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Clark Quinn’s Learnings about Learning

Christopher Pirie #mlearncon Keynote Mindmap

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Christopher Pirie opened the eLearning Guild’s mLearnCon mobile learning conference with a fair overview of technology for learning.  He talked about the usual trends, and pointed to some interesting game apps for learning.  Kodu, in particular, is an interesting advancement on things like Scratch and StageCast’s Creator.

I was somewhat surprised by his pointer to Bloom as the turning point to modern learning design, as I’d be inclined to point more to Collins & Brown’s Cognitive Apprenticeship. I also think he should take a look at Donald Clark’s criticisms of Mitra’s Hole in the Wall.  Finally, the characterization between the overhead projector as characteristic of 1991 and the Kinect for 2012 is a bit spurious: in 1991 we also had HyperCard, and in 2012 I don’t see the Kinect in many classrooms yet, but his point is apt about the potential for change we have at our fingertips.

Overall, a nice kickoff for the conference.

PirieKeynoteMindmap

What I wish I’d learned in school

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I was asked, somewhat out of the blue, what I wish I’d learned in school, and I thought it an interesting question. I also thought it worth putting out to a slightly broader audience.

So, here’re some off-the-cuff thoughts about what I wish I’d learned in school:

  • meta-cognitive and meta-learning skills (e.g. the SCANS competencies beyond the basic skills)
  • that it is ok to fail, and that persistence and effort is as much a part of learning as achievement
  • that your epistemological beliefs – what you believe learning is – affect your outcomes
  • how to work in groups on projects
  • about design, and the value of feedback and revision
  • how reflection on process is as important as reflection on product

These are just a few thoughts, but it’s a start. And let me ask what you wish you’d learned in school?

Evidence-based Design

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In my last post, I asserted that we need evidence-based design for what we do.  There are a number of sources for same. Of course, you could go do a Master’s or Ph.D. in cognition and learning, but there are shorter paths.

There are several good books out (and I believer that there is at least one more on the way) that summarize the implications of research design. Ruth Clark has been a co-author on a couple, eLearning and the Science of Instruction, and the subsequent Efficiency in Learning.  Julie Dirksen’s Design for How People Learn is another good one. Michael Allen’s work on design is also recommended, e.g. Guide to eLearning.

Will Thalheimer, Ruth, and Julie regularly write and talk about these things in other forums than books.  Go listen to them!  I try as well, though often filtered through games, mobile, or elsewhere.  There’re others, too.

A number of people run workshops on deeper design. I know I have one, and I’m sure others have them as well. Do try to make sure that it covers both cognitive and emotional elements, focusing on meaningful change.

There are gaps: there isn’t all the research we need, or at least not digested.  The role of emotional engagement isn’t as well fleshed out as we’d like, and some of the research is frankly focused on studies too small to give practical guidelines (c.f. the consternation on serious game design that surrounded a recent post).  Where we don’t have research, we have to make inferences from theoretical frameworks, but you should know those too.  It’s better than going on ‘intuition’ or folk science.

Still, there’s no excuse to do un-engaging, over-written, and under-practiced learning.  Better design doesn’t take longer (with the caveat that there’s some initial hiccup ’til we make the change).  We have the knowledge, and the tools aren’t the barrier.  Let’s do better, please!

No Folk Science-Based Design!

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When we have to act in the world, make decisions, there are a lot of bases we use.  Often wrongly.  And we need to call it out and move on.

As I pointed out before, Kahneman tells us how we often make decisions on less than expert reflection, more so when we’re tired, and create stories about why we do it. If we’re not experts, we shouldn’t trust our ‘gut’, but we do.  And we will use received wisdom, rightly or wrongly, to justify our choices.  Yet sometimes the beliefs we have about how things work are wrong.

While there’s a lot of folk science around that’s detrimental to society and more, I want to focus on folk science that undermines our ability to assist people in achieving their goals, supporting learning and performance.  Frankly, there are a lot of persistent myths that are used to justify design decisions that are just wrong.  Dr. Will Thalheimer, for instance, has soundly disabused Dale’s Cone.  Yet the claims continue. There’re more: learning styles, digital natives, I could go on.  They are  not sound bases for learning design!

