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Clark Quinn’s Learnings about Learning

Information to Miniscenarios

13 December 2022 by Clark 2 Comments

I’ve talked in the past about miniscenarios. By this, I mean rewriting multiple choice questions (MCQs) to actually be situations requiring decisions and choices thereto. I evangelize this, regularly. I’ve also talked about what you need from subject matter experts (SMEs). What I haven’t really done is talk about how how you map information to miniscenarios. So it’s time to remedy that.

So, first, let’s talk about the structure of a mini-scenario. I’ve suggested that it’s an initial context or story, in which a situation precipitates the need for a decision. There’s the right one, and then alternatives. Not random or silly ones, but ones that represent ways in which learners reliably go wrong. There’s also feedback, which is best as story-based consequences first, then actual conceptual feedback.

So what’s the mapping? One of the things we (should) get from SMEs are the contexts in which these decisions come to play.  Thus, the setting for the mini-scenario is one of these contexts. It may be made fantastic in story, but the necessary contextual elements have to exist. (“Pat had been recently promoted to line supervisor…”)

Then, we have the decisions the learners need to be able to make. These often come in the form of performance objectives. This forms the basis for choosing a situation that precipitates the decision, and the decision itself. (“The errors in manufacturing were higher than the production agreement stipulated. Pat:”) Also, at least, the correct answer. (* worked backward through the process.)

The wrong answers come from some other information we need from SMEs: misconceptions. These are the ways that individuals go wrong when performing. I’ve advocated before that you may want different types of SMEs. It may be that supervisors of the performers have more insight here than content experts. Regardless, you want to make these alternatives available as possible responses. You’ll want to address the difficultly of discrimination between alternatives as a way to manipulate the challenge of the task; it should be appropriate to the learners’ level. (*asked team members what they thought the problem was; *exhorted the team to pay more attention to quality).

The feedback starts with the consequences, which you should also get from SMEs. What happens when you get it right? What happens with each wrong answer? These may come from stories about wins and losses that you also want to collect. (“Pat’s team did not like the implicit claim that they weren’t working hard enough.”)

Finally, there’re the models that are the basis for good performance, and consequently also the basis for the feedback. These you should also collect, because you use them to explain why a choice is good or bad. You don’t want to just say right or wrong, learners need to understand the underlying reason to reinforce their understanding. (Which may also mean they also need to see their answer with the feedback, so they remember what they chose.) Importantly, they need specific feedback for each wrong answer, btw, so your implementation tool needs to support that!  (When investigating errors, don’t start with the team. We always look at the process first, as system flaws need to be eliminated first.)

Pretty much everything you need from SMEs plays a role in providing practice. Miniscenarios aren’t necessarily the best practice, but they’re typically available in your authoring environment.  Writing them isn’t necessarily as easy as generating typical recognition questions, but they more closely mimic the actual task, and therefore lead to better transfer. Plus, you’ll get better as you practice. So  know the mapping of information to miniscenarios, practice your miniscenario writing, and put it into play!

Exposing myself

29 November 2022 by Clark Leave a Comment

This blog is where I “learn out loud”. I try to show my thinking. Yet, I realize I haven’t been doing that as much as I should, or perhaps not as effectively and mindfully as I should  So here’re some reflections on sharing my thinking, or ‘exposing myself’.

Worked examples, as we know from John Sweller, are most effective when they come before practice. Similarly, in Cognitive Apprenticeship, instructors model the desired performance. And I do try to share my thinking. However, I may not have been doing it properly. It needs to unpack the expertise; it can’t be just the knowledge, but what the thinking behind it is. The expertise that experts don’t have access to!

For instance, in my workshops, I often show the outcome of what I (with a team) did, after I have learners do it. Other times, like in the recent L&D conference, I shared my deeper thinking on analyzing technology through affordance, but then didn’t challenge learners to apply that themselves (to be fair, I only had an hour; on the other hand, I didn’t properly prepare).

Increasingly, I think one of the ways to scale my impact is to share my thinking, in context. When people are practitioners, that may be enough, but at some times it may also help to provide ‘challenges’ and provide feedback as well. That, however, doesn’t scale as well. I can only review so many projects…

I guess my biggest take away is to be more conscious about making the underlying thinking clear. I think it’s helpful to learn out loud, but also to ensure that I’m showing the thinking. So, I’ll keep exposing myself…or, at least, my thinking. I’ll try to do it more explicitly and clearly, as well.

