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2015 Reflections

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It’s the end of the year, and given that I’m an advocate for the benefits of reflection, I suppose I better practice what I preach. So what am I thinking I learned as a consequence of this past year?  Several things come to mind (and I reserve the right for more things to percolate out, but those will be my 2016 posts, right? :):

  1. The Revolution  is real: the evidence mounts that there is a need for change in L&D, and when those steps are taken, good things happen. The latest  Towards Maturity report shows that the steps taken by their top-performing organizations are very much about aligning with business,  focusing on performance, and more.  Similarly, Chief Learning Officer‘s Learning Elite Survey similarly point out to making links across the organization and measuring outcomes.  The data supports the principled observation.
  2. The barriers are real: there is continuing resistance to the most obvious changes. 70:20:10, for instance, continues to get challenged on nonsensical issues like the exactness of the numbers!?!?  The fact that a Learning Management System is not a strategy still doesn’t seem to have penetrated.  And so we’re similarly seeing that other business units are taking on the needs for performance support, social media, and ongoing learning. Which is bad news for L&D, I reckon.
  3. Learning design is  rocket science: (or should be). The perpetration of so much bad elearning continues to be demonstrated at exhibition halls around the globe.  It’s demonstrably true that tarted up information presentation and knowledge test isn’t going to lead to meaningful behavior change, but we still are thrusting people into positions without background and giving them tools that are oriented at content presentation.  Somehow we need to do better. Still pushing the Serious eLearning Manifesto.
  4. Mobile is well on it’s way: we’re seeing mobile becoming mainstream, and this is a good thing. While we still hear the drum beating to put courses on a phone, we’re also seeing that call being ignored. We’re instead seeing real needs being met, and new opportunities being explored.  There’s still a ways to go, but here’s to a continuing awareness of good mobile design.
  5. Gamification is still being confounded: people aren’t really making clear conceptual differences around games. We’re still seeing linear scenarios confounded with branching, we’re seeing gamification confounded with serious games, and more.  Some of these are because the concepts are complex, and some because of vested interests.
  6. Games  seem to be reemerging: while the interest in games became mainstream circa 2010 or so, there hasn’t been a real sea change in their use.  However, it’s quietly feeling like folks are beginning to get their minds around Immersive Learning Simulations, aka Serious Games.   There’s still ways to go in really understanding the critical design elements, but the tools are getting better and making them more accessible in at least some formats.
  7. Design is becoming a ‘thing’: all the hype around Design Thinking is leading to a greater concern about design, and this is a good thing. Unfortunately there will probably be some hype and clarity to be discerned, but at least the overall awareness raising is a good step.
  8. Learning to learn seems to have emerged: years ago the late great Jay Cross and I and some colleagues put together the Meta-Learning Lab, and it was way too early (like so much I touch :p). However, his passing has raised the term again, and there’s much more resonance. I don’t think it’s necessarily a  thing yet, but it’s far greater resonance than we had at the time.
  9. Systems are coming: I’ve been arguing for the underpinnings, e.g. content systems.  And I’m (finally) beginning to see more interest in that, and other components are advancing as well: data  (e.g. the great work Ellen Wagner and team have  been doing on Predictive Analytics), algorithms (all the new adaptive learning systems), etc. I’m keen to think what tags are necessary to support the ability to leverage open educational resources as part of such systems.
  10. Greater inputs into learning: we’ve seen learning folks get interested in behavior change, habits, and more.  I’m thinking we’re going to go further. Areas I’m interested in include myth and ritual, powerful shapers of culture and behavior. And we’re drawing on greater inputs into the processes as well (see 7, above).  I hope this continues, as part of learning to learn is to look to related areas and models.

Obviously, these are things I care about.  I’m fortunate to be able to work in a field that I enjoy and believe has real potential to contribute.  And just fair warning, I’m working on a few areas  in several ways.  You’ll see more about learning design and the future of work sometime in the near future. And rather than generally agitate, I’m putting together two specific programs – one on (e)learning quality and one on L&D strategy – that are intended to be comprehensive approaches.  Stay tuned.

That’s my short list, I’m sure more will emerge.  In the meantime, I hope you had a great 2015, and that your 2016 is your best year yet.

Work with purpose

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As another component of the Future of Work thinking I’ve been doing, one thing that strikes me is the question of what helps people  want to work, which I think pretty clearly will be important.  And I was reminded by my ITA colleague Jane Hart of the work of Dan Pink in his book Drive, where he isolates three components of what makes people engaged: autonomy, mastery, and purpose.  And I think this is a good list.

