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Archives for June 2021

Misaligned expectations

29 June 2021 by Clark 1 Comment

As part of the Learning Development Conference that’s going on for the next five weeks (not too late to join in!), there have already been events. Given that the focus is on evidence-based approaches, a group set up a separate discussion room for learning science. Interestingly, though perhaps not surprisingly, our discussion ended up including barriers. One of the barriers, as has appeared in several guises across recent conversations, are the expectations on L&D. Some of them are our own, and some are others, but they all hamper our ability to do our best. So I thought I’d discuss some of these misaligned expectations.

One of the most prominent expectations is around the timeframes for L&D work. My take is that after 9/11, a lot of folks didn’t want to travel, so all training went online. Unfortunately (as with the lingering pandemic), there was little focus on rethinking, and instead a mad rush to get things online. Which meant that a lot of content-based training ended up being content-based elearning. The rush to take content and put it onscreen drove some of the excitement around ‘rapid elearning’.

The continuing focus on efficiency – taking content, adding a quiz, and putting it online – was pushed to the extreme.  It’s now an expectation that with an authoring tool and content, a designer can put up a course in 1-2 weeks. Which might satisfy some box-checking, but it isn’t going to lead to any change in meaningful outcomes. Really, we need slow learning! Yet there’s another barrier here.

Too often, we have our own expectation that “if we build it, it is good”. That is, too often we take an order for a course, we build it, and we assume all is well. There’s no measurement to see if the problem is fixed, let alone tuning to ensure it is. We don’t have expectations that we need to be measuring our impact! Sure it’s hard; we have to talk to the business owners about measurement, and get data. Yet, like other areas of the organization, we should be looking for our initiatives to lead to measurable change. One of these days, someone’s going to ask us to justify our expenditures in terms of impact, and we’ll struggle if we haven’t changed.

Of course, another of our misaligned expectations is that our learning design approaches are effective. We still see, too often, courses that are content-dump, not serious solutions. This is, of course, why we’re talking about learning science, but while one of us had support to be evidence-based, others still do not. We face a populace, stakeholders  and our audiences, that have been to school. Therefore, the expectation is that if it looks like school, it must be learning. We have to fight this.

It d0esn’t help that well-designed (and well-produced) elearning is subtly different than just well-produced elearning. We can’t (and, frankly, many vendors get by on this) expect our stakeholders to know the difference, but we must and we must fight for the importance of the difference. While I laud the orgs that have expectations that their learning group is as evidence-based as the rest, and their group can back that up with data, they’re sadly not as prevalent as we need.

There are more, but these are some major expectations that interfere with our ability to do our best. The solution? That’s a good question. I think we need to do a lot more education of our stakeholders (as well as ourselves). We need to (gently, carefully) generate an understanding that learning requires practice and feedback, and extends beyond the event. We don’t need everyone to understand the nuances (just as we don’t need to know the details of sales or operations or…unless we’re improving performance on it), but we do need them to be thinking in terms of reasonable amounts of time to develop effective learning, that this requires data, and that not every problems has a training solution. If we can adjust these misaligned expectations, we just might be able to do our job properly, and help our organizations. Which, really, is what we want to be about anyway.

Doing Gamification Wrong

22 June 2021 by Clark 8 Comments

roulette wheelAs I’ve said before, I’m not a fan of ‘gamification’. Certainly for formal learning, where I think intrinsic motivation is a better area to focus on than extrinsic. (Yes, there are times it makes sense, like tarting up rote memory development, but it’s under-considered and over-used.)  Outside of formal learning, it’s clear that it works in certain places. However, we need to be cautious in considering it a panacea. In a recent instance, I actually think it’s definitely misapplied. So here’s an example of doing gamification wrong.

This came to me via a LinkedIn message where the correspondent pointed me to their recent blog article. (BTW, I don’t usually respond to these, but if I do, you’re going to run the risk that I poke holes. 😈) In the article, they were talking about using gamification to build organizational engagement. Interestingly, even in their own article, they were pointing to other useful directions unknowingly!

