing to cope with missing data, scope creep, and other PM issues, so engineers could a) understand why they should be glad there were project managers, and b) that they shouldn’t be jerks to work with.

Biggest failure that I recollect was a team brought together by a publisher to work with the lead author on a wildly successful book series.  There was a movie script writer who’d become a game designer, and me, and a very creative team. However, we had a real problem with the SME, who couldn’t get over the idea that the ‘game’ had to develop the concept without getting mired in the boring details of particular tools. We would get progress, and then generate a great concept, and we’d be reined back in to “but where’s the tool simulation”?  Unfortunately, the SME had ultimate control, not the creative team, and the continuing back and forth ultimately doomed the project.

Q3. When determining game play is avoiding violence an issue? Q4. Is accounting for gender an issue when creating games?

I answered these two questions together; I don’t shy away from controversy, and believe that you use the design that works for the audience and the learning objective.  I believe education trumps censorship.  I argued many years ago (when Doom was the GTA of the day) that you could get meaningful learning experiences out of the worst of the shoot-em-ups.  Not that I’d advocate it.  Same with gender.  Figure out what’s needed.

As a caveat, I don’t believe in gratuitous violence, sex, or gender issues, (Why is sex more taboo than violence? I don’t get it.) but I believe you need to address them when relevant in context. In ways that glorify people, not violence or intolerance.

Q5. How did you develop your creation process?

I went from ad h0c at the start to trying to find the best grounding for process possible.  Even as an undergrad I had received a background in learning, but as a grad student I pursued it with a vengeance (I looked at cognitive, behavioral, constructivist, ID, social, even machine learning looking for insight).  At the time, the HCI field was also looking at what made engaging experiences, and I pursued that too. The real integration happened when I looked systematically at design and creative processes: what worked and what didn’t.  Using the learning design process as a framework (since folks don’t tend to adopt new processes whole-cloth, but tend to modify their existing ones), I worked out what specifically was needed in addition to make the process work for (learning) game design.

Q6. How do you work? Individually? As a team? If so, how do you develop a team?

Euphemistically, I work however anyone wants.  I seldom really do individual, however, because I have no graphic design skills to speak of (much to my dismay, but a person’s got to know their limitations, to paraphrase the great sage Harry Calahan).  Also, I strongly believe you should source the full suite of talent a game design needs: writing, audio, graphic, programming, UI, learning design, etc.  Naturally, in the real world, you do the best you can (“oh, I can do a good enough job of writing, and you can probably do a good enough job of audio as well as the programming”).

Q7. Is there a recipe for success in this industry? If so what is it and what would you say your biggest lesson has been so far?

My short answer is two-fold. I immodestly think that you really have to understand the alignment between effective practice and engaging experience (there’re lots of bad examples that show why you can’t just shove game and instructional designers into a room and expect anything good). Second, you have to know how to work and play well with others.  Game design is a team sport.

And finally, you really, really, have to develop your creative side.  As I tell my workshop attendees: I’ve got bad news, you have a big job ahead of you; if you’re going to do good serious game design, you’re going to have to play more games, go to more amusement parks, read more novels, watch more movies. It’s a big ask, I know, an onerous task, but hey, you’re professionals.   But you also have to be willing to take risks. Much to m’lady’s dismay, I argue that I continue to have to crack bad jokes as practice to find out what works (that’s my story, and I’m sticking with it).

If you can get a handle on these three elements: understanding the alignment, able to convince people to work with you on it, and push the envelope, I reckon you can succeed. What do you reckon?

A number of books have crossed my path for a variety of reasons, and there’re some lessons to be extracted from three of them.  All have to do with looking at how our brains work, and some lessons therefrom.  There have been quite a bit of kerfuffle about ‘brain-based learning’, of which too much is inappropriate inferences from neuroscience to learning.  What I’m doing here is not that, but instead reporting on three books, only one of which has an explicit discussion of implications for both education and work. Still, valuable insight comes from all three.