The idea is fairly straightforward: people want work that actually does something important, they want to be free to pursue that work, and they want to be developed in their ability to accomplish that work.   What work is appropriate for different people is part of the task of deciding who to hire, and who to assign to what.

And while I think autonomy and mastery are part of the picture, for sure, I want to focus on making work  meaningful.  OK, freeing up people from micromanaging is going to be a necessity going forward, but that’s part of the necessary move to agile organizations, and while that’s challenging, it has to happen for organizations to survive. And supporting people by giving them assignments that stretch their abilities, and coaching them through it is absolutely important, but flows out of the 70:20:10 model. Jane, in her valuable book  Modern Workplace Learning, gives very specific  guidance  about managers developing individual potential as part of the larger picture.  But the area that strikes me as something I haven’t developed my thoughts  about before is finding ways to characterize work so that it connects to people.

I think work has to be meaningful (just as I argue learning has to be meaningful). Here I mean something specific, in that people see the connection between what they’re doing and the impact on the world.  And that’s not always done, and certainly not systematically or well.  And yet I think it’s a service to the employees and part of a thriving organization.  Heck, it probably even leads to better employee engagement ;).

Seriously, it first takes an organization that has a clear focus on what it’s doing. There’re the old stories about ice companies losing out when refrigerators came in, and I think that’s part of it: a very clear focus on what purpose they serve. And this is important to align an organization, and make the strategy easier to focus on.  A secondary desirable component, to me, is to understand what contribution the organization is making to the world. I think the ‘b corp‘ notion is a great one here. (I may be an idealist, but that’s the world I  want to live in. ;).

Then, there needs to be a clear alignment between what the employee is doing and the overall organizational goal. I think that if there’s a clear purpose for the work, you have a greater likelihood for employees to be engaged.  No one likes busywork, after all, but even some drudge work that’s part of a bigger picture can be shouldered. And it also means that rote work, work that can be automated,  should be automated, leaving people free to do the important work.   Very much like learning needs to see how the learning connects to their work and the bigger picture, so too should their work connect to the bigger picture, within and outside the org.

Not to say this is easy. It requires clear communication (queue the Coherent Org), and a clear vision, but these are steps organizations need to do.  The recognition that this alignment, coupled with a ‘safe’ culture (i.e. not the Miranda Organization), is the necessity for going beyond survival to ‘thrival’ I think is the catalyst for change in meaningful work. And that’s a good place to go.

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Starting a revolution?

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In thinking a bit about the Future of Work, one of the issues is where to start.  If we take the implications of the Coherent Organization to heart, we realize that the components include the work teams, the communities of practice (increasingly I think of it as a community of improvement), and the broader network.  But where to begin?

A couple of principles fall into place for me.  The first is the notion of  ‘trojan mice’, e.g. small steps rather than a epic change. That, coupled with the notion of scaling up from the small, leads me to believe that the best place to start is to start small. This follows on the advice about change in general  that changes should be strategic and leveraged.

So, a natural place to start small is the team itself.  The goal would be to draw upon a diverse team meeting a real need, but facilitating their tool use. I remember an engagement with a Scandinavian oil company that I was brought in on, where they started out establishing teams for new projects that crossed geographies (and, implicitly, cultures), scaffolded them using collaboration and communication tools, and then released them back to other projects. The goal was to skill up teams and have the team members become viral influences.

Another approach, as there are already likely communities in existence, would be to migrate and facilitate communities online. I recall that the Defense Acquisition University took this approach.  However, I might like to get some project teams going with tools and then migrate out to the communities, where those team members that had participated were familiar with the tools and could be drawn upon by the community.

In fact, after the initial team work, I might facilitate a team not only working together, but working out  loud back to their respective communities.  And while it makes practical sense to be sequential, at some point it might make sense to go parallel, and be having the working out loud from the teams being worked on at the same time as the community development. But for resource reasons, I might make it sequential.  Ultimately, you want to be facilitating the communities participating in  and outside  the organizations, and looking to other communities both inside and outside for inspiration.

The point is to be finding a small way to begin, and maybe take several tries until you work out how to do it well, then start scaling up and out.  You want to build need, awareness, and ability steadily.  It can effect a change in culture too, if the principles that make this work in teams and communities begins to be made aware as well.

And this is not independent of work on going to more performance consulting and performance support in the organization, but instead is a complement.  In previous exercises, different organizations have prioritized different elements, where you begin will be dependent on your context.

