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Search Results for: Making it Meaningful

Measuring Impact (or not)

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So I saw a twitter thread pointing to an argument about how ROI is dead. And, well, that’s largely okay with me. However, the trigger for the post was from the results of Chief Learning Officer 2020 State of Learning report.  And, when I saw them, I saw some problems. The question is whether we’re measuring impact, or not. I’d like to go through them and evaluate each.

(Back to my usual prose, as I need visual support for this. ;)

So, in the report, they indicated that the respondents indicated the demonstrated impact of training in these ways:

  • General training output data
  • Training output data aligned with corporate initiatives
  • Learner satisfaction with training
  • Employee satisfaction with training availability
  • Employee engagement
  • Business impact
  • Employee performance data
  • Planned to actual budget, expense, revenue data for training group
  • Stakeholder satisfaction with training data
  • ROI measures
  • Net promoter score
  • Employee satisfaction with company data

Yikes!  Some of these are problematic at best.  Let’s look at why some of these might not be good measures of impact. And, let’s be clear; impact should be about positively affecting the organization in a meaningful way. Moving needles like fewer errors, more revenue, reduced costs, happier employees and customers, etc.

So, first, what  is  general training output data? If it’s like what I saw in (then) ASTD’s State of the Industry report, it’s metrics like employees served per L&D employee or cost/seat/hour for training. Which might a useful measure of efficiency, if you can come up with a principled basis for what a good number would be, and then see if you’re above or below that. Unfortunately, what people do is just compare themselves to the industry average. Is that a good indicator? How do you know? Do you want to be just ‘better than average’?

Then, training output data  aligned with corporate  initiatives.  Again, hard to say what this means (and I can’t seem to find the report). However, it sounds like it’s still efficiency, just doing that for things the business thinks are important.

And we go worse: learner satisfaction with training? Er, research I’ve read and heard cited (I think it’s from Salas, et al, but memory fails)  says that’s not valid. There’s a .09 correlation between what learners think of learning impact, and it’s actual impact. That’s zero with a rounding error. That’s all about making learning ‘fun’ (instead of ‘hard fun’). Yes, you do want them to think it’s  also been a good experience if you’re focusing on LXD, but that’s secondary.

Similarly, with satisfaction with training availability. What’s that matter? That’s not  impact!

Some good things buried here: employee engagement should be good; more engaged employees is a good thing. As long as it’s not at the cost of something else, like, say, impact?  And business impact is obviously good, as is employee performance data. Presumably positive business impact, and employee performance improving.

Planned to … stuff is all about efficiency again. And that’s ok, but only  after impact. Otherwise, well, we’re not  costing too much…?!?

Satisfaction again not good.

And, to the original point of the article. ROI?  Yes, what it costs you to move a needle should be less than the cost of what the needle was costing you.  However, I could be doing things that return the biggest ROI without doing the most important things. They can be different (e.g. a small program with a better ROI but less overall impact). So it’s only secondary.

Finally, employee satisfaction with company data? I have no idea what that means? But, again, ‘satisfaction’ isn’t really meaningful unless it’s based on real impact.

I’ve complained before about L&D measurement. Here it is, right in front of us. The answer to the question of whether we’re measuring impact or not appears to be ‘mostly not’.  We’re still (largely) measuring the wrong things. And we wonder why we don’t have credibility. Please, please, start designing to improve measurable gaps, and then actually improve the outcome. Otherwise, you’ve no idea whether that bum in that seat for an hour is doing the organization any good, versus just not costing too much relative to the industry average.

What is wrong with (higher) education?

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I was having a conversation with a colleague, sparked by dropping enrollments in unis. Not surprisingly, we ended up talking about flaws in higher education. He suggested that they don’t get it, and I agreed. He was thinking that they get the tech, but not the learning. I think it’s more complex. There are those that get some parts of the learning right. Just not enough, and not all of it right. Thinking further, post-convo, it occurs to me that there is a layer beneath the surface that matters. So I want to consider what is wrong with higher education.

And, let’s be clear, I’m  not talking about the problems with tuition and administration. Yes, tuition’s risen faster than the cost of living. And yes, there’s little commercial pressure to keep universities free from the persistent creep of increasing administration. I saw an interesting article talking about how universities without a solid financial foundation,  and ones without a good value proposition, will perish. It’s the latter I’m talking about.

