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Clark Quinn’s Learnings about Learning

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Return on Wisdom

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In the early days of the internet, I had a chance to read one of the early translations of  The Japan That Can Say No.  The point I took away was the critique of short-term decision making driven by the need for shareholder returns.  I was pondering this the other day, as I wondered how organizations can look to make longer-term investments. And it led me to ponder the question of what the return is on wisdom.

So, the book was a sensation. At the time, the rumor was that it was written by two top Japanese. It wasn’t released in English, but instead was illicitly translated because of the scandalous claims.    Still, I thought the assessment of the problems with derivative financing and efficiency approaches were apt.  Are these approaches wise?

I use the term wisdom because I think we can, and need to, go beyond ‘smart’.  I was pursuing my own quest to transcend what I do, and came upon a nice view of wisdom from Sternberg. This one argues that we should make decisions with both short-  and long-term views, for not just us and ours, but for all people, with an explicit consideration of the value that we are following. Ok, so I’m a native Californian, but I don’t see a problem with this view. Smart is ‘in the moment’, wise is looking at the bigger picture.

I ponder this in the context of organizations continually looking to reduce costs through expediency. As an alternative, they could be looking at longer term approaches that help them get their workforce more intrinsically engaged.  Does outsourcing and layoffs end up being more costly than investing in better leadership and culture?

There are some answers.  Laurie Bassie’s research found that there was a correlation between high scores on handling people and business results.  Similarly, Towards Maturity finds that companies with good L&D practices are more likely to be successful.  It’s not surprising. When you provide meaningful work with enablement to succeed, you’re aligning the elements to succeed. It’s a path to a coherent organization. And, like with light, it’s more powerful.

There are arguments to move in wise directions. It may be hard if you’re driven by the need to produce short-term returns. Still, it’s the wise thing to do.

Activity or Application?

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I’m a fan of Michael Allen’s, not only because he knows his stuff and he’s a very good person, but also because he has a knack for making things accessible.  For example, his Guide to eLearning is as good a guide to designing elearning as you can get (that and Julie Dirksen’s Design for How People Learn, both appropriately in their second edition).  So when I thought to criticize one of his models, I had to think  really hard!  And I’m still wrestling with it, but I also realize I’d gone down the same path!  Obviously, it’s time to explore the issue.

One of Michael’s models is the CCAF model for making meaningful elearning.  That’s:

  • Context: that sets up the situation
  • Challenge: that prompts the need for action
  • Activity: that the learner takes, and
  • Feedback: that comes from the situation.

There are nuances about this, but it nicely incorporates some of the best principles about designing effective (and engaging) practice. If you put people in a context and ask them to act, you’re minimizing the distance between the practice and the actual performance. Which is, of course, key to successful transfer.  So this is a very handy shorthand, like Cathy Moore’s Action Mapping.

Now, in many ways, this is similar to my own activity-based design, which is more a curricular model than a pedagogical one, but it foregrounds activity instead of content. The goal is to have learners  do something!  And, of course, I’m thinking of creating a work product in many instances, or making meaningful decisions.

So what was I concerned about?  Perhaps because I’d been thinking (and whinging) about ‘click to see more’ interactions, I want those activities to  mean something!  You could have an activity that’s just ‘matching’, or ‘identify the right word’ type of knowledge test. Those  are activities, just not cognitively challenging ones.  And of course Michael emphasizes this in his descriptions, but…there’s an opportunity for people to be slack.

I wondered about using ‘application’ instead of activity, focusing on the fact that people should be applying the knowledge to  do something, not just doing any sort of activity. Do the semantics matter enough to be worth considering?  Application-based design?  Context-Challenge-Application-Feedback? Perhaps not, but I thought I’d think ‘out loud’ as usual. (Both to reiterate the point as well as to solicit your input.) So, what are your thoughts? Worth it?  Or too much ‘splitting angel’s hairs on the head of a pin’ (metaphors mixed while you wait)?