So, in the social space,  this is my instinct and experience, but welcome hearing alternate viewpoints.

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Working and learning out loud

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I’ve been thinking about some of the talk around the Future of Work, and in addition to the free flow of information I recently posted about  from the Coherent Organization, I think working out loud is another component.  Inspired by a post from my colleague ITA Harold Jarche,  this is how I see it, in actionable terms.  (And I expect this is also part of Jane Bozarth’s Show Your Work, but I’ve yet to get my mitts on a copy, mea culpa.)

The point is to make your work visible.  There’re two points: showing the actual goals, progress and status of your work, and showing the thinking that’s going on behind it.  And there are two dimensions: within the organization, and outside the organization.  Pragmatically, this yields some concrete and actionable elements.

First, there have to be mechanisms to share.  Ideally, you don’t have to work and then separately post it, but instead your tools automatically share.  This really means collaborative work tools, because you want people to be able to engage: at least commenting, and of course sometimes (maybe most of the time) you’ll be working in a team. Also tools that track contributions and changes.  And there may have to be permissions: so some people can edit, some can only comment, etc.

And I wouldn’t assume folks know what it means to ‘narrate your work‘ (aka learn out loud).  Here, I mean exposing the underlying elements.  This includes the context, assumptions, considerations, experiments, and reflections.  In User Interface Design, it was called Design Rationale, and it’s showing not only the current state, but how you got there.  Benefits include others’ experiences, not revising early decisions when new team members are added, and more.  The typical techniques of being explicit, modeling, evangelizing, promoting, etc, play a role here.

Then of course it has to be ‘safe’ to share, you can’t be working in a Miranda organization.  If your work will be held against  you in any way, you won’t want to share.  This means culture and policies and more. Basically, you need to be working in a Learning Organization, where the elements are aligned to facilitate optimal engagement.  This includes the practices about how to work out loud and learn out loud.

Another   issue is how far to share.  What can you share outside the organization?  Harold talks about the essential requirement of sharing outside the workplace, and that can be a big concern.  Obviously, proprietary work needs to be protected until it’s not business vulnerable. This means policies about what’s safe to share, and when.  Certainly, ‘sanitized’ work, where critical details are obscured but the thinking is shown should be supported in going out to communities of practice.  And the end result, when the business advantage isn’t threatened, could and should be shared through articles or webinars or conference presentations.

At the end, it’s a risk/reward tradeoff for any project at any time. What’s the benefit of getting feedback to improve versus what’s the downside of information getting out to competitors or exposing regulated data?  At any point, with any particular version of ‘anonymizing’, the balance may tip one way or another.   But the point is to be open to the benefit, and take advantage of it when and where you can.  Getting systematic at making it a regular part of any project is likely to be key.

It’s what I do here, and I encourage you to work out loud as much as you can.  So, any feedback so far?

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Conferencing reflections

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It turns out that I’ve been to a  lot of conferences this year (8, if my math is right) scattered through the year and around the globe. And over the past decade, I’ve hit a lot more.  And it’s given me some opportunities to contrast and compare some of the tradeoffs that can be made.  So I thought I’d share my thoughts with you.

Now, my perspective starts out a bit different. At these events, I’m speaker, so I see things from a different perspective.  However, I also try to go see sessions as an audience member as well, and I still see the same events.  So I am trying to write this from all perspectives: conference organizer, attendee, speaker, and vendor.  And let me be clear, I’m a learning technology strategist, and my passions are learning, technology, and how to use them together to make things better. So that colors my comments.

Here are the major elements and my thoughts on them:

Keynotes: I am tired of ‘inspirational’ keynotes. I really don’t need to hear some person who climbed a mountain or sailed a sea and their attempts to connect that to learning somehow. I’d rather hear about an issue that affects learning.  Topics about how we think, work, or learn are of interest. Let’s hear about the risks of technology, or some new ones or ways to use them.  Yes, I like compelling speakers, but please give me new thoughts, not random aspiration.

Speakers:  I think it’s unconscionable to have an unprepared speaker who can’t manage time.  It’s even worse on panels or shared sessions where one speaker runs over. It’s just not fair to the other speakers.  It’s also essential that the talk is not a sales pitch, but instead presents real value in ideas or experience. And they should be happy to chat afterward.  It boggles my little mind when someone gets up and clearly hasn’t practiced and checked their timing. It’s appears  I’m somewhat unusual, but I really don’t necessarily feel the critical need to spend most of the time conversing with others. I don’t mind, and even can recommend some interaction, but I want to hear something substantive as well.

