Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » If you follow this blog, you haven’t had much to follow lately.  I’m still grappling with site-hacking problems.  Their persistence leaves me frustrated and far, far from gruntled. Two busy, productive couple of days working with a great client have re-energized me, so I’m back in business.  And, as a bonus, we’re halfway through the Ten Steps. Step 5 in Ten Steps to Complex Learning` is "analyze cognitive structures."  As the diagram depicts, this step falls under the "supportive information" component of the overall learning blueprint. Van Merriënboer and Kirschner point out that when someone encounters a task that’s different from what he’s seen before, procedural knowledge isn’t enough.  He needs strategic knowledge-a way to figure out how to do what he haven’t done. I’ve already talked about SAPs (strategic approached to problem-solving).  If you’re designing learning, these may already exist in job descriptions, instructional material, and other stored knowledge.  If not, you need to identify and make such SAPs explicit, which explains the three sections of this chapter: Specify SAPs. Analyzing intuitive cognitive strategies. Using SAPs in design decisions. (Time out for a quibble, and not about vM&K’s apparent determination to avoid parallel lists.  I really dislike their use of "intuitive" here.  What they mean, as you’ll see in a bit, are the homegrown strategics that newcomers bring with them to a new domain.  In other words, those existing strategies aren’t intuitive in the sense of ingenious;  they’re naive.) SAP: a plan with a goal-and rules of thumb A strategic approach to problem-solving has a goal, and likely subgoals as well, related to solving problems in a particular domain.  The SAP also has heuristics to help reach that goal.  In fact, those are key to SAPs. …SAPs are always heuristic….though they may help a learner to solve problems in the task domain, their application does not guarantee the solution of the problem. Although they are less powerful than algorithmic procedures, power is exchanged for flexibility, beause SAPs may be helpful in many more different problem situations than a solution algorithm. In identifying the cognitive strategies that go into SAPs, you will: Assemble material to develop problem-solving guidance (like process worksheets) Help refine classes of learning tasks (in other words, identify a sequence of simpler to more complex cognitive strategies) Start the development of a key part of the supportive information discussed under Step 4. If you’ve read any of the other posts in this series, you know how vM&K will go about identifying these strategies.  They’ll interview and observe expert performers performing the actual tasks, starting with relatively simpler ones and progressing to more difficult ones. Sometimes the problem-solving process is mostly linear or sequential.  The much-maligned ADDIE model for instructional design (analyze, design, develop, implement, evaluate) fits that category.  If you were working with expert designers, you could identify simpler and more complex goals in each of those stages, and from that develop simpler and more complex SAPs. vM&K use "solving thermodynamics problems" as an example of a non-linear set of phases to use in a particular domain.  Another example might be the CRAP principles for designing text and graphics (contrast, repetition, alignment, and proximity) that Robin Williams explains in The Non-Designer’s Design Book. Grasping rules of thumb The general form of a heuristic is, "If you want X, then do Y."  Rules of thumb are midway between domain-specific algorithms (like, say, how to calculate the number of shingles needed for a roof) and full-blown problem-solving methods in a domain. The image at the right (which you can click to enlarge) is an example of rules of thumb for managing conversations on a blog. vM&K offer this advice: Provide learners only with rules of thumb they don’t yet know. Limit the rules to those necessary for performing the most important tasks. Write them clearly.  (That is, "formulate rules-of-thumb in a readily understandable way…and use the imperative to make clear that they are directions for desired actions." ) Find a balance so the text is as specific as possible but applies to all the situations where the rules make sense. Analyzing intuitive strategies You see that the first step is to analyze the cognitive strategies used by experts, since these are built up and refined over time as the experts grapple with a range of problems in the domain.  What you end up with is how the task should be performed. If you observe the target learners addressing the same tasks, you find out how they are performed.   These are the approaches that non-experts figure out on their own-that they intuit, hence the lable "intuitive strategies."  Often, though, these naive approaches don’t work all that well. For examples, novices often take what the authors call a top-down, depth-first approach.  