Possible versus practical

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Last week, I gave a presentation to the local chapter of ATD. And I was surprised that their request was for mobile learning. Now that  is something I can speak to, but given that my book on the topic came out seven years ago now, it seemed like a dated topic. And I was wrong.  And the difference is between what’s possible and what’s practical.

Ok, so I am somewhat out ahead of the curve.  My games book came out in 2005, but the market wasn’t quite ready.  I similarly think my L&D revolution book, in 2014, was ahead of the market (the topic is finally getting more traction, close to four years later), though closer. But I thought the mlearning book was timely (not least because my publisher asked for it more than it was my initiative ;).

However, the audience was eager.  And it was relatively large for the group.  And it took a comment from the organizer to raise my awareness.  He said (and I paraphrase): “you think that it’s old, but it’s not old for everyone”. And that was indeed a wakeup call.  Because while mobile to me is very practical, for many it’s still possible.

I  do tend to move on once I reckon I’ve figured something out. I’m interested when it’s still something to be understood or solved. Once I have my mind around it, my restless brain is on to something new.  That’s why I have this blog, for instance, to wrestle with new thoughts. If they get organized enough, it becomes a presentation or even a book.  (Though sometimes I do ones that are requested, e.g. my forthcoming one on myths, and I’m supposed to be reviewing the second round of proofs!)

But the interesting thing to me is to look beyond my own bubble (and what my colleagues are talking about).  We’re looking at what’s possible but not yet done, or what’s on the horizon. Yet I need to remember to continue to tout what’s now on the menu, and recognize not everyone’s yet started moving.  The things that I think are already practical to implement are still on the ‘possible’ list for others.

If you’re reading this blog, you’re probably with me, but feel free to let others know that the things in my past I’m still happy to help with!  In any way: consulting or workshops or even speaking.  For instance, I’ll be talking engagement for the Guild at Learning Solutions, and in a webinar for AECT’s Learner Engagement group.  Just as I talk new things, like myths.  What goes around comes around, I guess, and what’s been possible is now practical.  Ask me how!

 

The Dearth of Science in Learning Technology

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Over the years, I’ve looked at a lot of learning technology.  And I see a dispiriting trend. There seems to be little learning science of late.  What I see are marketing driven decisions, even when there are claims to science!  And I think this is a problem.

First, I generally resist the ‘let me show you our product and give us your opinion’. That’s free consulting, and a very rude ask!  (Though I’m contemplating it but all they’ll get for free is the number of comments in each category I’ve noted. ;)  Still  I  will investigate things of my volition at times.  I end up seeing a lot of technology by checking it out when someone talks about it, or wandering expo halls.  And what I see concerns me.

For one, there are too many tools that have suites of features that are oriented towards ‘information dump and knowledge test’.  Which we know isn’t going to lead to meaningful learning.  Yet when I try to push them to the next level of engagement (cognitive and emotional), they’re uninterested.  The response: “this is what our customers say they want”.  Which, of course, isn’t what they need.

It gets worse when supposedly more advanced tools are proselytized. I recently sampled one system promoting their advanced memory model.  And the free-to-air course  on learning science was broken!  It failed on a couple of dimensions beyond drilling rote memory about one thing. That’s not a good example to be showing.  Yet people who don’t know better might be enthused.

For a quick test, check to see if there’s anyone who understands learning on the executive team of a vendor. You’ll see all the business roles filled.  Some might have advisory boards composed of learning folks, but it’s not clear what role they play.

And I get it.  Unfortunately, as an industry, we’re not informed consumers. I see continual conceptually fuzzy promotion of ideas, and even societies offering white papers on the latest buzzwords.  It’s business, and with business folks in charge (and shareholders to assuage), they’ll do what people want.  Yet this isn’t the professionalism we need.

Ok, so this rant doesn’t taint all companies, but it’s too true for many or most. It’s all too easy to look at the typical offerings and point out the fundamental flaws in what they’re doing, if you know how we learn. And you should.