Schedule: I like events that have a clear and comprehensible schedule. I want to know exactly what things are at the same time, so I can choose and then vote with my feet if the first choice isn’t working for me.  Having different tracks have different schedules doesn’t work.  And as a speaker and an attendee,  I don’t like short sessions.  Give me at least an hour as a speaker to set the tone, present the topic, talk about the issues and tradeoffs, and talk about the way forward.  Similarly as an audience member, I want suitable depth.  30 minutes just isn’t enough.

Breaks: And then I want a break.  The break should be long enough to potentially chat  with the speaker at the preceding event, get out and find some sustenance, use the facilities, have a conversation or two, and get to the next event.  Workshop breaks can be shorter, as you’re with a group for a half or full day, but for separating concurrent sessions, they need to be sufficiently long.

Events: I love having social events, as a way to have those important serendipitous  conversations. An evening reception after the first day is mandatory.  I like sufficient nibbles to fend off the need to escape to dinner, or dinner actually provided. And for the end of the day, I like social lubricant.  Preferably on demand, not via a limited ration.  It doesn’t have to be a broad selection, but not having to worry about  logistics means my mind is free to focus on conversations.  I assume lunch is provided, of course, and it doesn’t have to be fancy or rich, just healthy, substantive, and reasonably tasty.  Other events, such as mid afternoon treat breaks, and mid morning snack breaks are great.  I really like it if some form of breakfast is available as well.  I think I’m not the only one who prefers to eat little bits over time, not big meals.

Expo Hall: I like to have an exhibition. I like to see what’s around. Yes, I don’t like walking past and being grabbed, but I do like it if I can go up, have an intelligent conversation about the problem solution, and not feel pressured. I like to see the alternatives, and take the temperature of the market. And I like people who might have real needs to be able to explore real solutions.  Having events  in  the expo area  makes sense to me and the vendors.

App: I used to get a PDF of the program and put it on my tablet.  Now I am happy using an app, and it’s become a must-have. I like it when I can choose sessions for my schedule and have reminders.  I like having a stream of information, though it could be via Twitter. I like having an expo map if the expo is of any size at all.  And I don’t really care for  gamification to reward participation.  While I like the engagement of users, it leads to too many frivolous posts.  I really like it if presentation material is  available through the app, and happy to do evaluations that way.

Bookstore: I think a bookstore is important, for several reasons.  For one, you can get a heads up on a speaker before you see them. Or if you miss a session, you can graze what you might have missed.  You might also want to get the works of someone who you really were intrigued by. It’s also a way to see what’s happening in the field.

Rest areas: I don’t really need speaker prep.  Sometimes it may be handy if the event is really big, but the main things is, instead, having good connection to event staff. And I think that’s true for all, not just speakers.  Having places to sit for all attendees means that  anyone needing a break whether social or physical can achieve that end.

People:  The staff makes quite a big difference when they’re knowledgeable and helpful.  This has almost always been the case, but it’s nice to have informed people ready and willing to help.  This is true for vendors as well, having friendly and knowledgeable people trumps having shills who can chat you up but can’t really answer questions.

So, what have I forgotten to address?

I realize that there are different audiences,  purposes, and business models for these events, and so not all things are comparable.  And this is also my opinion, and your motives may differ, but I hope I’ve laid out some of the thinking to help you think about what works for you.  And I hope to see you at a conference sometime!

Scenarios and Conceptual Clarity

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I recently came across an article ostensibly about branching scenarios, but somehow the discussion largely missed the point.  Ok, so I can be a stickler for conceptual clarity, but I think it’s important to distinguish between different types of scenarios and their relative strengths and weaknesses.

So in my book  Engaging Learning, I was looking to talk about how to make engaging learning experiences.  I was pushing games (and still do) and how to design them, but I also wanted to acknowledge the various approximations thereto.  So in it, I characterized the differences between what I called mini-scenarios, linear scenarios, and contingent scenarios (this latter is what’s traditionally called branching scenarios).  These are all approximations to full games, with various tradeoffs.

At core, let me be clear, is the need to put learners in situations where they need to make decisions. The goal is to have those decisions closely mimic the decisions they need to make  after the learning experience. There’s a context (aka the story setting), and then a specific situation triggers the need to make a decision.  And we can deliver this in a number of ways. The ideal is a simulation-driven (aka model-driven or engine-driven) experience.  There’s  a model of the world underneath that calculates the outcomes of your action and determines whether you’ve yet achieved success (or failure), or generates  a new opportunity to act.  We can (and should) tune this into a serious game.  This gives us deep experience, but the model-building is challenging and there are short cuts.