The problem, as claimed, is that working remote can remove engagement. Which is plausible. The suggestion, however, was that gamification was the solution. Which I suggest is a patch upon a more fundamental problem. The issue was a daily huddle, and this quote summarizes the problem: “there is zero to little accountability of engagement and participation “.  Their solution: add points to these things. Let me suggest that’s wrong.

What facilitates engagement is a sense of purpose and belonging. That is, recognizing that what one does contributes to the unit, and the unit contributes to the organization, and the organization contributes to society. Getting those lined up and clear is a great way to build meaningful engagement. Interestingly, even in the article they quote: “to build true engagement, people often need to feel like they are contributing to something bigger than themselves.” Right! So how does gamification help? That seems to be trying to patch a  lack of purpose. As I’ve argued before, the transformation is not digital first, it’s people first.

They segue off to microlearning, without (of course) defining it. They ended up meaning spaced learning (as opposed to performance support). Which, again, isn’t gamification but they push it into there. Again, wrongly. They do mention a successful instance, where Google got 100% compliance on travel expenses, but that’s very different than company engagement. It’s  got to be the right application.

Overall, gamification by extrinsic motivation can work under the right circumstances, but it’s not a solution to all that ails an organization. There are ways and times, but it’s all too easy to be doing gamification wrong. ‘Tis better to fix a broken culture than to patch it. Patching is, at best, a temporary solution. This is certainly an example.

 

Update on my events

17 June 2021 by Clark Leave a Comment

In January I posted about my upcoming webinars (now past), workshops, etc. As things open up again (yay, vaccines), some upcoming events will be happening live!  And, of course, virtual. In fact, one starts next week! So I thought it time to update you on the things I’ll be doing. Then we’ll get back to my regular posts ;). So here’s an update on my events.

First, starting next week, is the Learning Development Conference, by the Learning Development Accelerator (caveat: I’m on their advisory board). Last year, it was an experiment. They did several things very well: it was focused on evidence-based approaches, it created timings that worked for a broad section of the world’s populace (e.g. live sessions were offered twice, once early once late), and it had asynchronous content as well as synchronous. It also had ways to maintain contact and discussions. As a result, it was a success, leading to the Accelerator and this second event.

It’s for six weeks, and first I’ve got an asynchronous course on learning science (a subset of the bigger one I do as a blended workshop for HR.com/Allen Academy). I’m also doing two live sessions (at different times) on some of the new results from cognitive science. I’m already dobbed in for one debate, and they’ll likely call on me for more. There are also a suite of the top names in evidence-based L&D appearing doing either or both of live or asynchronous content.

Second, at the end of August, I’ll be speaking at ATD’s International Conference and Exposition. This is a live event in Salt Lake City. (My first since the pandemic!) Of course I’m speaking on learning science; the topic of my book with them. There could even be a book-signing event!  If you don’t know ATD’s ICE, it’s huge, both a blessing and curse. Lots of quality content (ok, mostly ;), almost too many people to find your friends, but lots of new friends to make, with broad coverage. Also, a big exposition (maybe smaller this year ;).

Third, I’ll be at the Learning Guild’s DevLearn again this year. This has always been one of the best conferences because the Guild runs good events (caveat: I’m their first Guild Master). They want it to grow, of course, but as yet it’s still be reasonably sized, and with quality content. For one, I’ll be speaking on learning science implications.

I’ll  also be running a pre-conference workshop on Making Learning Meaningful. And this is, I suggest, truly of interest. I’ve been seeing more and more examples of well-designed content that’s still lacking in engagement, and this workshop is all about that. It’s an area I’ve been actively exploring and synthesizing into practical implications. Like in the series I did on the topic here, I cover how to hook initial interest, then maintain it through the experience. Also considered are the implications for the elements of learning, and a process to make it practical.

I recommend all three (or I wouldn’t be inclined to speak at them). So that’s the current update on my events. Hope to see you at one or another!

Exploring Exploration

15 June 2021 by Clark Leave a Comment

Compass  Learning, I suggest, is action and reflection. (And instruction should be  designed action and  guided reflection.) What that action typically ends up being is some sort of exploration (aka experimentation). Thus, in my mind, exploration is a critical concept for learning. That makes it worth exploring exploration.