So, I’ll continue on my crusade for us as an industry to lift our game. I hereby offer to assist any learning technology that wants to put it’s money where it’s mouth is to help them understand learning science, build it into their products, and help them promote the benefits. And I likewise offer any organization  using learning technology to help them lift their game and be better consumers.  I’ve done both before, and am ready to assist others. Because our learners need us to represent their true interests.

 

Listening

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Listening, as I mentioned, in this case to  Guy Wallace.  As one of the premier promoters of evidence-based design, he responded to my question  about what to post on with:

Any “How Tos” using methods, tools and techniques that you‘ve found to work in L&D and Performance Improvement.

Since I am a fan of Guy’s work, I thought I should answer!  Now, obviously I don’t work in a typical L&D environment, so this list is somewhat biased. So I mentally ran through memorable projects from the past and looked for the success factors. Besides the best principles I usually advocate, here are a few tips and tricks that I’ve used over the years:

  • Engage.  Obviously, I wrote a book about this, but some of the quick things I do include:
    • embed the decisions they should be making in contexts where they make sense
    • as Henry Jenkins put it: “put the player in a role they  want to be in”
    • exaggerate the context
    • minimize the distractions
    • hook the learners in emotionally from the start
  • Decisions. I find that working with the objectives for learning projects, it’s critical to focus on the decisions that learners will ultimately be making.  I argue that what will make the difference for organizations, going forward, will be better decisions. And it keeps the discussion from focusing on knowledge. Knowledge is needed, but it’s not central.
  • Brainstorming. When working a strategy session with clients, I seed the discussion before hand with the challenges and background material, and ask that everyone think on their own before we begin collaboration.
  • Better ‘Pair and Share’.  If, in brainstorming, you should think individually before collectively, so should you do so in all forms. So I trialed a ‘pair and share’ where I asked everyone to:
    • think on the questions (asking for 2 things) first,
    • then share with another,
    • and try to reach agreement
    • (I polled the first audience I trialed it on, and they said that the discussion was better, FWIW).
  • Shared language. I have found it valuable, when starting a new project, to run a little ‘presentation’ where I present some of the models that I’m bringing to the table (that’s why I‘m there ;), so we’re starting from a shared understanding. And of course I’ve reviewed materials of theirs beforehand so I can use their terminology.  Educating clients is part of a Quinnovation engagement!
  • Test.  In making the Workplace of the Future project with Learnnovators,  we were barreling along full tilt, working on the second module, and I was getting increasingly worried about the fact that we hadn’t tested the first.  We finally did, relatively informally, but still got valuable feedback that changed our design somewhat. Similarly on other projects, get feedback early and often.
  • Visualize. My diagramming bent had me map out the workflow of a client’s production process, to identify opportunities to tweak the process to bring in better learning science with minimal interruption.  In general, I will often jump up to the whiteboard and try to represent what I’m hearing to see if it’s shared.
  • Prototype.  Similar to the above, I will often mock up what I’m thinking about (in sort of a ‘ape with a crayon’ level of fidelity), to help communicate the idea; e.g. some sort of walkthrough.  I find that only a percentage of the audience can imagine what the experience will be without getting somewhat concrete. (And, yes, they do then complain about the production values, despite the tradeoff of cost versus value.  Sigh.)
  • Get the context.  I generally try to understand the whole ecosystem (ala ‘the revolution‘) before I engage in specifics.  What are the goals, stakeholders, what’s already being done and by whom, etc. It’s important to re-contextualize ‘best principles’, and that requires  knowing the context.
  • Architecture. Thinking through things using a design thinking approach and a systems-thinking perspective, I’ve tried to think of platforms, not just solutions. It might be content architectures, ecosystem elements, but it’s thinking in terms of systems, not just tactics.
  • Pragmatism. One final approach that has been beneficial is thinking about how to approximate the best with a budget.  I used to talk about ‘what would you do if you had magic’, and then see how close you can get with the resources to hand. It’s a heuristic that often has led to an innovative yet viable solution.

Looking at them, I see that they generally reflect my overall focus on aligning what we do with how we think, work, and learn. Your thoughts?