Let me get the negative stuff out of the way first, a book that a number of folks have been excited about, Joshua Foer’s Moonwalking with Einstein, just did nothing for me. It’s a great tale well told, but the lessons were only cautionary. In it, a journalist gets intrigued enough with remembering to train sufficiently to win the US memory championships (apparently, globally, a relatively minor accomplishment).  He reveals many memory tools to accomplish this, and points out some potential fraud along the way.  He also concludes that despite this heightened ability, there is little relevance in the real world.  We have devices that can be our memory now, and the need for these skills is questionable at best.  All in all, little benefit except to be skeptical.

A second book, Daniel Kahnemann’s Thinking Fast and Slow, is a different story. Kahnemann, and his late long-time collaborator Amos Tversky, conducted some seminal research in how we make decisions (essential reading in my grad school career).  And the best way to convey how we do this, as Kahnemann tells us, is to postulate two separate systems. Not surprisingly one is fast, and one is slow.  The book is quite long, as Kahnemann goes through every phenomenon of these outcomes that they’ve discovered (often with collaborators), but each chapter closes with some statements that capture the ways your thinking might be wrong, and ways to compensate. It could use more prescriptions and less description (I started skimming, I confess), but understand the two systems and the implications are important.  It’s a well-written and engaging book, I just wish there was a ‘take home’ version.

The fast system is, essentially, intuition. This comes in many ways from your experience, and experts in a field should trust their intuition (there’s a strong argument here for hiring someone with lots of experience) in their area.  In areas where expertise is needed, and you don’t have it, you should go to the slow system, conscious rational thought.  Which is very vulnerable to fatigue (it taxes your brain), so complex decisions late in a day of decision are suspect.  If your decision is commonplace, you can trust the fast system, and many times you’ll be using the slow system just to explain the decision the fast system came up with, but we’re prone to many forms of bias.  It’s a worthwhile read, and tells us a lot about how we might adapt our learning to develop the fast system when necessary, and when to look to the slow system.

Finally, Cathy Davidson’s written Now You See It, a book that takes an attentional phenomena and builds a strong case for more closely matching learning and work to how we really think.  (I was pointed to it by a colleague who complained that my learning theory references are old; I still take my integration of learning theory as appropriate but nice to see that more recent work reflects my take on the best from the past. :) The phenomena is related to how our attention is limited and we need help focusing it.  For a dramatic demonstration of this phenomena, view this video and follow the instructions.  Her point is that what and how we pay attention does not reflect our current schooling systems nor our traditional work environments.  She uses this and myriad examples to make a compelling case for change in both.  On the learning side, she argues strongly for making learning active and meaningful (a view I strongly support), and start using the technology. On the other side, she talks about the new ways of working consonant with our Internet Time Alliance views.  It’s very readable, as it’s funny, poignant, apt, and more.

I highly recommend Cathy Davidson’s book as something everyone should understand.  Like I said, I wish there were a ‘Readers Digest Condensed‘ version of Kahnemann’s book.  It’s worth having a look at if you’re responsible for decisions by folks, however, and at least the first few chapters if you’re at all responsible for helping people make better decisions.

I’m a real fan of styles, ala Microsoft Word.  If you don’t get this concept, I wish you would.  Let me explain.

The concept is fairly simple. Instead of hand-formatting a document by manually adding in bold, font sizes, italics, indents, extra paragraph returns, you define a paragraph as a ‘style’.  That is, you say this paragraph is a heading 1, that paragraph is normal or body text, this other one is a figure, etc. Then you define what a heading one looks like: bold, font size 14, with space before of 6 pts, and space after of 6 pts, etc.

Why use styles?  Several reasons. First, I can then use the outline feature to organize my writing, and then automatically have the right headings.  Second, if I add in content, I don’t have to hand-reformat the way returns have been used to force page breaks (really).  Third, and most importantly, if someone wants there to be a different look and feel to the document, I just change the definition of styles, I don’t have to manually reformat the document.