MiniScenarioIn  mini-scenarios, you put the learner in a setting with a situation that precipitates a decision.  Just one, and then there’s feedback.   You could use video, a graphic novel format, or just prose, but the game problem is a setting and a situation, leading to choices. Similarly, you could have them respond by selecting option A B or C, or pointing to the right answer, or whatever.  It stops there. Which is the weakness, because in the real world the consequences are typically more complex than this, and it’s nice off the learning experience reflects that reality.  Still, it’s better than knowledge test.  Really, these are  just a better written multiple choice question, but that’s at least a start!

LinearScenarioLinear scenarios are a bit more complex. There are a series of game problems in the same context, but whatever the player  chooses, the right decision is ultimately made, leading to the next problem. You use some sort of sleight of hand, such as “a supervisor catches the mistake and rectifies it, informing you…” to make it all ok.  Or, you can terminate out and have to restart if you make the wrong decision  at any point.  These are a step up in terms of showing the more complex consequences, but are a bit unrealistic.  There’s some learning power here, but not as much as is possible.  I have used them as sort of multiple mini-scenarios with content in between, and  the same story is used for the next choice, which at least made a nice flow. Cathy Moore  suggests  these  are valuable for novices, and I think it’s also useful if everyone needs to receive the same ‘test’ in some accreditation environment to be fair and balanced (though in a competency-based world they’d be better off with the full game).

BranchingScenarioThen there’s the full branching scenario (which I called contingent scenarios in the book, because the consequences and even new decisions are contingent on your choices).  That is, you see different opportunities depending on your choice. If you make one decision, the subsequent ones are different.  If you don’t shut down the network right away, for instance, the consequences are different (perhaps a breach) than if you do (you get the VP mad).  This, of course, is much  more like the real world.  The only difference between this and a serious  game is that the contingencies in the world are hard-wired in the branches, not captured in a separate model (rules and variables). This  is easier, but it gets tough to track if you have too many  branches. And the lack of an engine  limits the replay and ability to have randomness.  Of course, you can make several of these.

So the problem I had with the article  that triggered this post is that their generic model looked like a mini-scenario, and nowhere did they show the full concept of a real branching scenario. Further,  their example was really a linear scenario, not a branching scenario.  And I realize this may seem like an ‘angels dancing on the head of a pin’, but I think it’s important to make distinctions when they affect the learning outcome, so you can more clearly make a choice that reflects the goal you are trying to achieve.

To their credit, that they  were pushing for contextualized decision making at all is a major win, so I don’t want to quibble too much.  Moving our learning practice/assessment/activity to more contextualized performance is a good thing.  Still, I  hope this elaboration is useful  to get more nuanced solutions.  Learning design really can’t be treated as a paint-by-numbers exercise, you really should know what you’re doing!

Evidence for benefits: Towards Maturity Report

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An organization that I cited in the Revolution book, Towards Maturity, has recently released their 2015-2016 Industry Benchmark Report, and it’s of interest to individuals and organizations looking for real data on what’s working, and not, in L&D.  Towards Maturity has been collecting benchmarking data on L&D practices for over a decade, and what they find bolsters the case to move L&D forwards.

The report has a number of useful sections, including documenting the current state of the industry, guidance for business leaders on expectations, on listening to learners, and on rethinking  the L&D team.  Included are some top level pointers for executives and L&D.  And while the report is  biased towards Europe, respondents cover the globe including Asia, Americas, and more.

Overall, they’re finding a 19% average in  technology spending out of L&D budgets (and this has been essentially flat for 3 years). This seems light;  given that technology is a key enabler of performance and development, such a figure doesn’t seem appropriate.  Of course, given that 55% of formal learning is still delivered face-to-face, this isn’t surprising.

A more interesting outcome is comparing what they call  Top Deck organizations; those in the top 10% of their Towards Maturity Index. These organizations are characterized by four elements that are tied to success:

  • Learning aligned to need
  • Active learner voice
  • Design beyond the course
  • Proactive in connecting

Here we see key elements of the revolution. For one, learning isn’t done on demand, but is coupled to organizational improvements.  For another, the learner is engaged in the processes of determining what solutions make sense.  One that intrigues me is that the solutions go beyond courses, looking at performance support and more. And finally, L&D is reaching out across silos to engage in conversations.  These are all key to achieving results from 6 – 8 times the average organization.