In learning, we must experiment (e.g. act) and observe and reflect on the outcomes. We learn to minimize surprise, but we also act to generate surprise. I stipulate that we do so when the costs of getting it wrong are low. That is, making learning  safe. So providing a safe sandbox for exploration is a support for learning. Similarly, have low consequences for mistakes generated through informal learning.

However, our explorations aren’t necessarily efficient nor effective. Empirically, we can make ineffective choices such as changing more than one variable at a time, or missing an area of exploration completely. For instruction, then, we need support. Many years ago, Wallace Feurzig argued for  guided exploration, as opposed to free search (the straw man used to discount constructivist approaches). So putting constraints on the task and/or the environment can support making exploration more effective.

Exploration also drives informal learning. Diversity on a team, properly managed, increases the likelihood of searching a broader space of solutions than otherwise. There are practices that increase the effectiveness of the search. Similarly, exploration should be focused on answering questions. We also want serendipity, but there should be guidelines that keep the consequences under control.

By making exploration safe and appropriately constrained, we can advance our understanding most rapidly, either helping some folks learn what others know, or advance what we all know. Exploration is a key to learning, and we need to understand it. Thus, we should also keep exploring exploration!

New recommended readings

8 June 2021 by Clark Leave a Comment

My Near Book ShelfOf late, I‘ve been reading quite a lot, and I‘m finding some very interesting books. Not all have immediate take homes, but I want to introduce a few to you with some notes. Not all will be relevant, but all are interesting and even important. I‘ll also update my list of recommended readings. So here are my new recommended readings. (With Amazon Associates links: support your friendly neighborhood consultants.)

First, of course, I have to point out my own Learning Science for Instructional Designers. A self-serving pitch confounded with an overload of self-importance? Let me explain. I am perhaps overly confident that it does what it says, but others have said nice things. I really did design it to be the absolute minimum reading that you need to have a scrutable foundation for your choices. Whether it succeeds is an open question, so check out some of what others are saying. As to self-serving, unless you write an absolute mass best-seller, the money you make off books is trivial. In my experience, you make more money giving it away to potential clients as a better business card than you do on sales. The typically few hundred dollars I get a year for each book aren‘t going to solve my financial woes! Instead, it‘s just part of my campaign to improve our practices.

So, the first book I want to recommend is Annie Murphy Paul‘s The Extended Mind. She writes about new facets of cognition that open up a whole area for our understanding. Written by a journalist, it is compelling reading. Backed in science, it’s valuable as well. In the areas I know and have talked about, e.g. emergent and distributed cognition, she gets it right, which leads me to believe the rest is similarly spot on. (Also her previous track record; I mind-mapped her talk on learning myths at a Learning Solutions conference). Well-illustrated with examples and research, she covers embodied cognition, situated cognition, and socially distributed cognition, all important. Moreover, there‘re solid implications for the redesign of instruction. I‘ll be writing a full review later, but here‘s an initial recommendation on an important and interesting read.  

I‘ll also alert you to Tania Luna‘s and LeeAnn Renninger‘s Surprise. This is an interesting and fun book that instead of focusing on learning effectiveness, looks at the engagement side. As their subtitle suggests, it‘s about how to Embrace the Unpredictable and Engineer the Unexpected. While the first bit of that is useful personally, it‘s the latter that provides lots of guidance about how to take our learning from events to experiences. Using solid research on what makes experiences memorable (hint: surprise!) and illustrative anecdotes, they point out systematic steps that can be used to improve outcomes. It‘s going to affect my Make It Meaningful  work!

Then, without too many direct implications, but intrinsically interesting is Lisa Feldman Barrett‘s How Emotions Are Made. Recommended to me, this book is more for the cog sci groupie, but it does a couple of interesting things. First, it creates a more detailed yet still accessible explanation of the implications of Karl Friston‘s Free Energy Theory. Barrett talks about how those predictions are working constantly and at many levels in a way that provides some insights. Second, she then uses that framework to debunk the existing models of emotions. The experiments with people recognizing facial expressions of emotion get explained in a way that makes clear that emotions are not the fundamental elements we think they are. Instead, emotions social constructs! Which undermines, BTW, all the facial recognition of emotion work.