I previously mentioned the three pillars I think create a valid learning offer:

  • a  killer learning experience,
  • being a partner in your success
  • and developing you as an individual.

I suggest that all three are doable, but it occurred to me that there’s a bit more to unpack.

The ‘being a partner in your success’ bit is most frequently seen. Here, it’s about looking for signs of trouble and being proactive about reaching out and assisting. It’s not ‘sink or swim’, but recognizing there can be troubles and helping learners cope. The Predictive Analytics work that Ellen Wagner did is the type of opportunity we have here.

The ‘developing you as an individual’ is really building your more general skills: communicating, working with others, a positive attitude, knowing how to search, etc. And, of course, knowing how to continue to learn. Given the rate of change, most of what you learn as the core of a degree may well be out of date in short order!  But you can’t address these skills on their own, they’re specifically about how you do domain things.  And that’s a layer I’ve yet to see.

And the ‘killer learning experience’ is a second area where I think folks still aren’t doing well. My short (and admittedly cheeky) statement about education is that they’re wrong on two things, the curriculum and pedagogy, other than that they’re fine. Most universities aren’t doing a good job of curriculum, focusing on knowledge instead of skills. And some are moving in a good direction. Startups are addressing this area as well.

The other problem is the pedagogy. There’re two elements here: the learning design, and engagement. Too often, it’s still the ‘information dump and knowledge test’. But even when that’s right, making it truly meaningful for the learners is sadly neglected. Even professors who care often forget to put the ‘why’ into the syllabus.

In short, what is wrong with higher education is the ability to successfully execute on  all these points. (It’s true for other education, too, but…) I’ve seen efforts that address one, or two (and plenty that get none right). However, as of yet, I have not seen anyone doing it the way it could be done.  It’s doable, but not without some serious attention to not only the elements, but their successful integration. And it’s important enough that we should be doing it. At least, that’s what I think. So, what do  you think?

Addressing fear in learning

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One of my mantras in ‘make it meaningful‘ is that there’re three things to do. And one of those  was kind of a toss away, until a comment in a conversation with a colleague brought it home. So here’s a first take at addressing fear in learning.

The mantra, to be clear, is that you have 3 major hurdles to overcome in getting someone to ‘buy in’ to learning:

  • I  do need this
  • I don’t know it already
  • and I trust this experience will address that

I’ve focused mostly on the first, to date. The second is for the case where someone’s overconfident in their own abilities. However, the latter one was a toss-away, until…

My colleague mentioned how in trying to train data analysis, you could be coming up against decades of a belief such as ‘I don’t do well at math’. And I saw how you could have anxiety or a lack of confidence that this learning could address it.

Which makes it clear that you need to know the audience, and anticipate barriers. How can you address such a situation? I think you have to make sure that you make it steady and slow enough, or that it’s misperceived. So here, I could see either suggesting “we’ll take it slow enough and make it simple enough that you’ll find it easy” or “you may think data analytics is about math, but that’s the least part of it, it’s really about asking and answering questions”.

The point being, you need that trust, and that means addressing any barriers. It’s addressable, but you need to be aware. I also wonder if the typical elearning experience might have undermined trust such that there would have to be a series of successes to reestablish the trust that a learning unit  should have. However, if we start regularly addressing all three, we have a start. That includes establishing the need, removing false conceptions, and addressing fear in learning. Those are my thoughts, what are yours?

The case for gated submissions

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Twice out of three recent opportunities, I’ve been thwarted from my intentions by platform capabilities. And, once, I was supported. But this capability is so basic and so valuable, I thought I’d make the argument. So here I’m making the case for gated submissions.

First, what  are gated submissions? It’s pretty simple: learners post their response to a question, and can’t see others’ responses until they submit their own. A valuable extension is for them to then be able to comment on others’ submissions. Technically, it’s simple. Pedagogically, it’s powerful.

Why is this so valuable? Well, it starts from social cognitive processing. When you have to create a response, you have to apply knowledge. And that’s a necessary part of learning. The assignment matters, of course, so it’s about applying the knowledge in a way you’ll need to do afterwards, or reflecting. It’s useful additional processing.

Not seeing others’ responses before you create your own is important, just like in brainstorming. That means you’re processing on your own, before you see how others have processed. Thus, the importance of gating, not just any old discussion.