Conference Outcomes?

24 November 2022 by Clark Leave a Comment

Two months ago, I wrote about the L&D Conference we were designing. In all fairness, I reckon I should report on how it went, now that it’s finished. There are some definite learnings, which we hope to bring forward, both for the conference (should we run it again, which we intend), and for the Learning & Development Accelerator (LDA; the sponsoring org, of which I’m co-director with Matt Richter) activities as well. So here are some thoughts on the conference outcomes.

Our design was to have two tracks (basic and advanced) and a limited but world-class faculty to cover the topics. We also were looking not just to replicate what you get at typical face-to-face conferences (which we like as well), but to do something unique to the medium and our audience. Thus, we weren’t just doing one-off sessions on a topic. Instead, each was an extended experience, with several sessions spread out over days or weeks.

The results of that seemed to work well. While not everybody who attended one of the sessions on a topic attended all, there was good continuity. And the feedback has been quite good; folks appreciate the deep dive with a knowledgeable and articulate expert. This, we figure, is an important result that we’re proud of. If someone misses a session, they can always review the video (we’re keeping the contents available for the rest of the year).

Our social events, networking and trivia, didn’t do quite so well. The networking night did have a small attendance but the trivia night didn’t reach critical mass. We attribute this at least partly to it being a later thought, and not promoting from the get-go.

We struggled a bit with scheduling. First, we spread it across changes in countries that switch to/from daylight savings time. The platform we used didn’t manage that elegantly, and we owe a lot to a staffer who wrestled that into submission. Still, it led to some problems in folks connecting at the right time. On the other hand, having the courses spread out meant we didn’t collide, you could attend any sessions you want (the tracks were indicative, not prescriptive).

The platform also had one place to schedule events, but it was as web page. As a faculty member opined, they wished they could’ve loaded all the sesssions into their calendar with one click. I resonate with that, because in moments when I might’ve had spare bandwidth to attend a session, I’m more likely to look at my calendar rather than the event page. Not sure there’s an easy solution, of course. Still, folks were able to find and attend sessions.

We also didn’t get the social interaction between the sessions we’d hoped, though there was great interaction during the sessions. Faculty and participants were consistent in that perspective. There was a lot of valuable sharing of experiences, questions, and advice.

One thing that, post-hoc, I realize is that it really helps to unpack the thinking. The faculty we chose are those who’ve demonstrated an ability to help folk see the underlying thinking. That paid off well! However, we realize that there may be more opportunities. An interesting discussion arose in a closing event about the value of debates; where two folks who generally agree on the science find something to diverge on. Everyone (including the debaters), benefit from that.

We’re going to be looking to figure out how to do more unpacking, and share the ability to do the necessary critical thinking around claims in our industry. The LDA focuses on evidence-based approaches to L&D. That requires a bit more effort than just accepting status quo (and associated myths, snakeoil, etc), but it’s worth it for our professional reputation.

So those are my reflections on the L&D Conference outcomes. Any thoughts on this, from attendees or others?

Learning Science Bandwagon?

8 November 2022 by Clark Leave a Comment

I’m not alone in carrying the banner for learning science. Others are talking about evidence-based practices, making it stick, and more. This, I maintain, is a good thing. Is there too much of good thing? Is there a problem with a learning science bandwagon?

First, let’s be clear. There are some initiatives that do strike me as redundant or worse. For one, folks have been talking about neuroscience. And I think neuroscience research is quite interesting! What I also believe, buttressed by others, is that there haven’t been any results from neuroscience that are essential for learning science design. All the implications have been previously documented from learning science research at the cognitive or social level. Neuroscience is cool, but its use in learning design tends to be to draw attention (read: marketing), not for any new outcomes.

I feel similarly about the term brain-based. Yes, learning is brain-based. Isn’t it a wee bit redundant to say so? I suppose they’re implying that they’re aligned with how the brain works. Which is a good thing. Still, despite the alliteration, it seems a bit more like hype than being informative. As the saying goes, your mileage may vary.

However, I’m seeing more and more people now talking about learning science. That’s a good thing. Are they jumping on a bandwagon? Maybe, but there’s lots of room. As long as folks are actually digging into what the learning say, and not just paying lip-service, they’re welcome. To be clear, I don’t own the wagon anyway; I’m a practitioner, not a core researcher. So, I really do think it’s great if more and more people start talking, and walking, learning science.