It goes on: much of what poses under ‘brain-based’ learning, that any interaction is good, that high production values equal deep design, that knowledge dump and test equals learning.  Folks, if you don’t  know, don’t believe it.  You  have  to do better!

Sure, some of it’s compelling.  Yes, learners do differ.  That doesn’t mean a) that there are valid instruments to assess those differences, or more importantly b) that  you should teach them differently.  Use the best learning principles, regardless!   And using the year someone’s born to characterize them really is pretty coarse; it almost seems like discrimination.

Look, intuition is fine in lieu of any better alternative, but when it comes to designing solutions that your organization depends on, doing anything less than science-based design is frankly fraudulent.  It’s time for evidence-based design!

Animations

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I’ve been thinking more about animations of late.  I am a big fan of diagrams (as you probably infer :), and animations add an important dimension.  However, they’re more problematic to create.  Yet I’ll argue that they can be really powerful.

As Larkin & Simon pointed out in their landmark Cognitive Science article  (PDF) “Why a diagram is (sometimes) worth ten thousand words”, a mental model is composed of conceptual relationships between the elements.  And a mental model provides predicative and explanatory power: you can infer from the model why something happened or how to do something.  A diagram maps those conceptual relationships to spatial relationships, providing a memorable framework to both comprehend and remember that model.

Now, sometimes the relationships aren’t static, but change under different conditions.  Then, we need to convey those changes, and so we need a moving diagram, an animation.  An animation can convey things like the effects of introductions of various factors on related elements, such as heat in a steam system, or chemicals in an ecosystem, helping learners understand the dynamic relationships.

For instance, the diagrams I used yesterday to convey a meta-learning architecture could be animated to show the flow and aggregation of the information of competencies over time.  Similarly, for those who have trouble visualizing use of the experience API, an animation could show how individual activity generates data that can be aggregated and then mined, either for specific answers or with machine learning for new insights.  I think that there may be a barrier to comprehending the whole picture (more than happy to be wrong), and here an animation could help.

Animation is inherently more complex than creating diagrams, and requires additional skills than just static visualization.  Consequently, I haven’t developed that particular capability, but I strongly encourage design teams to acquire that capability either internally or a strong partner.

I like the Common Craft ones, which typically include this sort of dynamic relationship exposition, but also narrative (which you also see in  RSA Animate, another favorite).  I remember the ones that explained reproduction that they showed us in school many years ago, stripping away the yucky bits so we could understand the underlying processes (and risks).  Can you think of animations that have really helped you comprehend something?

Integrating Meta-learning

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There’s much talk about 21st Century skills, and rightly so: these skills are the necessary differentiators for individuals and organizations, going forward.  If they’re important, how do we incorporate them into systems, and track them?  You can’t do them in a vacuum, they only can be brought out in the context of other topics.  We can integrate them by hand, and individually assess them, but how do we address them in a technology-enabled world?  In the context of a project, here’s where my thinking is going:

MetaLearningTaggingFirst, you have some domain activity you are having the learner engage in. It might be something in math, science, social studies, whatever (though ideally focused on applied knowledge). Then you give them an assignment, and it might have a number of characteristics: it might be social, e.g. working with others, or problem solving. You could choose many characteristics, e.g. from the SCANS competencies (using information technology, reasoning), that the task entails.  That task is labeled with tags associated with the required competency, and tracked via SCORM or more appropriately with the Experience API.  There may be more than two, but we’ll stick with that model here.

MetaLearningStructureSo, when we then look across topics that the learner is engaging in, and the characteristics of the assignments, we can look for patterns across competencies. Is there a particular competency that is troubling or excelling?  It’s somewhat indirect, but it’s at least one way of systematically embedding meta-learning skills and tracking them.  And that’s a lot better than we’re doing now.