Then, when you’ve committed and come up with a solution, seeing others’ is now much more valuable. You can compare their output with yours, and infer their underlying thinking. And for anything with a reasonable amount of complexity, this is insightful. Even better, of course, if you have them also share their thinking.

Further, if then they can comment on others, substantively (not just “great work”), you’re getting even more processing. I recommend you require commenting on someone’s who hasn’t been commented on helps ensure everyone gets useful feedback. The instructor observes the overall tilt, and comments on that, addressing any misconceptions, etc.

It can just be text, or ideally they can also have attachments. Thus, the outputs can be videos, spreadsheets, documents, whatever captures the thinking, and appropriately if particular types of assignments. Students respond in either their preferred way, or as the dictates of the assignment suggest.

Overall, you’re supporting rich responses and having a way to see others’ thinking. Short of doing group assignments, this is a great way to support meaningful thinking. So that’s the case for gated submissions. Now, will you please go and implement them in your platforms? Please?

 

 

The plusses and minuses of learning science research

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A person who I find quite insightful (and occasionally inciteful ;) is Donald Clark. He built and sold Epic, an elearning company, and now he leads a learning AI company, Wildfire. He’s knowledgeable (for instance, having read up and summarized centuries of learning theorists), willing to call out bad learning, and he’s funny. And so, when he reported on a new study, I of course looked into it. And I find that it points out the plusses  and  minuses of learning science research.

To be clear, this is about his product, so there’s a vested interest. However, he’s got integrity; he’s not going to sully his reputation with a bad study. And, it’s a good study. It rightly demonstrates an important point. It’s just that it stops short of what we need for full  learning.

So, his product does something pretty amazing. You give it content, and it can not only answer questions about the content (as, for instance, some chat tools do), it can turn the tables and ask  you questions about the content. That is, it can serve as a sort of tutor. Which is all to the good.

What it can’t do, of course, is design meaningful practice. As Van Merriënboer’s Four Component Instructional Design (4C/ID) points out, you need to know the information, and you also need practice applying it. And I reckon we’re still far from that. So, while this is part of a whole solution (and Donald knows this), it’s not the full solution. He’s subsequently let me know it can do language tasks, which is impressive. I’m thinking more of contextualized scenarios, however.

The study demonstrates, as you might expect, that breaking up a video into reasonable chunks, and having system-generated questions asked in-between, led to 61% better retrieval, going from getting 8 to 14 questions right. That is a big improvement. it’s also impressive, since it’s generating those questions from video! That is, it parses the video, establishes a transcript, and then uses that to generate a knowledge base. Very cool.

And it’s a well-designed study. It’s got a control group, and a  reasonable number of subjects. It uses the same test material, for an AB comparison. Presumably, the video chunking was done by hand, into four pieces. The chunking and break might account for the difference, which wasn’t controlled for, but it’s still a big improvement. Granted, we know that watching a video alone isn’t necessarily going to improve retention (except, perhaps, over some other non-interactive way of dumping content). But still, this is good as it’s an improvement and a lot of work was saved.

What I quibble about, however, is the nature of the retrieval. The types of questions liable to be asked (and it’s not indicated), are knowledge questions. As suggested above, knowledge is a necessary component. But using that knowledge to make decisions in context is typically what our goals are. And to achieve such goals, you basically have to practice making decisions in context. (Interestingly, the topic here was equality and diversity, a topic he has complained about!)

Knowledge about a topic isn’t likely to impact your ability to apply it. What will  make a difference are actually doing things about it, like calling it out, having consequences, and actively working to remedy imbalances. And that requires separate practice. Which he’s acknowledged in the past, and rightly points out that his solution means you can devote more resources to that end.

Thus, the plusses of learning science research are we nibble away at the questions we need to answer, and find answers about the questions we ask. The minus, of course, is not necessarily asking the most important questions. It’d be easy to see this and say: “we’ve improved retention, and we’re done”. However, it won’t necessarily lead to reducing the behaviors being learned about, or building ability to deal with it.  There are plusses and minuses of learning science research, and we need to know the strengths, and limitations, of it when we hear it.