I’ll go further, of course. I think we should be paying attention to what cognitive and learning sciences say about how we think, work, and learn. That is, the applicability of understanding how our minds work goes beyond learning to our overall organizational practices. But, hey, we gotta start somewhere, right? I think it’s good if we’re moving in the right direction. I can quibble that it’s slower than I’d like, but progress is progress.

So, yay, more learning science! C’mon, jump on, the learning science bandwagon; we’ve got space and it appears we’re moving forward. All good. Hope you’ll join us!

Web 3.0 and whither the LMS

1 November 2022 by Clark 3 Comments

At the recent DevLearn conference, I was part of a Guild Master panel on emerging technologies. It featured notables such as Julie Dirksen, Mark Lassoff, Megan Torrence, Ron Price, Chad Udell, Karl Kapp, and Jane Bozarth, all hosted by Mark Britz. Not surprisingly, I guess, the topic went to the future of the LMS. In a session the next day, Dr. Jen Murphy of QIC talked insightfully (as she does) about the Metaverse, and compared it to Web 3.0. The conjunction of discussion prompted me to reflect on the intersection, considering Web 3.0 and whither the LMS.

To start, I’m not one proposing that the LMS should or will wither. I’ve suggested that courses make sense, particularly for novices. That said, they’re not full development plans. So it’s worth looking, and thinking, deeper. The conversation on the panel suggested the evolution of the LMS, and I think that’s an apt way to think about it.

What prompted this was Dr. Murphy’s comparison of Metaverse to Web 3.0. She argued that Web 3.0 was about user-control of content. That is, it’s about things like P2P, e.g. blockchain, NFT, etc. I’ve had a different view (now over a decade old, admittedly), that we’d moved from producer-generated content, through user-generated content, and the next would be system-generated content. AI can parse content (that people have painstakingly hand-crafted). Then systems can use models and rules to individualize the experience. That’s what web content is doing already.

So, have things changed? The recognition I see is that folks are concerned with identity and rights. Which I applaud, to be clear. The statement is that by having clear documentation, we can reward individual contributions instead of someone owning all the transactions. The latter of which would be part of a ‘system-generated’ web, for sure. Maybe my 3.0 is really 2.5? Or maybe theirs should be 4.0. Not sure I care…

What does matter is what that implies for courses. Obviously, if courses aren’t enough, we need a bigger picture. An associated question is who should own it? I see a development path as having many components. Even courses should be broken up for spacing, and have a follow-on for ongoing feedback whether digitally delivered and/or a coach. There was an LMS that actually allowed you to mix things into your paths: so you could interview someone, or read a book, or…other things besides courses. Made sense.

The other part aligns more closely with the user-controlled vision. I believe (and have stated, not that I can find it) that I think that ultimately, the community should own the path into membership. That is, just as we should determine the path into membership of L&D, a group in sales should determine what the necessary component skills are. They may need facilitation of this, but us ‘owning’ it isn’t right. We should merely be supporting the endeavor.

Again, it doesn’t really matter whether it’s labeled Web 3.0 or not, but I think that having a mechanism to track development, owned by the associated community (or communities) is useful. It’s not really a Learning Management System (you can’t really ‘manage’ learning), but it can include courses, and it is worthwhile. So those are my thoughts on Web 3.0 and whither the LMS, what’re yours?

Bethune #DevLearn Keynote Mindmap

26 October 2022 by Clark Leave a Comment

Kevin Bethune kicked off the 2022 DevLearn conference with a personal story about getting to delivering strategic innovation. Talking about interdisciplinary work that has an impact, he ended up laying out factors in leadership to support innovation. (Apologies, I had to take a brief break, so I missed a small bit. Sorry.)

Misusing affordances?

11 October 2022 by Clark Leave a Comment

Affordances is a complex term. Originally coined by Gibson, and popularized by Norman, it’s been largely used in terms of designing interfaces. Yet, it’s easy to misinterpret. I may have been guilty myself! In the past, I used it as a way to characterize technologies. Which isn’t really the intent, as it’s about sensory perception and action. So maybe I should explain what I mean, so you don’t think I’m misusing affordances.

