Archives for December 2017

The Quinnov 8: An online course

28 December 2017 by Clark Leave a Comment

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:

Performance consulting: what to do before you decide to course
Objectives: making the right decisions about what to focus on
SMEs: working with them for objectives and more
Practice: making practice meaningful
Models: the conceptual frameworks that guide performance
Examples: the link between concepts and application.
Engagement: wrapping the front and back to create experiences
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.

Pernicious problems

27 December 2017 by Clark 4 Comments

I’m using a standard for organizational learning quality in the process of another task. Why or for whom doesn’t matter. What does matter is that there are two problems in their standard that indicate we still haven’t overcome some pernicious problems. And we need to!

So, for the first one, this is in their standard for developing learning solutions:

Uses blended models that appeal to a variety of learning styles.

Do you see the problem here? Learning styles are debunked! There’s no meaningful and valid instrument to measure them, and no evidence that adapting to them is of use. Appealing to them is a waste of time and effort. Design for the learning instead! Yet here we’re seeing someone conveying legitimacy by communicating this message.

The second one is also problematic, in their standard for evaluation:

Reports typical L&D metrics such as Kirkpatrick levels, experimental models, pre- and post-tests and utility analyses.

This one’s a little harder to see. If you think about it, however, you should see that pre- and post-test measures aren’t good measures. What you’re measuring here is a delta, and the problem is, you would expect a delta. It doesn’t really tell you anything. You shouldn’t have even bothered if the performance isn’t up to scratch! What you want to do is confirm that you’re achieving a higher level of performance set objectively. Are they now able to perform? Or how many are? Doing the pre-post is like doing normative reference (e.g. grading on a curve) when you should be doing criteria-referenced performance.

And this is from an organization that’s purports to communicate L&D quality! These are both from their base level of operation, which means it’s acceptable. This is evidence that our problems aren’t just in practice, they’re pernicious; they’re present in the mindset of even the supposed experts. Is it any wonder the industry is having trouble? And I haven’t rigorously reviewed the standard, I was merely using it (I wonder what I’d find if I did?).

Maybe I’m being too harsh. Maybe the wording doesn’t imply what I think it does. But I’ll suggest that we need a bit more rigor, a bit more attention to science in what we do. What have I missed?

Expertise

21 December 2017 by Clark Leave a Comment

Expertise is an elusive thing. It comes from years of experience in a field. However, it turns out that it doesn’t just accumulate. You need very specific practice and/or useful feedback to develop it. And the more expertise one has, the better you are able to apply it to situations. Which has implications for what you do and when and how you do it.

Expertise is valuable. The properties of expertise include that it’s compiled away to be essentially automatic. Which implies it’s not accessible for conscious introspection. (Which is why experts quite literally cannot tell you what they do!) On the other hand, their responses to situations in their area of expertise are likely to be as good as you can get. They apply mental models they’ve developed to solve problems.

If you want to develop expertise as an individual, you need to understand how to practice. Deliberate practice, as Ericsson details, is the key. You need to practice at the limits of your ability, and consciously learn from the outcomes. It’s not just doing the job, it’s pushing the boundaries, and actively reflecting.

If you want to develop expertise as an organization internally, the situation is very much the same. You need resources to develop people, and stretch assignments with feedback and coaching to optimally develop the expertise.

Of course, you can bring in expertise from outside, as well. The question then becomes one of when and who. You can contract out work, which makes sense when the activity isn’t part of your core ability. Outsourcing to technology or external expertise is fine for things that are in areas that are well developed.

Otherwise, you can bring in consultants. The latter is particularly useful when you are moving in a new direction or want to deepen your understandings. A good consultant will work with you to not only help address the situation, but internally develop your own understanding. The key is working collaboratively and transparently. Yes, I’m a vested interest, but I believe these things are true on principle and should be in practice.

Expertise is core to situations you know you need expertise in, but also in those that are new. When you need innovation, you need expertise in the complementary areas that you are applying to address the situation. You don’t want to develop learning except in the problem. At least, that’s my expert opinion. Which, of course, is on tap if needed ;).

Innovations

19 December 2017 by Clark Leave a Comment

Sparked by a colleague, I’m reading The Digital Transformation Playbook, by David Rogers. In the chapter on innovation, he talks about two types of experimentation: convergent and divergent. And I was reminded that I think of two types of innovations as well. So what are they?