The advice to business leaders also echoes the revolution. The call is to focus on performance, not on courses.  It’s not about learning, it’s about outcomes.  The recommendation  is to break down silos so as to achieve the conversations that will achieve meaningful impact.

The advice goes on: understand how learners are learning, create a participatory culture, and use  real business metrics.  All grounded in what successful organizations are doing.  The point here is not to recite all the outcomes, but instead to list highlights and encourage you to have a look at the report.  Going forward, you might even consider benchmarking your own organization!

Benchmarking is best practices, and of course I encourage best principles, but the frameworks they use are grounded in the best principles, and measuring yourself against the framework and improving is really more important than comparing yourself to others.  I will suggest that  measuring yourself and evaluating your progress is a valuable investment of time in conjunction with a strategy.

What I really like, of course, is that the data support the position posited by principles that I derived from both practical experience and relevant conceptual models. The evidence is converging that there are positive steps L&D can, and should, take.  The revolution provides the roadmap, and their data provides a way to evaluate progress.  Here’s to improving L&D!

A Competent Competency Process

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In the process of looking at ways to improve the design of courses, the starting point is good objectives. And as a consequence, I‘ve been enthused about the notion of competencies, as a way to put the focus on what people do, not what they know. So how do we do this, systematically, reliably, and repeatably?

Let‘s be clear, there are times we need knowledge level objectives. In medicine or any other field where responses need to be quick and accurate, we need a very constrained vocabulary. SO drilling in the exact meanings of words is valuable, as an example. Though ideally, that‘s coupled with using that language to set context or make decisions. So “we know it‘s the right medial collateral ligament, prep for the surgery” could serve as a context, or we could have a choice to operate on the left or right atrial ventricle as a decision point. As Van Merriënboer‘s 4 Component Instructional Design talks about, we need to separate out the knowledge from the complex problems we apply it to. Still, I suggest that what‘s likely to make a difference to individuals and organizations is the ability to make better decisions, not recite rote knowledge.

So how do we get competencies when we want them? The problem, as I‘ve talked about before, is that SMEs don‘t have access to 70% of what they actually do, it‘s compiled away. We then need good processes, so I‘ve talked to a couple of educational institutions doing competencies, to see what could be learned. And it‘s clear that while there‘s no turnkey approach, what‘s emerging is a process with some specific elements.

One thing is that if you‘re trying to cover a whole college level course, you‘ve got to break it up. Break down the top level into a handful of competencies. Then you continue to take each of those apart, and perhaps another level, ‘til you have a reasonable scope. This is heuristic, of course, but with a focus on ‘do‘, you have a good likelihood to get here.

One of the things I‘ve heard across various entities trying to get meaningful objectives is working with more than one SME. If you can get several, you have a better chance of triangulating on the right outcomes and objectives. They may well disagree about the knowledge, but if you manage the process right (emphasize ‘do‘, lather, rinse, repeat), you should be able to get them to converge. It may take some education, and you may have to let them get the

Not just any SMEs will do. Two things are really valuable: on the ground experience to know what needs to be done (and doesn‘t), and the ability to identify and articulate the models that guide the performance. Some instructors, for instance, can teach to a text but really aren‘t truly masters of the content nor are experienced practitioners. Multiple helps, but the better the SME, the better the outcome.

I believe you want to ensure that you‘re getting both the right things, and all the things. I‘ve recommended to a client about triangulating not just with SMEs, but with practitioners (or, rather, the managers of the roles the learners will be engaged in), and any other reliable stakeholders. The point is to get input from the practice as well as the theory, identifying the models that support proper behavior, and the misconceptions that underpin where they go wrong.

Once you have a clear idea of the things people need to be able to do, you can then identify the language for the competencies. I‘m not a fan of Bloom‘s (unwieldy, hard to reliably apply), but I am a fan of Mager-style definitions (action, context, metric).

After this is done, you can identify the knowledge needed, and perhaps created objectives for that, but to me the focus is on the ‘do‘, the competencies. This is very much aligned with an activity-based learning model, whereby you immediately design the activities that align with the competencies before you decide the content.

So, this is what I‘m inferring. There would be good tools and templates you could design to go with this, identifying competencies, misconceptions, and at the same time also getting stories and motivations. (An exercise left for the reader. ;) The overall goal, however, of getting meaningful objectives is key to getting good learning design. Any nuances I‘m missing?