In programming, that might mean breaking an overall problem into a group of subproblems, and then attacking each subproblem in depth: writing highly detailed code for one section at a time. As a result, the novices can lose track of relationships between sections, and they’ll often spent a lot of time linking things together after the fact. Experts in contrast take a top-down, breadth first approach.  After identifying the subproblems, they’ll continue to expand each subproblem before starting extensive coding. An instructional design example might be breaking a large course up into what seems like logical sections.  Less-experienced designers tunnel down into the separate sections, writing them in detail.  More experience designers (ahem) will break those subsections down but will tend to think of them in outline or summary mode, making it easier to move up and down levels and see the larger picture. In a client project I’ve been working on, this means we haven’t yet finalized the overall sequence for what will be a two-and-a-half-day workshop, but we have what I think of as lots of recipes for areas of concentration and for activities.  We sketch enough detail so understand them and look at the design for other course elements.  It’s much easier to refine and shift at this stage. So we won’t end up with, say, a freestanding section on ethics (which most of the time is like a long sermon on a warm Sunday).  Instead, we plan an activity where participants handle a typical contract problem, then they’ll get questioned by the client about business-ethics issues, embedded (as in real life) in what looks like real work. Mind the gap Not only do gaps exist between the rules of thumbs that novices use and those that experts use, but the expert heuristics may be counter-intuitive to the newcomer.  (Maybe this is where "intuitive strategy" came from?  Not that I’m obsessing about the term.) Think of a beginning driver: her naive model for steering is "keep the car straight at all times," resulting in constant adjustments of the wheel.  The skilled driver’s heuristic might be something like "aim 20 feet ahead of the car," providing more reaction time and seeming to ignore the distance directly in front.  But the latter is the more effective strategy. So what?  If you find that novice learners come to complex learning with naive strategies in place, these will conflict with more carefully worked-out strategies. SAPs and design strategy If you’ve developed strategic approaches to problem solving, you’ve got a head start on a number of design decisions. You can design problem-solving guidance, like process worksheets or performance constraints. You can present rules of thumb as statements ("if you want X, do Y") or as guiding questions ("what might lead you to develop a job aid for this task?"). You can develop or refine task classes based on a sequence of SAPs. You may need to provide extra guidance, especially to prevent the unproductive or even mistaken results that would come from the naive strategies.  Performance constraints can come into play.  The authors have an example in which researchers have to frame an effective database query before they can enter it into the database-to provide practice in preparing effective queries. Similarly, the use of task classes (groups of problems at a similar level of difficulty) provide extra opportunity for the novice learner to work with the new strategies-although, as vM&K point out, some intuitive strategies are highly resistant to change. Modeling examples can help (seeing a skilled performer in action and hearing her comment specifically on her strategies).  In addition, less use of inductive approaches and more guided discovery will allow learnes to interconnect parts of the new skills, and to integrate the new strategies into their repertory. In a final triple play: You can give an SAP directly to a learner (it’s supportive information, remember, which means it’s helpful for the non-recurrent tasks). SAPs can help you find or design modeling examples. SAPs can support cognitive feedback-for example, have learners compare their own process with a given SAP. This was the shortest Ten Steps chapter to date, so the next post in the series will move on to Step 6, Analyze Mental Models. CC-licenses project-status photo by brylyn. CC-licensed rules for blog conversations by choconancy1. CC-licensed audio-mixer photo by magnifynet. The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do) (that's this post) Step 6: (thinking about) mental models

I’ve been here before, but only in kitchens-sitting around, drinking tea and eating biscuits. Buddy MacMaster