Experimentation

He talks about how experimentation is the key to innovation (in fact, the chapter title is Innovate by Rapid Experimentation). His point is that you need to be continually experimenting, rapidly. And throughout the organization, not just in separate labs. Also, it’s ok to fail, as long as the lesson’s learned. And then he distinguishes between two types of experimentation.

The first is convergent. Not surprisingly, this is when you’re trying to eliminate options and make a decision. This is your classic A/B testing, for example. Here you might try out two or three different solutions, to see which one works best. You create the options, and have measures you’ll use to determine the answer. You might ask: should we use a realistic video or a cartoon animation? A situation where there isn’t a principled answer, and you need to make a decision.

Divergent experimentation is, instead, exploratory. Here you give folks some ideas, or a prototype, and see what happens. You don’t know what you’ll get, but you’re eager to learn. What would a scenario look like here?

Innovation

These roughly correspond to the two types of innovation I think of. One is the ‘we need to solve this’ type. I think of this as short-term innovation. Here we are problem-solving or trouble-shooting. You bring together a team of relevant capabilities and otherwise as diverse as possible. You facilitate the process. And you’re likely to try convergent experimentation.

At the other end is the serendipitous, long-term innovation that happens because you create an environment where ideas can gestate. You’ve got access to the adjacent possible, and the opportunities to explore and share. It’s safe to experiment and fail. People are supposed to take time to reflect! This is more closely aligned to divergent experimentation.

Note that this is all learning, as you don’t know the answers when you start! The success of organizational learning, however, is a product of both. You need to solve the problems you know you have, and allow for ideas to generate solutions to problems you didn’t know you had. Or, more optimistically, to search through idea spaces for opportunities you didn’t know to look for.

Rogers is right that continual experimentation is key. It has to become baked into how you do what you do. Individually, and organizationally. And you can’t really get it unless you start practicing it yourself. You need to continually challenge yourself, and try things both to fix the problems, and to explore things that are somewhat tangential. Your own innovations will be key to your ability to foster them elsewhere.

Too many orgs are only focused on the short-term. And while that may solve shareholder return expectations, it’s not a receipt for longer-term organizational survival. You need both types of innovations. So, the question is whether you can assist your org in making a shift to the serendipitous environment. Are you optimizing your innovation?

Video Lessons

15 December 2017 by Clark Leave a Comment

So, I’ve been creating a ‘deeper elearning’ course for one of the video course providers. And I’m not mentioning where it is (yet), since it’s still under development. But to do this, I had to do some serious learning about creating video. And there were some realizations in this, of course.

One of the decisions to be made was how to include graphics.. My mentor/colleague/friend showed me (by video chat) his elegant setup. He has green screens, and lights, and has a full studio in a separate room as well. Of course, he’s been doing video for decades. I’ve hardly done much besides taking a multimedia course at least 20 years ago. And narrating the occasional Keynote deck.

In the meantime I asked around, and colleagues were pretty unanimous on ScreenFlow being the tool to use. So I got a copy. And, indeed, I was able to film myself. Moreover, I quickly found out I could include diagrams and text right on the screen! That eliminated the need for a green screen.

I had a couple of lights, and without them my screen reflected on my glasses. However, that’s not really fixable, since I didn’t get the anti-glare coating when I had them made. Doh! Next time, for sure. I positioned a couple of lights off to each side, and they reduced (though not eliminated) the glare.

We were moving my office back to the front of the house (long story), so we moved a bookcase behind me, with my library. It looks good, but…you don’t see much of it anyway. I filmed standing up (on my new stand/sit desk converter), and I block most of the background anyway (except for the Albert Einstein poster that sits on the wall).

Having read up, I knew to have a written script, which, without a prompter, I just positioned to the top of the screen under the camera. Of course I changed it a bit, and adlibbed a bit, but mostly stuck to what I’d written. It’s not quite as spontaneous (and goofy) as I am in person, but it ensures consistent quality. And I filled in diagrams a few times, and added some text a few times, to help keep pace.

Frankly, it’s not great, but I had a deadline. It’s too much of me talking, without animation. But this is done by me, alone, under a tight deadline. And that’s my error, too, since I have video anxiety almost as bad as my phone anxiety, and dragged my heels until things were too late. Dang emotions getting in the way again! (Even when you know this.)