I also was pointed to Tim Harford‘s The Data Detective, and I do think it‘s a well done work about how to interpret statistical claims. It didn‘t grip me quite as viscerally as the afore-mentioned books, but I think that‘s because I (over-)trust my background in data and statistics. It is a really well done read about some simple but useful rules for how to be a more careful reviewer of statistical claims. While focused on parsing the broader picture of societal claims (and social media hype), it is relevant to evaluating learning science as well.  

I hope you find my new recommended readings of interest and value. Now, what are you recommending to me? (He says, with great trepidation. ;)

The case for model answers (and a rubric)

3 June 2021 by Clark 4 Comments

Human body modelAs I‘ve been developing online workshops, I‘ve been thinking more about the type of assessment I want. Previously, I made the case for gated submissions. Now I find another type of interaction I‘d like to have. So here‘s the case for model answers (and a rubric).

As context, many moons ago we developed a course on speaking to the media. This was based upon the excellent work of the principals of Media Skills, and was a case study in my  Engaging Learning book. They had been running a face to face course, and rather than write a book, they wondered if something else could be done. I was part of a new media consortium, and was partnered with an experienced CD ROM developer to create an asynchronous elearning course.  

Their workshop culminated in a live interview with a journalist. We couldn‘t do that, but we wanted to prepare people to succeed at that as an optional extra next step. Given that this is something people really fear (apocryphally more than death), we needed a good approximation. Along with a steady series of exercises going from recognizing a good media quote, and compiling one, we wanted learners to have to respond live. How could we do this?

Fortunately, our tech guy came up with the idea of a programmable answering machine. Through a series of menus, you would drill down to someone asking you a question, and then record an answer. We had two levels: one where you knew the questions in advance, and the final test was one where you‘d have a story and details, but you had to respond to unanticipated questions.  

This was good practice, but how to provide feedback? Ultimately, we allowed learners to record their answers, then listen to their answers and a model answer. What I‘d add now would be a rubric to compare your answer to the model answer, to support self-evaluation. (And, of course, we’d now do it digitally in the environment, not needing the machine.)

So that‘s what I‘m looking for again. I don‘t need verbal answers, but I do want free-form responses, not multiple-choice. I want learners to be able to self-generate their own thoughts. That‘s hard to auto-evaluate. Yes, we could do whatever the modern equivalent to Latent Semantic Analysis is, and train up a system to analyze and respond to their remarks. However, a) I‘m doing this on my own, and b) we underestimate, and underuse, the power of learners to self-evaluate.  

Thus, I‘m positing a two stage experience. First, there‘s a question that learners respond to. Ideally, paragraph size, though their response is likely to be longer than the model one; I tend to write densely (because I am). Then, they see their answer, a model answer, and a self-evaluation rubric.  

I‘ll suggest that there‘s a particular benefit to learners‘ self-evaluating. In the process (particularly with specific support in terms of a mnemonic or graphic model), learners can internalize the framework to guide their performance. Further, they can internalize using the framework and monitoring their application to become self-improving learners.

This is on top of providing the ability to respond in richer ways that picking an option out of those provided. It requires a freeform response, closer to what likely will be required after the learning experience. That‘s similar to what I‘m looking for from the gated response, but the latter expects peers and/or instructors to weigh in with feedback, where as here the learner is responsible for evaluating. That‘s a more complex task, but also very worthwhile if carefully scaffolded.  

Of course, it‘d also be ideal if an instructor is monitoring the response to look for any patterns, but that‘s outside the learners‘ response. So that‘s the case for model answers. So, what say you? And is that supported anywhere or in any way you know?

How to be an elearning expert

1 June 2021 by Clark 3 Comments

I was asked (and have been a time or two before): “What’s the one most important thing you’d like to tell to be successful Ed Tech industry leader” Of course there wasn‘t just one ;). Still, looking at colleagues who I think fit that characterization, I find some commonalities that are worth sharing. So here‘s one take on how to be an elearning expert.