This post is my slightly-belated contribution to the May 2009 Working/Learning blog carnival, hosted at Kevin Jones’s Engaged Learning blog. The CSTD National Symposium in Halifax, Nova Scotia has just ended.  The theme was All hands on deck-because organizations need to get the most out of all their employees, and because you can’t escape the sea in Nova Scotia any more than you can escape tartan. I was eager to make a presentation at this session, and fortunately for me, CSTD liked what I proposed doing.  I think that speaking to your professional peers-in the sense of  "here’s something interesting I’ve been working on"-is a great opportunity. On a ship, of course, a deck is a workplace-it’s where you are.  As a learning professional, I want to make sure my personal deck has the equipment and room I need to be effective.  Here are my thoughts on ways to do that: Do what matters. The obvious thing is to work on great projects.  In my experience, you don’t always know which ones will turn out to be great.  And in larger organizations, you sometimes have little choice.  Inside nearly every project, though, there are things that matter-to you and to your organization.  So, whatever the work you have to do, do it well.  Go beyond the routine; avoid sticking to the same old paths. Change your level. I don’t mean "get promoted," necessarily.  I mean to zoom in to the details of what you do, and zoom out to see things in a larger perspective.  If you’re developing training courses for customs workers, find out how the particular skills fit into the larger context of their jobs, and how their jobs fit into the context of their location and their agency. The old story about turtles all the way down in one sense is true.  It’s systems all the way down, and all the way up: inputs, processes, outputs.  Changing your level means you’re better able to see how what looked like a standalone function aligns with other functions for some higher-level process. Watch yourself. Along with changing your level, I think it makes a lot of sense to change your distance from yourself.  Ask, explicitly, what you’re doing.  Where are you running into difficulty?  What are you doing about that? From another angle: what have you been doing that you get jazzed about?  A couple of weeks back, I was bouncing in my chair (during a meeting with clients who have been too polite to comment on this) because of the many great ideas and possibilities that were emerging. It’s this self-awareness, almost the idea that your job is a kind of science experiment, that I think holds great value. Think of others. If the reflective question was "What have I been doing?" then the collaborative question is "How’s my problem like problems that aren’t mine?" What have you been doing that someone who’s doing something different could learn from?  What have you figured out that I haven’t? I saw a definition of "expert" as someone who knows something you don’t, that you’re glad to learn.  If you pay attention to your work, if you change levels so you get a fuller picture, and if you watch what you do and what results, you’re going to be a hell of an expert on the specifics. The next step is stripping the trivial out of those specifics so that another person can extrapolate to a different situation. Be yourself. I’m not an expert on using web 2.0 tools at work.  I tried to make that clear in my presentation: I’ve learned how to work with some of these tools, and I can show you: Stuff other people have done with them Ways to try out the tools for yourself A little bit about how they look under the hood I didn’t pretend to know more than I do, nor (I hope) am I over-impressed by my own sagacity.  I had fun creating my presentation, I tried to be clear about who might find it interesting, and I had lots of chances to practice saying, "I don’t know much about XXX; tell me more about what you’re doing." Few things will make you smarter about what you do than trying to explain what you do to others in a way that can benefit them. CC-licensed turtle photo by wwarby.

Note: this is something of a repeat.  When I checked the Whiteboard this morning, my last few posts seem to have disappeared.  I haven’t figured out why, but I decided to recreate them-it seemed a simpler path than trying to travel through time.  Please excuse the repetition (and the apparent incompetence). Browsing through some Mr. Tweet suggestions (recommendations of people to follow on Twitter), I happened across Marianne Lenox, "gadabout library trainer." Earlier this month, she posted the TED commandments, advice given to presenters at the TED talks. I’m just going to re-post the image she used (by Rives, transcribed by Tim Longhurst via Garr Reynolds) and the text she added. Thou Shalt Not Simply Trot Out thy Usual Shtick. Thou Shalt Dream a Great Dream, or Show Forth a Wondrous New Thing, Or Share Something Thou Hast Never Shared Before. Thou Shalt Reveal thy Curiosity and Thy Passion. Thou Shalt Tell a Story. Thou Shalt Freely Comment on the Utterances of Other Speakers for the Sake of Blessed Connection and Exquisite Controversy. Thou Shalt Not Flaunt thine Ego. Be Thou Vulnerable. Speak of thy Failure as well as thy Success. Thou Shalt Not Sell from the Stage: Neither thy Company, thy Goods, thy Writings, nor thy Desparate need for Funding; Lest Thou be Cast Aside into Outer Darkness. Thou Shalt Remember all the while: Laughter is Good. Thou Shalt Not Read thy Speech. Thou Shalt Not Steal the Time of Them that Follow Thee.