Let’s talk

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“Conversations are the stem cells of learning.” – Jay Cross

I recently read something that intrigued me. I couldn’t find it again, so I’ll paraphrase the message.  As context, the author was talking about how someone with a different world view was opining about the views of the author. And his simple message was “if you want to know what I, or an X, thinks, ask me or an X. Don’t ask the anti-X.”  And I think that’s important.  We need to talk together to figure things out. We have to get out of our comfort zone.

It’s all too evident that we seem to be getting  more divisive. And it’s too easy these days to only see stuff that you agree with.  You can choose to only follow channels that are simpatico with your beliefs, and even supposedly unbiased platforms actually filter what you see to keep you happy. Yet, the real way to advance, to learn, is to see opposing sides and work to find a viable resolution.

Innovation depends on creative tension, and we need to continue to innovate.  So we need to continue to engage.  Indeed, my colleague Harold Jarche points to the book  Collaborating with the Enemy  and argues that’s a  good thing.  The point is that when things are really tough, we have to go beyond our boundaries.  And life is getting more complex.

So I keep connections with a few people who don’t think like me, and I try to understand the things that they say. I don’t want to listen just to those who think like me, I recognize that I need to understand their viewpoints if we’re going to make progress.  Of course, I can’t guarantee reciprocity, but I can recognize that’s not my problem.

And I read what academic research has to say. I prefer peer-review to opinion, although I keep an open mind as to the problems with academic research as well. I have published enough, and reviewed many submissions, so I recognize the challenges.  Yet it’s better than the alternative ;).

This is, however, the way we have to be as professionals. We have to understand other viewpoints.  It matters to our world, but even in the small little worlds we inhabit professionally.  We need to talk.  And face to face. It matters, it turns out.  Which may not be a surprise.  Still, getting together with colleagues, attending events, and talking, even disagreeing (civilly) are all necessary.

So please, talk.  Engage.  Let’s figure stuff out and make things better. Please.

 

Reflections on 2017

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The end of the calendar year, although arbitrary, becomes a time for reflection.  I looked back at my calendar to see what I’d done this past year, and it was an interesting review.  Places I’ve been and things I’ve done point to some common themes.  Such are the  nature of reflections.

One of the things I did was speak at a number of events. My messages have been pretty consistent along two core themes: doing learning better, and going beyond the course.  These were both presented at TK17 that started the year, and were reiterated, one or the other, through other ATD and Guild events.

With one exception. For my final ATD event of the year, I spoke on Artificial Intelligence (AI). It was in China, and they’re going big into AI. It’s been a recurrent interest of mine since I was an undergraduate. I’ve been fortunate to experience some seminal moments in the field, and even dabble.  The interest in AI does not seem to be abating.

Another persistent area of interest has been Augmented Reality (AR) and Virtual Reality (VR). I attended an event focused on Realities, and I continue to believe in the learning potential of these approaches. Contextual learning, whether building fake or leveraging real, is a necessary adjunct to our learning.  One AR post of mine even won an award!

My work continues to be both organizational learning, but also higher education. Interestingly, I spoke to an academic audience about the realities of workplace learning!  I also had a strategic engagement with a higher education institution on improving elearning.

I also worked on a couple of projects. One I mentioned last week, a course on better ID.  I’m still proud of the eLearning Manifesto (as you can see in the sidebar ;).  And I continue to want to help people do better using technology to facilitate learning.  I think the Quinnov 8 are a  good way.

All in all, I still believe that pursuing better and broader learning and performance is a worthwhile endeavor. Technology is a lovely complement to our thinking, but we have to do it with an understanding of how our brains work.  My last project from the year is along these lines, but it’s not yet ready to be announced. Stay tuned!

The Quinnov 8: An online course

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Ok, so I told you the story of the video course I was creating on what I call the Quinnov 8, and now I’ll point to it.  It’s available through Udemy, and I’ve tried to keep the price low.  With their usual discounts, it should be darn near free ;).  Certainly no more than a few cups of coffee.