Tips to Avoid Millennials Marketing Hype

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I received, in my email, a solicitation for a webinar titled 5 Tips to Engage Gen Z and Millennial eLearners in 2020 and Beyond.  And, as you might imagine, it tweaked my sensibilities for the worse. My initial reaction is to provide, as a palliative, tips to avoid millennials marketing hype.

The content starts off with this scintillating line: “if you‘re searching for current, new ways to engage people online and keep your business thriving, look to your youngest learners.” What? Why do you want current and new ways to engage people? How about the evidence-based ways instead? Tested and validated ones. And why your youngest learners? Organizations need to be continually learning across all employees. Why not just your  newest employees (regardless of age)?

So, your first tip is to look for phrases like ‘new’ as warnings, and look for “research-based” or “evidence-based” instead. “Science-based” is likely okay, as long as it’s not neuroscience-based (wrong level) or brain-based (which is like saying ‘leg-based walking’ as someone aptly put it.)

Second tip: don’t be ageist. Why focus on their age at all? Deal with people by their knowledge and background. It’s discriminatory, really.

The ad goes on: “To future-proof your learning program, make sure your content is designed with these young professional learners in mind.”   What’s different for these learners? Their cognitive architecture isn’t fundamentally different; evolution doesn’t work that fast. So why would you do something just for them (and discriminate against others) instead of doing what’s right for the topic?

Next tip: avoid any easy and inappropriate categorizations. Don’t try to divide content or experiences in trendy ways instead of meaningful ways.

You should already be leery. But wait, there’s more! “On one hand, they can be distracted, overwhelmed, and impatient. On the other, they are highly collaborative, technically-savvy, and driven by fairness and storytelling.”This is like a horoscope; it fits most everyone, not just young people. We all have distractions and increasingly feel overwhelmed. And our brains are wired for storytelling.   These describe human nature! And that ‘tech savvy’ bit is a clear pointer to the digital native myth. Doh!

They then go on. “With this in mind, how can you effectively engage this digitally dependent group to attract, train, and retain them?” Um, with what attracts, trains, and retains humans in general?  That would be helpful!

Thus, another tip: let’s not make facile attributions that falsely try to portray a meaningful difference. Let’s focus on design that addresses capturing and maintaining attention and motivation, and communicating in clear and compelling ways. And skip mashing up myths, ok?

We’re not  quite done with the pitch: “how to level up your existing learning strategy to meaningfully engage your Millennial and Gen Z learners.” This is just a rehash of the tips above. Meaningfully engage  all your learners!

There’s also this bullet list of attractions:

  • What motivates Millennials and Gen Z and how to tailor your learning strategy to keep them engaged
  • Ways in which traditional learning programs fail younger learners and how you can prevent these common mistakes
  • A step-by-step process for evaluating your instructional content, providing you with an actionable blueprint on transforming your content

This could easily be rewritten as:

  • What motivates Millennials and Gen Z learners and how to tailor your learning strategy to keep them engaged
  • Ways in which traditional learning programs fail younger learners and how you can prevent these common mistakes
  • A step-by-step process for evaluating your instructional content, providing you with an actionable blueprint on transforming your content

And, for all I know, that’s what they’re really doing. That would be actually useful, if they avoid perpetuating the myths about generational differences. But, as you can tell, they’re certainly trying to hit buzzword bingo in drawing you in with trendy and empty concepts. Whether they actually deliver is another issue.

Please, avoid the marketing maelstrom. Follow these tips to avoid millennials marketing hype, and focus on real outcomes. Thanks!

Curious about Curiosity

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Looking into motivation, particularly for learning, certain elements appear again and again.   So I’ve heard ‘relevance’, ‘meaningfulness‘, consequences, and more. Friston suggests that we learn to minimize surprise. One I’ve heard, and wrestled with, is curiosity. It’s certainly aligned with surprise. So I’ve been curious about curiosity.

Tom Malone, in his Ph.D. thesis, talked about intrinsically motivating instruction, and had curiosity along with fantasy and challenge. Here he was talking about helping learners see that their understanding is incomplete. This is in line with the Free Energy Principle suggesting that we learn to do better at matching our expectations to real outcomes.

Yet, to me, curiosity doesn’t seem enough. Ok, for education, particularly young kids, I see it. You may want to set up some mismatch of expectations to drive them to want to learn something. But I believe we need more.