Remember the old educational computer games that said ‘develops problem solving skills’?  That was misleading. Most of those games ‘required’ problem-solving skills, but no real development of said skills was embedded.  A skilled parent or teacher could raise discussion across the problems, but most of the games didn’t.  But they could. Moreover, additional 21C resources could be made available for the assignments that required them, and there could be both programmatic or mentor intervention to develop these.

We need to specifically address meta-learning, and with technology we can get evidence.  And we should.  Now, my two questions are: does the concept make sense?  And does the diagram communicate it?

Extending Learning

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At the just concluded ASTD International Conference and Exhibition, on exhibit were, finally, two instances of something that should’ve been obvious. And I’m not alone in having waited.

SpacedPracticeSeveral years ago, Dr. Will Thalheimer was touting a ‘learning follow-on’ solution, a mechanism to continue to reactivate knowledge after a learning experience. He’s talked about the spacing effect (even providing the basis for a diagram in Designing mLearning), drawing upon his experience as one of our best proponents of evidence-based learning design. We know that reactivation leads to better outcomes, whether seeing a re-representation of the concept, a new example (ideally in another context), and most usefully, having more practice. I’m not aware of how the solution he was touting at the time, but as we really haven’t seen any significant awareness raising, I’m not optimistic.

However, at the conference were two separate examples of such systems. They worked differently, but that they exist at all is a positive outcome. Both used diagrams (e.g. Ebbinghaus forgetting curve) to show the effects of memory over time, and it’s apt that the problem is real. If we just use the traditional event model, things are likely to be gone a few days later if it’s not immediately put into action. That doesn’t characterize many of our learning outcomes.

The solutions were different, of course. One used mobile technology to provide reminders and access to content. The other used the web. Both basically provided the same opportunity. I didn’t evaluate the relative costs, ease of integration, etc, but having such capability is great. It’s something that folks could arrange for themselves, but as yet I haven’t really seen it, at least not in a systematic way.

They still separate solutions, not integrated, but it’s reason for hope. It’s surprising no one’s baked it into their LMS, but there you go. At least we’re seeing the beginning of awareness, and hopefully we’ll get more.

Assessing online assessments

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Good formal learning consists of an engaging introductions, rich presentation of concepts, annotated examples, and meaningful practice, all aligned on cognitive skills. As we start seeing user-generated online c, publishers and online schools are feeling the pressure. Particularly as MOOCs come into play, with (decreasingly) government funded institutions giving online content and courses for free. Are we seeing the demise of for-profit institutions and publishers?

I will suggest that there’s one thing that is harder to get out of the user-generated content environment, and that’s meaningful practice. I recall hearing of, but haven’t yet seen, a seriously threatening repository of such. Yes, there are learning object repositories, but they’re not yet populated with a rich suite of contextualized practice.

Writing good assessments is hard. Principles of good practice include meaningful decisions, alternatives that represent reliable misconceptions, relevant contexts, believable dialog, and more. They must be aligned to the objectives, and ideally have an increasing level of challenge.

There are some technical issues as well. Extensions that are high value include problem generators and randomness in the order of options (challenging attempts to ‘game’ the assessment). A greater variety of response options for novelty isn’t bad either, and automarking is desirable for at least a subset of assessment.

I don’t want to preclude essays or other interpretive work like presentations or media content, and they are likely to require human evaluation, even with peer marking. Writing evaluation rubrics is also a challenge for untrained designers or experts.

While SMEs can write content and even examples (if they get pedagogical principles and are in touch with the underlying thinking, but writing good assessments is another area.

I’ve an inkling that writing meaningful assessments, particularly leveraging interactive technology like immersive simulation games, is an area where skills are still going to be needed. Aligning and evaluating the assessment, and providing scrutable justification for the assessment attributes (e.g. accreditation) is going to continue to be a role for some time.

We may need to move accreditation from knowledge to skills (a current problem in many accreditation bodies), but I think we need and can have a better process for determining, developing, and assessing certain core skills, and particularly so-called 21st century skills. I think there will continue to be a role for doing so, even if we make it possible to develop e necessary understanding in any way the learner chooses.