I also created some quizzes, in mini-scenario fashion pretty much. That is, there’s a fair bit of dialog that you either are asked and/or choose to respond with. Because it’s only a multiple choice option, I was somewhat constrained. I subsequently was prodded for some assignments, and found I could do what I’d talked about. I used the assignment tool to create questions that asked learners to go out and do things and then provide them with some guidance to self-evaluate.

One thing I learned is that I don’t have a good mental model of how the software works. I ‘get’ the tracks, but there’s another aspect I don’t understand. So, it turns out though I’d filmed myself at 720p, and exported at 720p, it still had an unnecessary border. Fortunately, in stumbling around I found a ‘crop’ setting that forced it to 1280 x 720 (720p), but I don’t understand why that was necessary!?!?

I still want to add some examples (as documents) before I feel it’s fully ready to go. And I now sympathize much more with those who struggle to do good learning design under real-world constraints. It’s also certainly been an example of my accepting assignments that are within my reach, but not within my grasp; my learning style ;). More later, but thought I’d share my struggles and learning. I welcome your feedback.

Higher Ed & Job Skills?

13 December 2017 by Clark 2 Comments

I sat in on a twitter chat yesterday, #DLNChat, that is a higher ed tech focused group (run by EdSurge). The topic was the link between higher ed and job skills, and I was a wee bit cynical. While I think there are great possibilities, the current state of the art leaves a lot to be desired.

So, I currently don’t think higher ed does a good job of preparation for success in business. Higher ed focuses too much on knowledge, and uses assignments that don’t resemble the job activities. Frankly, there aren’t too many essays in most jobs!

Worse, I don’t think higher ed does a good job of developing meta-cognitive and meta-learning skills. There is little attempt to bridge assignments across courses, so your presentations in psychology 101 and sociology 202 and business 303 aren’t steadily tracked and developed. Similarly with research projects, or strategy, or… And there’re precious little (read: none) typically found where you actually make decisions like you would need to.

And, sadly, the use of technology isn’t well stipulated either. You might use a presentation tool, a writing tool, or a spreadsheet, maybe even collaboratively, but it’s not typically tied to external resources and data.

Yes, I know there are exceptions, and it may be changing somewhat, but it still appears to be the case. Research, write a paper, take a test.

Yet the role of developing higher skills is possible and valuable. We could be providing more meaningful assignments, integrating meta-learning layers, and developing both meaningful skills and meta-skills.

This doesn’t have to be done at the expense of the types of things professors believe are important, but just with a useful twist in the way the knowledge is applied. It might lead to a revision of the curriculum, at least somewhat, but I reckon it’d likely be for the better ;).

Our education system, both K12 and higher-ed, isn’t doing near what it could, and should. As Roger Schank says, only two things wrong: what we teach, and how we teach it. We can do better. Will we?

Conceptual Clarity

6 December 2017 by Clark 1 Comment

Ok, so I can be a bit of a pedant. Blame it on my academic background, but I believe conceptual clarity is important! If we play fast and loose with terminology, we can be be convinced of something without truly understanding it. Ultimately, we can waste money chasing unwarranted directions, and worse, perhaps even do wrong by our learners.

Where do the problems arise? Sometimes, it’s easy to ride a bizbuzz bandwagon. Hey, the topic is hot, and it sounds good. Other times, it’s just too hard to spend the effort. Yet getting it wrong ends up meaning you’re wasting resources.

Let’s be clear, I’m not talking myths. Those abound, but here I’m talking about ideas that are being used relatively indiscriminately, but in at least one interpretation there’s real value. The important thing is to separate the wheat from the chaff.

Some concepts that are running around recently and could use some clarity are the following:

Microlearning. I tried to be clear about this here. In short, microlearning is about small chunks where the learning aggregates over time. Aka spaced learning. But other times, people really mean performance support (just-in-time help to succeed in the moment). What you don’t want is someone pretending it’s so unique that they can trademark it.

70:20:10. This is another that some people deride, and others find value in. I’ve also talked about this. The question is why they differ, and my answer is that the folks who use it as a way to think more clearly about a whole learning experience find value. Those who fret about the label are missing the point. And I acknowledge that the label is a barrier, but that horse has bolted.

Neuro- (aka brain- ). Yes, our brains are neurologically based. And yes, there are real implications. Some. Like ‘the neurons that fire together, wire together’. And yet there’re a whole lot of discussions about neuro that are really at the next higher level: cognitive. This is just misleading folks to make it sound more scientific.