Matt Richter, in his well-done L&D conference presentation on motivation, discussed self-determination theory. He had a nice diagram (my revision here) that distinguished various forms of motivation. From amotivated, that is, not, there were levels of external motivation and then internal motivation. The ultimate is what he termed intrinsic motivation, but that’s someone wanting it of their own interest. Short of that, of course, you have incentive-driven behavior (gamification), and then what you’re guilted into (technically termed Introjection), to where you see value in it for yourself (e.g. WIIFM).

While intrinsic motivation, passion, sounds good, I think having someone be passionate about something is a goal too far. Instead, I see our goal as helping people realize that they need it, even if not ‘want’ it. That, to me, is where consequences kick in. If we can show them the consequence of having, or not, the skills, and do this for the right audience and skills, we can at least ensure that they’re in the ‘value’ dimension.

So, my take is that while we should value curiosity, we may not be able to ensure it. And we can ensure that, with good analysis and design, we can at least get them to see the value. That’s my current take after being curious about curiosity. I’d like to hear yours!

Mythless Learning Design

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If I’m going to rail against myths in learning, it makes sense to be clear about what learning design without  myths looks like. Let me lay out a little of what mythless learning design is, or should be.

Myths book coverLearning with myths manifests in many ways. Redundant development to accommodate learning styles, or generations. Shortened to be appropriate for millennials or the attention span of a goldfish. Using video and images for everything because we process images 60K faster. Quiz show templates for knowledge test questions because they’re more engaging. And all of these would be wrong.

Instead, mythless design starts with focusing on  performance. That is, there’re clear learning outcomes that will change what people do that will affect the success of the organization. It’s not about knowledge itself, but only in service of achieving better ability to make decisions.

Then, it’s about designing meaningful practice in making those decisions. It’s not about testing knowledge, but ability to apply that knowledge to choose between alternative courses of action. It can be mini-scenarios (better multiple choice), branching, or sims, but it’s about ‘do’, not  know.

We reinforce practice with content that guides performance and provides feedback. It does use multiple media, because we use the right media for the message. Yes, we look to engage multiple senses, but for comprehending and encoding information. And variety. We use visuals to tap into our powerful visual processing system, not because they have any particular metric improvement. We also use audio when appropriate. And while text is visual, we use it as appropriate too. To address learning outcomes, not learner preferences.

Mythless learning design may use small amounts of content, but because minimalism keeps cognitive load in check, not because our attention span has changed. We need appropriate chunking, as our working memory is limited, so we want to make things as small as possible, but no smaller!

We design meaningful active practice not because any generation needs it, but because it’s better aligned with how our brains learn at pretty much any age. There are developmental differences in working memory capacity and experience base, but  everyone benefits from doing things, not passively consuming content.

There are good bases for design. Ones that lead to real outcomes. Starting from a performance focus, and reflecting what’s been demonstrated in learning science research, and tested and refined. Evidence guiding design, not myths.

There are also bad bases for design. Dale’s Cone, shiny object syndrome, the list goes on. Gilded bad design is still bad design. Get the core right. Let’s practice good, mythless learning design. Please.

 

Wanna talk meaning, learning science, and more…?

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The L&D conference, starting today, has a wide variety of things going on. I’m actually impressed, because in addition to the asynchronous and synchronous sessions I knew about, there are a number of other things going on. Including things I’m in. So, do you wanna talk meaning, learning science, and more…? Here’s when and how.

In addition to the presenters who have prepared asynchronous learning experiences, and the live presentations by the same and others, there are other things going on. There are panels on, for instance, on diversity & inclusion, state of learning, learning technology, women in learning, as just a few. There are also debates on games, evaluation, to e- or not to e-, at least. Lots of interesting topics. But wait, there’s more!

There are also networking sessions, a quiz show, roundtable breakouts, breakfast/cocktail (depending on timezone) networking, … There are also some interviews with prominent folks, both specifically for the conference and some legacy ones courtesy of Guy Wallace (HPT guru). And there’s either or both of more I don’t know about, and more to come.

A special mention for the CrowdThinking project, in collaboration with IBSTPI. My colleague, Fernando Senior, will be leading an event to understand the current and anticipated requirements for L&D roles. And there’s a survey you’re requested to fill out regardless of whether you’re attending the conference. Please help!