It’s about an hour of video of me talking, with a  few diagrams and text placeholders.  I’ve included quizzes for each of the content sections. Also, I have assignments to go away and apply the principles to your own work.  Finally, I created a page or several for each section showing some ideas, models, and more.

I do  not recommend going through it in one run. I can’t control it, but as I mention in the course, you want to space it out. We know that that leads to better outcomes. Instead, I recommend spacing it out a section a week or so perhaps, and doing the work and coming back to reactivate before moving on.

The content is organized around what I’m terming the Quinnov 8, the eight elements I think are core to making the step to better elearning design.  While the ideal is to push to a robust iterative and prototyping model, I’m focusing mostly on the small steps that will give you the greatest leverage. The elements are:

  1. Performance consulting: what to do  before you decide to course
  2. Objectives: making the  right decisions about what to focus on
  3. SMEs: working with them for objectives and more
  4. Practice: making practice meaningful
  5. Models: the conceptual frameworks that guide performance
  6. Examples: the link between concepts and application.
  7. Engagement: wrapping the front and back to create  experiences
  8. Process: the extra steps to make this work

I’m trying to go  deep, that is to unpack the levels of cognitive depth to explain how the Quinnov 8 elements work.  I’ve identified the challenges I’ve faced, and I may well update it over time, but it’s at a stage I think I can at least give you the chance to explore.  I welcome your feedback, but I reckon this is one way you can further your understanding on a significant budget.

Solutions for Tight Cycles of Assessment

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In general, in a learning experience stretching out over days (as spaced learning would suggest), learners want to regularly get feedback about how they’re doing. As a consequence, you want regular cycles of assessment. However, there’s a conflict.  In workplace performance we produce complex outputs (RFPs, product specs, sales proposals, strategies, etc). These still typically require human oversight to evaluate.  Yet resource limitations are likely in most such situations, so we prefer auto-marked solutions (read: multiple choice, fill-in-the-blank), etc.  How do we reconcile meaningful assessment with realistic constraints?  This is one of the questions I’ve been thinking about, and I thought I’d share my reflections with you.

In workplace learning, at times we can get by with auto-assessment, particularly if we use coaching beyond the learning event.  Yet if it matters, we’d rather them practice things that matter  before they actually are used for real work.  And for formal education, we want learners to have at least weekly cycles of performance and assessment.  Yet we also don’t want just rote knowledge checks, as they don’t lead to meaningful performance.  We need some intermediate steps, and that’s what I’ve been thinking on.

Multiple choice mini-scenario structureSo first, in  Engaging Learning, I wrote about what I called ‘mini-scenarios’. These are really just better-written multiple-choice questions.  However, such questions don’t ask learners to identify definitions or the like (simple recognition), but instead put learners in contextual situations.  Here, the learner chooses between different  decisions. Which means retrieving the information, mapping it to the context,  and then choosing the best answer.  Such a question has a story context, a precipitating situation, and then alternative decisions. (And the alternatives are ways learners go wrong, not silly or obviously incorrect choices).  I suggest that your questions should be like this, but are there more?

Branching scenarios are another, rich form of practice. Here it’s about tying together the decisions (they  do tend to travel in packs) and consequences. When you do so, you can provide an immersive experience.  (When designed well, of course.)  They’re a pragmatic approximation of a full game experience.  Full games are  really good when you need lots of practice (or can amortize over a large audience), but they’re an additional level of complexity to develop.

Another one that Tom Reeves presented in an article was intriguing. You not only have to make the right choice, but then you also choose the reason  why you made that choice. It’s only an additional step, but it gets at the choice  and the thinking.  And this is important. It would minimize the likelihood of guessing, and provide a richer basis for diagnosis and feedback.  Of course, no one is producing a ‘question type’ like this that I know of, but it’d be a good one.