Browsing through some Mr. Tweet suggestions (recommendations of people to follow on Twitter), I happened accross Marianne Lenox, "gadabout library trainer." Earlier this month, she posted the TED commandments, advice given to presenters at the TED talks.  I’m just going to repost the image she used ("by Rives, transcribed by Tim Longhurst. Via Garr Reynolds") and the text she added. Thou Shalt Not Simply Trot Out thy Usual Shtick. Thou Shalt Dream a Great Dream, or Show Forth a Wondrous New Thing, Or Share Something Thou Hast Never Shared Before. Thou Shalt Reveal thy Curiosity and Thy Passion. Thou Shalt Tell a Story. Thou Shalt Freely Comment on the Utterances of Other Speakers for the Sake of Blessed Connection and Exquisite Controversy. Thou Shalt Not Flaunt thine Ego. Be Thou Vulnerable. Speak of thy Failure as well as thy Success. Thou Shalt Not Sell from the Stage: Neither thy Company, thy Goods, thy Writings, nor thy Desparate need for Funding; Lest Thou be Cast Aside into Outer Darkness. Thou Shalt Remember all the while: Laughter is Good. Thou Shalt Not Read thy Speech. Thou Shalt Not Steal the Time of Them that Follow Thee.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » Note: this is a repeat post (I think).  When I checked the Whiteboard this morning, my last few posts seem to have disappeared.  I don’t know why.  I decided to recreate them-it seemed a simpler path than trying to travel through time.  Please excuse the repetition (and the apparent incompetence). "What we know determines what we see, and not the other way around."  That’s how van Merrienboër and Kirschner start Step 6 (analyze mental models) in Ten Steps to Complex Learning. Two people hiking the mountains in France, they suggest, see different places: the geologist sees rock formations; the cyclist sees gear ratios. As the diagram shows, Step 6 fits with other elements that make up the supportive information component of the Ten Steps model. (You can click the diagram to enlarge it.) From a learning perspective, supportive information underpins those skills that you apply differently in different situations. vM&K see three different types of mental models: conceptual ones that answer the question, "What is this?", causal ones that answer, "How does this work?", and structural once that answer, "How is this organized?" This chapter of the book parallels the previous one: Specify domain models Analyze intuitive (meaning "naive") models Using domain models to make design decisions Models: good news, bad news A mental model is a description of how the world of some domain is organized.  You often hear "mental map" as a synonym, because a map shows layout and relationships. You can find mental models in documents; you can also develop them by talking with expert performers who can describe the models they use as they work. vM&K suggest that such discussions start with simpler classes of tasks and work up to more complex ones.  At the same time, they lean away from the common belief that the more you know about a domain, the better able you are to solve problems in it. In a sense, everything is related to everything, and thus the analyst can build seemingly endless networks of interrelated pieces of knowledge.  Therefore, new relationships must not be added if a competent task performer cannot clearly explain why newly associated facts or concepts improve her or his performance. Getting the concept Conceptual models explain a domain by various features.  You can classify computers by their processors, or by their age, or by manufacturer, or by color (though most of the time, color’s not a particularly helpful organizer). In kind-of relationships, the model explains that both "chair" and "table" are kinds of furniture.  Kind-of relationships lead naturally to taxonomies, which are hierarchical models, like the biological kingdom, phylum, class, order, and so on. Similarly, part-of relationships show that one concept is contained within a larger one.  A leg is part of a chair; a keyboard is part of a laptop computer. A hierarchical model like a taxonomy isn’t the only possible conceptual model.  Concept maps and semantic networks also show relationships; the latter is more carefully definite with explicit labels for relationships, as in the example on the left (from Wikipedia). These relationships are fairly obvious, but vM&K offer some other types of relationships that would be useful in analyzing and in teaching mental models. For example, experiential relationships connect a concept to a familiar, concrete example: the alternator on a car is like a generator (the device that cars used before alternators).  Similarly, analogical relationships aid understanding by comparing a new concept to one that’s familiar although outside the domain in question-for example, the theme used by a WordPress blog is like a set of clothes: changing the theme changes the appearance of the blog, but not the content (the posts). Other types of relationships: Prerequisites: if you understand the concept of division, it’s easier to learn the concept of prime number. Location-in-time: the relation in time between two concepts in the domain (pilot program relative to implementation) Location-in-space: in a scientific article, the results section appears after the method section. Natural-process: evaporation and condensation have a relationship, but not a causal one (evaporation doesn’t cause condensation, and vice-versa) Structure matters Another major type of mental model is the structural model, which explains how elements of the model, related by time or space, fit together.  