Unlearning. There’s a lot of talk about unlearning, but in the neurological sense it doesn’t make sense. You don’t unlearn something. As far as we can tell, it’s still there, just increasingly hard to activate. The only real way to ‘unlearn’ is to learn some other response to the same situation. You learn ‘over’ the old learning. Or overlearn. But not unlearn. It’s an unconcept.

Gamification. This is actually the one that triggered this post. In theory, gamification is the application of game mechanics to learning. Interestingly, Raph Koster wrote that what makes games fun are that they are intrinsically about learning! However, there are important nuances. It’s not just about adding PBL (points, badges, and leaderboards). These aren’t bad things, but they’re secondary. Designing the intrinsic action around the decisions learners need to acquire is a deeper and more meaningful implication. Yet people tend to ignore the latter because it’s ‘harder’. Yet it’s really just about good learning design.

There are more, of course, but hopefully these illustrate the problem. (What are yours?) Please, please, be professional and take the time to get clear about our cognitive architecture enough to ensure that you can make these distinctions on your own. We need the conceptual clarity! Hopefully then we can reserve excitement for ideas that truly add value.

Usability and Networks

5 December 2017 by Clark Leave a Comment

As I mentioned in an earlier post, I have been using Safari and Google to traverse the networks. And in a comment, I mentioned that the recent launch of the new Firefox browser was prompting me to switch. And that’s now been put through a test, and I thought it instructive to share my learnings.

The rationale for the switch is that I don’t completely trust Google and Apple with my data. Or anyone, really, for that matter. On principle. I had used Safari over Chrome because I trust Apple a wee bit more, and Firefox was a bit slow. And Safari just released a version that stops videos from auto-starting. And similarly, Google’s search has been the best, and with a browser extension and some adjustments, I was getting ads blocked, tracking stopped, and more. Still, I wasn’t happy. And I hadn’t figured out how to do an image search with DuckDuckGo (something I do a fair bit) the last time I tried, so that hadn’t been a search option.

All this changed with the release of Firefox’s new Quantum browser. After a trial spin, the speed was good, as was the whole experience. Now, I want to have an integrated experience across my devices, so I downloaded the Firefox versions for my iDevices as well. And, as long as I was changing, I tried DuckDuckGo again, and found it did have browser search. So I made it my search engine as well.

And, after about a week of experience, I’m not sticking with Firefox. The desktop version is all I want, but the iDevice versions don’t cut it. I use my toolbar bookmarks a lot. Many times a day. And on the iDevices, they do synch, but…they’re buried behind four extra clicks. And that’s just not acceptable. The user experience kills it for me. Those versions also don’t take advantage of the revised code behind the new desktop version, but it wasn’t the speed that killed the deal. The point I want to make is that you have to look at the total experience, not just one or another in isolation. It’s time for an ecosystem perspective.

On the other hand, I’m still trying DuckDuckGo. It seems to have a good output on it’s hits. And the fact that they’re not tracking me is important. If I can avoid it, I will. Sure, my ISP still can track me, and so can Apple, but I’ll keep working on those. Oddly, it seems to return differently on different devices (?!?!). Still testing.

And, as long as we’re talking the net, I’m going to do something I don’t usually do here; I’m going to take a position on something besides learning. To do so, let me provide some context. I’ve been on the net since before there was a web. Way before. Circa 1978, I was able to send and receive email even though there wasn’t any internet. I was at a uni with ARPANET, however, so I had a taste. Roll forward a decade and more, and I was playing with Gopher and WAIS and USENET before Tim Berners-Lee had created http. That is, there were other protocols that preceded it. (In fact, I was blasé about the web at first, because of that; doh!) My point is that I’ve been leveraging the benefits of networks for a bloody long time.

And now we depend on it. The internet is the basis for elearning! And, of course, so much more. It has vastly accelerated our ability to interact. And while that’s created problems, it’s also enabled incredible benefits. Innovation flourishes when there are open standards. When people can build upon a solid and open foundation, creativity means new opportunity. Network effects are true for people and for data.

Which is why I’m firmly in the camp for net neutrality. This is important! (It must be, because I used bold, which I almost never do ;). The alternative, where providers will be able to throttle or even bar certain types of data will stifle innovation. It’s like plumbing, telephone, and electricity: they need to be available as long as you can pay your bill (and there need to be options to support those with limited incomes). Please, please, please let your elected representatives and the FCC know that this is important to you.