To be clear, in interface design, it’s about the affordances you can perceive. If something looks like it can slide (e.g. a scrollbar), it lets you know you might be able to move the target of a related window in a field. Similarly a button affords pushing. One of the complaints about touch screens is that as people work to overload more functions on gestures. There might be affordances you can’t perceive: does a two-fingered swipe do anything differently than a single-finger swipe?

In my case, I’m talking more about what a technology supports. In my analysis of virtual worlds and mobile devices, I was looking to see what their core capabilities are, and so what we might naturally do with them. Similarly with media, what are their core natures?

So, for instance, an LMS’s core affordance is managing courses. Video captures dynamic context.  You might be able to do course management with a spreadsheet and some elbow grease, or you can mimic video with a series of static shots (think: Ken Burns) and narration, but the purpose-designed tool is likely going to be better. There are tradeoffs. You can graft on capabilities to a core, still an LMS won’t naturally serve as a resource repository or social media platform.

It’s an analytical tool, in my mind. You should end up asking: what’s the DNA? For example, you can match the time affordance of different mobile devices to the task. You can determine whether you need a virtual world or VR based upon whether you truly need visual or sensory immersion, action, and social (versus the tradeoffs of cost and cognitive overhead).

With an affordance perspective, you can make inferences about technologies. For instance, LXPs are really (sometimes smart) portals. AI (artificial intelligence)’s best application is IA (intelligence augmentation). AR’s natural niche, like mobile, is performance support. This isn’t to say that each can’t be repurposed in useful ways. AR has the potential to annotate the world. LXPs can be learning guides for those beyond novice stage. AI can serve in particular ways like auto-content parsing (more an automation than an augmentation). Etc.

My intent is that this way of thinking helps us short-circuit that age-old problem that we use new technologies first in ways that mimic old technologies (the old cliche of tv starting out by broadcasting radio shows). It’s a way to generate your own hype curve for technologies: over-enthusiasm leading to overuse, disappointment, and rebirth leveraging the core affordances. Maybe there’s a better word, and I’ve been misusing affordances, but I think the concept is useful. I welcome your thoughts.

Prompted by prep for the advanced seminar on instructional tech for the upcoming Learning & Development Conference.

Myth Persistence

4 October 2022 by Clark 2 Comments

It’s been more than a decade (and probably several), that folks have been busting myths that permeate our industry. Yet, they persist. The latest evidence was in a recent chat I was in. I didn’t call them out at the time; this was a group I don’t really know, and I didn’t want to make any particular person defensive or look foolish. Sometimes I will, if it’s a deliberate attempt at misleading folks, but here I believe it’s safe to infer that it was just a lack of understanding. I’ll keep calling them out here, though. However, the myth persistence is troubling.

One of the myths was learning preferences. The claim was something like that with personalization we could support people’s preferences for learning. This is, really, the learning styles myth. There’s no evidence that adapting to learners’ preferred or identified styles makes a difference. Learner intuitions about what works is not well correlated with outcomes.. So this wasn’t a sensible statement.

There were several comments on unlearning. There is some controversy on this, some people saying that it’s necessary for organizations if not individuals. I still think it’s a misconception, at least. That is, your learning doesn’t go away and something replaces it, you have to actively practice the new behavior in response to the same context to learn a new way of doing things. It’s people, after all, and that’s how our cognitive architecture works!

Gamification also got a mention. Again, this is more misconception perhaps. That is, it matters how you define it. We had Karl Kapp on the LDA’s You Oughta Know session, talking about gamification (and micro learning). He talks about understanding that it’s more than just points and leaderboards. Yes, it is. However, that term leads people quickly to that mindset, hence my resistance to the term. However, the chat seemed to suggest that gamification, in combination with something else (memory fails), was a panacea. There are no panaceas, and gamification isn’t a part of any major advance. It’s a ‘tuning’ tool, at best.

A final one was really about tech excitement; with all the new tools, we’ll usher in a new era of productivity. Well, no. The transformation really is not digital. That is, if we use tech to augment our existing approaches, we’re liable to be stuck in the same old approaches. Most of which are predicated on broken models of human behavior. The transformation should be humane, reflecting how we really think, work, and learn. Without that, digitization isn’t going to accomplish as much as it could.

So, there’s significant myth persistence. I realize change can be hard and take time. Sometimes that’s frustrating, but we have to be similarly persistent in busting them. I’ll keep doing my part. How about you?