As for me, first, my asynchronous session is on Learning Science 101. I’ve created some short videos that talk about, and illustrate, a number of things our cognitive architecture has to account for. And, hint hint, it presages something hopefully to be announced soon.

My synchronous sessions (two different times; they’re making a serious effort to reach out globally) are 3PM ET (noon PT) Wed July 1, and 11AM ET (8AM PT) on July 8. Here, I’ll be talking about what I think is a huge missed opportunity and addressable (tho’ not simple) element of our learning design. I’ll also be part of the panel on learning science (The State of Learning) 8AM PT July 9 and 11 AM PT July 17. And, a reprise of the great debate on evaluating learning or impact (4PM PT 25 June).

And, importantly, I’ll be holding some office hours where we can truly talk about learning science, meaningfulness, and more! So will the other presenters. (They’re still to be set; I’ll update here when I know!)

Of course, there is a host of other really great speakers. Have a look at this lineup! Also, guests for a variety of things will include people like Charles Jennings & Jos Arets, Paul Kirschner, and many many more. Most of the live sessions have two times, so there’s a good chance you can catch them sometime. And there’s no overlap (so far ;), but things going on every day.

If, by the way, you are thinking about attending the  conference, but have some struggles with cost, get in  touch  with me. I may have a way to help out ;).   I hope to see you there, whether you want to be talking meaningful learning, or for any of the other myriad reasons.

As you can probably infer, I’m interested in this. It’s not surprising, but most online events have mimicked face-to-face events. Webinars, basically. Here there’s more going on. I don’t expect all of it to work (though it all sounds good), but I love that they’re experimenting to find ways to go beyond. We’ll all learn from this initiative. Hope to see you there if you wanna talk meaning, learning science, and more…

 

Taking courses online

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So I was talking to my brother the other day. He is a community college instructor (and, now, department chair). He was telling me about taking his class online (like so many others). I of course offered some suggestions, and he opined that I could (and should) be helping others too. Which, of course, I agree with, because that’s what I do. So, here, is a brief summary of my experience taking courses online. Because, owing to circumstances, I do have some availability.

My background is deeply steeped in applying learning science to technology-mediated experiences. To start, I saw the opportunities and designed my own major in the topic. After some work, I obtained a Ph.D. because I wanted to know more about cognition and learning. And I’ve been doing it for decades now, both academic and organizational. I not only taught, but was asked to lead my university’s learning technology committee.

I stepped away from the university to assist first one, then another initiative in online learning. For one, I set the learning design (policies and plans) to spin up an agency to support national online learning. For the latter, I led the learning design effort to get an innovative course online. At the same time, I was assisting and leading other initiatives. These include an online learning competition, advising other orgs, and creating an online learning quality assessment.

I came back to the US to lead the development of an adaptive learning platform for online courses. Since then, I’ve been assisting many orgs in a wide variety of roles around online learning. I’ve guided the design of online content for high school curricula, advised on improving design processes for a courseware provider, and guided an online program manager to incorporate learning science in their practices.

Along the way, I’ve continued to lead in technology approaches, including games and mobile (and wrote the books on each topic ;).   And I’ve maintained a reputation for staying on top of learning science as well, recently writing a book on myths around learning science. My work’s been recognized, with invitations to speak nationally and internationally, as well as being the first recipient of the eLearning Guild’s Guild Master award. I’m noted as a clear communicator who helps folks ‘get’ the opportunities, and apply the principles to achieve desirable goals.

As you see, I’ve worked at every level, from helping design individual courses, to working with design processes and teams, to looking at organizational approaches and issues. And I’ve demonstrated a commitment to design solutions that leverage the best learning design to achieve engaging experiences with meaningful outcomes under pragmatic constraints. And I’m adept at working virtually, which I’ve been doing for a long time in many ways.

So, I’d like to help  you!   Whether it’s working serially on courses, assisting a team get on top of best principles, or conducting sessions to assist your instructors, I’m willing to be flexible to figure out the best ways to help you make the best changes quickly, not just the expedient ones. In the long term, you still want effective learning design and engagement, because it matters to your learners and your reputation.

The opportunity to get better quickly is on tap. I’ve spent my entire career caring about making good learning happen. Are you ready? Let me know.

This has been a public service announcement, we now return you to your irregularly scheduled blog.