If you use styles correctly, the document automatically handles things like page breaks and formatting, so the document looks great no matter how you change and edit it. Which is why, when someone sends me a document to edit that is hand formatted, I’ll often redo the whole (darn) thing in styles, just to make my life easier.  And grumble, with less than complimentary thoughts about the author.

Now, styles are not just in Microsoft Word, they’re in Pages, Powerpoint, Keynote, and other places where you end up having repeated formats.  They may have a different title, but the idea plays a role in templates, or themes, or masters, or other terms, but the concept is about separating out what it says from how it looks, and having the description of how it looks separately editable from what it says.  It’s the point behind CSS and XML, but it manifests increasingly in smart content.

And I admit, I’m really good with styles in Word, I’m pretty good in Pages, and still wrestle with Keynote, and I don’t know about other tools like Excel, but I reckon the concept is important enough that it should start showing up everywhere.

Please, please, use styles. At least in anything you send to me ;).

I’m regularly trying to do two things: explore mobile capabilities, and get folks to think more broadly about how we can support performance in the organization.  I was asked to flesh out a proposed title for a stage at the upcoming mLearnCon, and thought about trying to map the 4C’s of mobile to the major categories of mobile work opportunities.  It’s a slightly different take than my previous meta-mobile post where I looked at performance support, formal learning, and meta-learning.

In this case I’m looking at the 4 C’s by work categories.  I see augmenting formal learning as one, providing performance support as a second, social media as a 3rd area, and the unique mobile contribution of context-sensitive support as a 4th area.

I realize there are some problems in this, in that Social and Communicate are hard to discriminate (hence using the catchall phrase social network), and Capture is core to context-sensitivity. Alternate Reality Games (ARGs) don’t have to be social, but can be.  And I hadn’t really thought through what context-sensitive computing and communicating might mean. Certainly you could have a focused directory that knows who knows about this context, and perhaps an app that presents different options for context-sensitive trouble-shooting or repair (e.g. knowing what device you’re liable to be working on), but I could be missing some options.  And I’m not sure I’ve seen socially edited or maintained apps as opposed to content. Anyone?  Anyone?  Bueller?

So, as this is a first shot at this, I welcome feedback. What am I missing?

Karl Kapp’s written another book, this time on gamification, and I certainly liked his previous book with Tony O’Driscoll on Virtual Worlds.  This one’s got some great stuff in it too, and some other ideas that raise some hackles.

Let me get one of the quibbles out of the way at the start: I hate the title “The Gamification of Learning and Instruction” (to the point I previously wrote a post arguing instead for ‘engagification‘).  Karl makes it clear that he’s not on the trivial notion of gamification: “Gamification is not Badges, Points, and Rewards”.  My problem is that by just having the title, folks who don’t read the book will still point to it to justify doing the trivial stuff. I’d much rather he’d titled it something like “Beyond Gamification” or “Engagification” or “Serious Gamification” or something.  He can’t be blamed for people misusing the term, and even his book, but I still fret about the possible consequences.

With that caveat, I think there is a lot to like here.  Karl’s got the right perspective: “Serious games and gamification are both trying to solve a problem, motivate people, and promote learning using game-based thinking and techniques.”  He does a good job of laying out the core ideas, such as:

“Games based on this complex subject matter work, not because they include all the complexities, but precisely because they reduce the complexity and use broad generalizations to represent reality. The player is involved in an abstraction of events, ideas, and reality.”

I liked his chapter 2, as it does a good job of exploring the elements of games (though it’s not quite as categorical as I’d like ;).  He’s got pragmatic advices there, and lots of examples to help illustrate the possibilities.  He goes beyond serious games in a number of ways, talking about adding motivation factors for other things than making good decisions. I worry somewhat that folks might (and do) use the same things to get people to do things that they might not otherwise believe are good to do, and the ethical issues aren’t addressed too much, but again that’s not Karl’s point, as his many examples clearly show.