An approach we used in the past was to have learners create a complex answer, but have the learner evaluate it! In this case it was a verbal response to a question (we were working on speaking to the media), but then the learner could hear their own answer and a model one.  Of course, you’d want to pair this with an evaluation guide as well. The learner creates a response, and then is presented with their response,  a good response, and a rubric about what makes a good answer. Then we ask the learner to self evaluate against the rubric.  This has the additional benefit that learners are evaluating work with guidance, and can internalize the behavior to become a self-improving learner. (This is the basis of ‘reciprocal teaching’, one of the component approaches in Cognitive Apprenticeship.)

Each of these is auto-(or self-) marked, yet provides valuable feedback to the learner and valuable practice of skills. Which shouldn’t be at the expense of also having instructor-marked complex work products or performances, but can supplement them. The goal is to provide the learner with guidance about how their understanding is progressing while keeping marking loads to a minimum. It’s not ideal, but it’s practical.  And it’s not exclusive of knowledge test as well, but it’s more applied and therefore is likely to be more valuable to the learner and the learning. I’m percolating on this, but I welcome hearing what approaches (and reflections) you have.

#AECT17 Conference Contributions

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So, at the recent AECT 2017 conference, I participated in three ways that are worth noting.  I had the honor of participating in two sessions based upon writings I’d contributed, and one based upon my own cogitations. I thought I’d share the thinking.

For my own presentation, I shared my efforts to move ‘rapid elearning’ forward. I put Van Merrienboer’s 4 Component ID and Guy Wallace’s Lean ISD as a goal, but recognized the need for intermediate steps like Michael Allen’s SAM, David Merrill’s ‘Pebble in a Pond‘, and Cathy Moore’s Action Mapping. I suggested that these might be too far, and want steps that might be slight improvements on their existing processes. These included three thing: heuristics, tools, and collaboration. Here I was indicating specifics for each that could move from well-produced to well-designed.

In short, I suggest that while collaboration is good, many corporate situations want to minimize staff. Consequently, I suggest identifying those critical points where collaboration will be useful. Then, I suggest short cuts in processes to the full approach. So, for instance, when working with SMEs focus on decisions to keep the discussion away from unnecessary knowledge. Finally, I suggest the use of tools to support the gaps our brain architectures create.   Unfortunately, the audience was small (27 parallel sessions and at the end of the conference) so there wasn’t a lot of feedback. Still, I did have some good discussion with attendees.

Then, for one of the two participation session, the book I contributed to solicited a wide variety of position papers from respected ed tech individuals, and then solicited responses to same.  I had responded to a paper suggesting three trends in learning: a lifelong learning record system, a highly personalized learning environment, and expanded learner control of time, place and pace of instruction. To those 3 points I added two more: the integration of meta-learning skills and the breakdown of the barrier between formal learning and lifelong learning. I believe both are going to be important, the former because of the decreasing half-life of knowledge, the latter because of the ubiquity of technology.

Because the original author wasn‘t present, I was paired for discussion with another author who shares my passion for engaging learning, and that was the topic of our discussion table.  The format was fun; we were distributed in pairs around tables, and attendees chose where to sit. We had an eager group who were interested in games, and my colleague and I took turns answering and commenting on each other’s comments. It was a nice combination.  We talked about the processes for design, selling the concept, and more.

For the other participation session, the book was a series of monographs on important topics.  The discussion chose a subset of four topics: MOOCs, Social Media, Open Resources, and mLearning. I had written the mLearning chapter.  The chapter format included ‘take home’ lessons, and the editor wanted our presentations to focus on these. I posited the basic mindshifts necessary to take advantage of mlearning. These included five basic principles:

  1. mlearning is not just mobile elearning; mlearning is a wide variety of things.
  2. the focus should be on augmenting us, whether our formal learning, or via performance support, social, etc.
  3. the Least Assistance Principle, in focusing on the core stuff given the limited interface.
  4. leverage context, take advantage of the sensors and situation to minimize content and maximize opportunity.
  5. recognize that mobile is a platform, not a tactic or an app; once you ‘go mobile’, folks will want more.

The sessions were fun, and the feedback was valuable.