The power of emotion

29 September 2022 by Clark Leave a Comment

Increasingly, we’re seeing that emotion matters. Scientific evidence supports what we intuitively know. Yet, in many cases, our actions don’t support that understanding. At least, in nuance. In particular, our learning designs suffer from trivialized ‘like’ as opposed to useful and effective approaches. We can and should do better to tap into the power of emotion.

Again, I’m using the term ’emotion’ loosely here. While we do care about emotions like joy and grief (though our picture is changing), what we really need to be caring about are non-cognitive elements like motivation, anxiety, and confidence. It’s about designing to appropriately address them: develop motivation, keep a lid on anxiety, and build confidence. Each has it’s elements.

Motivation improves learning outcomes, but requires understanding what makes us interested. We’re driven by a desire to understand the world (c.f. ‘predictive coding‘. Curiosity can assist in developing an interest. Certainly, self-interest plays a role as well, and helping people tune into the positive consequences of a learning experience (or the negative outcomes of not having the requisite understanding) is also useful. Self-Determination Theory (c.f. Deci and Ryan) talks about mastery, autonomy, and relatedness. We can use this to help people connect with others (instructors/peers/experts), give them tasks (autonomy) and support to succeed (mastery).

Anxiety interferes, if it’s too much. While a small amount helps, that’s quickly overwhelming. Given that learning can be intrinsically anxiety-inducing, keeping anxiety to a minimum is important. Making it safe to fail is an important component of this. Psychological safety is an important element in organizational operation, and learning as well.  We can not attach consequences to practice, certainly at first. We can also have the instructor make mistakes as well.

Building confidence is an adjunct here. As people master the skills, at greater and greater levels of challenge (an important component of successful learning experience design), they build confidence. That reduces anxiety, and maintains motivation. We don’t want false confidence, but we can steadily build confidence as we go. Ultimately, we want learners to have sufficient confidence to try out the skills (and succeed) after the learning experience.

There’s lots more that goes into making an experience effective and engaging, but understanding these elements, and how to enact them, is an important component. The power of emotion, properly harnessed, improves learning outcomes (which is what we should be about ;). I’ll be addressing these and more in my workshop Make It Meaningful at the upcoming DevLearn conference in Las Vegas on Oct 24. I’d love to see you there, as we talk about the complement to learning science that combines to achieve those experience goals.

Better RFPs, Please

27 September 2022 by Clark Leave a Comment

I regularly rant about the quality of the learning designs we see. Knowledge dump and information test, I rail, is not going to lead to meaningful outcomes. Consequently, I work to promote more learning science in what we do. However, I have to acknowledge that frequently, the problem isn’t in the designer, but in the requester. Too often, there are RFPs (emblematic, they’re equivalent to the internal request for ‘a course on X’) that are asking for designers to take content and essentially put it up on the screen with a quiz (and window dressing). So we need better RFPs, please.

Ideally, RFPs would be expecting a good process. That includes a number of steps, from analysis through to deliver. For instance, to expect due diligence in analysis, with either clear metrics of success, or expectations of an appropriate process. That latter would include where appropriate individuals (experts, supervisors, performers) work with the team to identify ideal performance, gaps, and the causes.

Similarly in design, there’d be an expectation of iterative development and review, with testing. Where’s the expectation of meaningful practice, where the lowest level of practice is mini-scenarios (better written multiple choice questions) through full scenarios, to even serious games? We need identification of misconceptions and specific feedback as well.

Yet, the RFPs that come out often focus on cost, visual design, and an expectation that PPTs and PDFs are a sufficient basis to build a course. I recently suffered through a droned presentation of bullet points and unclear diagrams, followed by quiz questions that a) focused on random knowledge that wasn’t emphasized during the presentation and b) provided as feedback only ‘right’ or ‘wrong’. Let me assure you that little meaningful learning came from that experience.

While we need to push ourselves to be better, we also need to educate our clients (internal or external). They need to educate themselves, too. Orgs will get the courses they ask for. However, will the ask have any impact? Too often, unfortunately, the answer is no. There’s a quote in the article The Great Training Robbery that estimates suggest only 10% of the multi-billions spent on training has any impact. That’s a staggering loss. While there are many contributors, it behooves us to try to address them all. For one, can we have better RFPs, please?

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