As is not unusual, I’m thinking out loud, so I welcome your thoughts and feedback.

Designing Higher Learning

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I’ve been thinking a lot about the higher education situation, specifically for-profit universities. One of the things I see is that somehow no one’s really addressing the quality of the learning experience, and it seems like a huge blindspot.

I realize that in many cases they’re caught between a rock and a hard place. They want to keep costs down, and they’re heavily scrutinized.  Consequently, they worry very much about having the  right  content.  It’s vetted by Subject Matter Experts (SMEs), and has to be produced in a way that, increasingly, it can serve face to face (F2F) or online.  And I think there’s a big opportunity missed.  Even if they’re buying content from publishers, they are focused on content, not  experience.  Both for the learner, and developing learner’s transferable and long-term skills.

First, SMEs can’t really tell you what learners need to be able to do. One of the side-effects of expertise is that it gets compiled away, inaccessible to conscious access.  Either SMEs make up what they  think  they do (which has little correlation with reality) or they resort to what they had to learn. Neither’s a likely source to meaningful learning.

Even if you have an instructional designer in the equation, the likelihood that they’re knowledgeable enough and confident enough to work with SMEs to get the real outcomes/objectives is slim.  Then, they also have to get the engagement right.  Social engagement can go a good way to enriching this, but it has to be around meaningful tasks.

And, what with scrutiny, it takes a strong case to argue to the accrediting agencies that you’ve gone beyond what SMEs tell you to what’s really needed. It sounds good, but it’s a hard argument to an organization that’s been doing it in a particular way for a long time.

Yet, these institutions also struggle with retention of students.  The learners don’t find the experience relevant or engaging, and leave.  If you took the real activity, made it meaningful in the right way, learners would be both more engaged and have better outcomes, but it’s a hard story to comprehend, and perhaps harder yet to implement.

Yet I will maintain that it’s both doable, and necessary.  I think that the institution that grasps this, and focused on a killer learning experience, coupled with going the extra mile to learner success (analytics is showing to be a big help here), and developing them as learners (e.g, meta-learning skills) as well as performers, is going to have a defendable differentiator.

But then, I’m an optimist.

Sach’s Winning the Story Wars

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On a recommendation, I’ve been reading Jonah Sach’s Winning the Story Wars.   While it’s ostensibly about marketing/advertising, which interests me not,  I was intrigued by the possibilities to understand stories from a different perspective.   I was surprised to find that it offered much more.

The book does cover the history of advertising, going through some classic examples of old-style advertising, and using some surprisingly successful examples to elicit a new model.  Some personal stories and revelations make this more than a conceptual treatise.

The core premise  is turning your customer into a potential hero of an important journey.  You play the role of the mentor, providing the magic aid for them to accomplish a goal that they know they need, but for a variety of reasons may have avoided.  The journey is motivated from core values, a feature that resonates nicely with my personal quest for using technology to facilitate wisdom.

The book also provides, as one of the benefits, a nice overview of story, particularly the hero’s journey as synthesized by Joseph Campbell across many cultures and time periods.  If you find Campbell a tough read, as many do, this is a nicely digested version.  It talks in sensible ways about the resistance, and trials, and ultimate confrontation.

The obvious focus is on new way to build your brand, tapping into higher purpose, not the more negative fears of inadequacy.  So this book  is valuable for those looking to market in a higher way.  And I do intend to rethink the Quinnovation site as a consequence.  But I suggest there’s more.

The notion of the individual being offered the opportunity to play a transformative role seems to be a useful framing for learning. We can, and should, be putting learners in meaningful practice roles, and those roles can be coming from learners’ deep motivators.  One of the heuristics in learning game design is Henry Jenkins’ “put the player in a role they’d like to be in”.  This provides a deeper grounding,  put the learner in a role they aspire to be in.

I think this book provides not only practical marketing advice, but also guidance for personal journeys and learning.  I think that the perspective of designing stories and roles that are based on personal values to be a great opportunity to do better design. I haven’t completely finished it yet, but I’ve already found enough value in the majority of it to recommend it to you.