Let‘s start with that ‘one thing‘.   Which is challenging, since it‘s more than one thing! Still, I boiled it down into two components: know your stuff, and let people know.   That really is the core. So let‘s unpack that some more.   The first thing is to establish credibility. Which means demonstrating that you track and promote the right stuff.  

Some folks have created a model that they tout. Cathy Moore has Action Mapping, Harold Jarche has PKM, Con Gottfredson has the 5 moments of need, and so on.   It‘s good having a model, if it‘s a good, useful one (there are people who push models that are hype or ill-conceived at best). Note that it‘s not necessarily the case that these folks are just known for this model, and most of these folks can talk knowledgeably about much more, but ‘owning‘ a model that is useful is a great place to be. (I occasionally regret that I haven‘t done a good job of branding my models.) They understand their model and its contribution, it‘s a useful one, and therefore they contribute validly that way and are rightly recognized.

Another approach like this is owning a particular domain. Whether gaming (e.g. Karl Kapp), visuals (Connie Malamed), design (Michael Allen), mixed realities (Ann Rollins), AI (Donald Clark), informal (Jane Hart), evaluation (Will Thalheimer), management (Matt Richter), and so on, they have deep experience and a great conceptual grasp in a particular area. Again, they can and do speak outside this area, but when they talk about these topics in particular, what they say is worthy of your attention!

Then there are other folks who don‘t necessarily have a single model, but instead reliably represent good science. Julie Dirksen, Patti Shank, Jane Bozarth, Mirjam Neelen, and others  have established a reputation for knowing the learning science and interpreting it in accurate, comprehensible, and useful ways.  

The second point is that these folks write and talk about their models and/or approaches. They‘re out there, communicating. It‘s about reliably saying the important things again and again (always with a new twist). A reputation doesn‘t just emerge whole-cloth, it‘s built step by step. They also practice what they preach, and have done the work so they can talk about it. They talk the talk and walk the walk. Further, you can check what they say.  

So how to start? There are two clear implications. Obviously, you have to Know. Your. Stuff! Know learning, know design, know engagement, know tech. Further, know what it means in practice!   You can focus deeply in one area, or generate one useful and new model, or have a broad background, but it can‘t just be in one thing. It‘s not just all your health content for one provider. What you‘re presenting needs to be representative and transferable.  Further, you need to keep up to date, so that means continually learning: reading, watching, listening.

Second, it‘s about sharing. Writing and speaking are the two obvious ways. Sure, you can host a channel: podcast, vlog, blog, but if you‘re hosting other folks, you‘re seen as well connected but not necessarily as the expert. Further, I reckon you have to be able to write and speak (and pretty much all of these folks do both well).   So, start by speaking at small events, and get feedback to improve. Study good presentation style. Then start submitting for events like the Learning Guild, ATD, or LDA (caveats on all of these owing to various relationships, but I think they‘re all scrutable). I once wrote about how to read and write proposals, and I think my guidance is still valid.

Similarly, write. Learning Solutions or eLearn Mag are two places to put stuff that‘s sensibly rigorous but written for practitioners.   Take feedback to heart, and deliberately improve. Make sure you‘re presenting value, not pitching anything. What conferences and magazines say about not selling, that your clear approach is what sells, is absolutely true.  

Also, make sure that you have a unique ‘voice’. No one needs the same things others are saying, at least in the same way. Have a perspective, your own take. Your brand is not only what you say, but how you say it.

A related comment: track some related fields. Most of the folks I think of as experts have some other area they draw inspiration from. UX/UI, anthropology, software engineering, there are many fields and finding useful insight from a related one is useful to the field and keeps you fresh.

Oh, one other thing. You have to have integrity. People have to be able to trust what you say. If you push something for which you have a private benefit, or something that‘s trendy but not real, you will lose whatever careful credibility you‘ve built up. Don‘t squander it!  

So that‘s my take on how to be an elearning expert. So, what have I missed?

Clark Quinn

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