Chapters 7-9 are, to me, the most valuable from my point of view; how do you do game design (the focus of Engaging Learning). Chapter 7 talks about Applying Gamification to Problem Solving and helps explain how serious games provide deep practice. Chapter 8 maps gamification on to different learning domains such as declarative, procedural, affective, and more. There are valuable hints and tips here for other areas as well as the ones I think are most important.  And Chapter 9 provides valuable guidance about the design process itself.

I wish there was more discussion of how meaningful challenges for problem-solving will make fact based learning more relevant, rather than just gamifying it, but that’s not necessarily the role of this book.  I very much like this statement, however: “The gamification of learning cannot be a random afterthought. It needs to be carefully planned, well designed, and undertaken with a careful balance of game, pedagogy, and simulation.”  Exactly!  You can’t just put instructional designers and game designers in the room together and expect good things to happen (look at all the bad examples of edutainment out there); you have to understand the alignment.

There are some interesting additional chapters.  Guest authors come in and write on motivations and achievements (Blair), the gamer perspective (presumably son Kapp), a case study of a serious initiative in gaming (Sanchez), and alternate reality games (Olbrish).  These provide valuable depth in a variety of ways; certainly Alicia Sanchez is walking the walk, and the alternate reality games that Koreen Olbrish are talking about have struck me as a really compelling opportunity.

There are flaws. I can’t comprehend how he can go from talking about objectives straight to talking about content.  Games are not about content, they’re about context; putting the player into a place where they have to make the decision that they need to be able to make as an outcome.  This statement really strikes me as wrong: “The goal of gamification is to take content that is typically presented as a lecture or an e-learning course and add game-based elements…”. Given my focus on ability, not content, this predictably irks me.

Karl also misses what I would consider are some important folks who probably should be referenced.  While he did get Raph Koster and Jane McGonigal, he hasn’t cited Aldrich, Gee, Shaffer, Barab, Jenkins, Squire, Steinkuehler, or even Quinn (ok, I had to say it).  It seems a bit narrow-focused to miss at least (the ‘other’ Clark) Aldrich, who’s written now 4 books on the topic.  I mean, being an academic and all…. :)

Overall, I know he’s fighting for the right things, and think there’s some very broad and useful information in here. If you’re looking to make your learning designs more effective, this book will show you a lot of examples, give you some valuable frameworks, and provide many hints and tips.

Mayra Aixa Avilar (who I hope to meet someday, maybe at mLearnCon?)pointed to this post saying “mLearning is starting to diverge from eLearning not only in specific meaning, but in approach and design as well”, and I want to politely disagree.   Depends, of course, on what you mean by elearning, to start with.

The clear implication is that elearning is about courses on the desktop.  As I’ve discussed before, when I’m talking about ‘big L‘ learning, I’m covering research, performance, innovation, creativity as well as more typical execution. As a consequence, I’m talking performance support, social networks, portals, and more, as well as courses on the desktop.  The full spectrum of how digital technology, even desktop, can be supporting performance.  Of course, I acknowledge that, to most, elearning is the simple case.

Now, what’s interesting in mobile is that it’s many other things than courses on a phone.  Please.  While it might be courses on a tablet, it’s so much more.  In my workshops, I like to ask the audience how they use their mobile devices to make them smarter, and it ranges across info, contact, notes and calendar, snapping pictures, and more. So not courses.

Which is one of the reasons I like mobile learning, because it’s a real game changer.  As we look to how mobile devices can support performance, we then open the door to looking at how performance across the organization can be supported, and we start seeing how much more a learning unit could be doing besides courses (not replacing them, mind you, but stopping relying on them exclusively).

The post did mention that context-specific things could be done, and communication, but video can be captured, and software can do context-specific things at your desktop too. It’s just that we don’t tend to think about this, and we should. Yes, there is the mobility factor, and that’s a significant opportunity.  Yet this strikes me as an opportunity to redefine elearning to mean a bigger opportunity.

So I guess I’d reframe the conversation, and say that mlearning is helping us see what technology support for performance is, and that’s helping us revaluate elearning.  A good thing.