For example, the life-stages of an organism are a time-based mental model.  vM&K mention the location-in-space models of chess experts, who are able to grasp the relationships of chess pieces. I’ve read elsewhere that when chess pieces are arrayed randomly, expert players aren’t any better able than novices to remember the positions, probably because the relationships seem arbitrary to the experts. Often there are interrelated sets of structural models-this is complex learning we’re talking about.  You can think of these as the 50,000-foot version, the 20,000-foot version, the treetop version, and so on, as the focus becomes more and more specific.  I could have a model for writing a nonfiction book; within that, a model for a typical chapter; within that, models for constructing sections, paragraphs, and even sentences. Causal models: domains at work Causal models concentrate on cause-and-effect or natural processes.  They form principles that allow learners to explain how something works, or why it isn’t working. Molecular biologist Bonnie Bessler and her colleagues discovered a form of communication in bacteria that helps explain how single-cell organisms as a group can engage in behavior beyond their individual capabilities.  You can hear her describe this quorum-sensing model in a February 2009 TED talk. vM&K acknowledge that it may be helpful to focus on only one type of model at first, depending on the nature of the domain.  For example, areas like mechanical engineering, architecture, and instructional design are heavily analytic, and so structural models make a good starting place. Intuition: not necessarily a good thing As in Step 5  (analyze cognitive strategies), newcomers to a field often bring with them their own mental models.  These "intuitive or naive mental models are often fragmented, inexact, and incomplete," vM&K argue.  Novices are usually unaware of the underlying relationships between elements, and frequently carry unexamined misconceptions. One example is the notion that the internet is a centralized system, with all computers eventually connected to some vast, central server.   This hierarchical model is easy to imagine, but gets in the way of someone trying to understand how the internet actually works. A favorite example of mine is the Microsoft Word document template; another is the cascading style sheet.  Both are used to control appearance and layout, either of a Word document or a web page.  The underlying concept, not always grasped by newcomers, is that there is no necessary relationship between the text on a page and the appearance of that text (size, color, alignment, etc.). To the newcomer, a document is a document.  Only when that naive model is extended does the newcomer understand that the width, spacing, font, height, weight, and so on can be controlled without any regard to the actual words. Models and design decisions As with cognitive strategies, the designer develops mental models only if there aren’t pre-existing ones.  With models in hand, the developer is able to carry out essential design tasks. For example, a progression of mental models helps to refine the task classes that are a central component of the Ten Steps.  The simplest domain model enables learners to perform the simplest class of learning tasks. vM&K give a three-level progression for electronics troubleshooting as an example of this relationship between models and task classes: In the zero-order model, the model has basic principles of electricity.  The tasks might involve a problem like "given this arrangement, will the light bulb be on, or off?" The first-order model adds principles related to changes-"Is there an increase in voltage when the resistance is lowered?" The quantitative model moves on to more complex laws of electricity (e.g., Ohm’s law) with questions like "what is the voltage across points X and Y in this circuit?" Because mental models are supportive information, you can present them explicitly to the learner (e.g., to introduce or explain the domain).  You can also use them to help identify relevant examples and case studies.  Finally, you can use the model as a form of cognitive feedback, allowing the learner to compare his work with a given model. Intuitive mental models-those homegrown structures that novices may bring to a new field-can be especially resistant to change.  So it might be worth investigating whether that’s true of novices in the field you’re dealing with.  You may need to begin with assumptions in those naive models and gradually work on elaborating new information. Mental models versus cognitive strategies The Ten Steps sees a reciprocal relationship between these two types of supportive information.  The main difference is in how they’re used.  Cognitive strategies focus more on the task performer’s actions, which mental models focus more on the domain itself.  going back to the map analogy I used earlier, you can use the map to plan a route from A to B (the cognitive strategy), and you can use the same map to understand the layout of a geographic area (the mental model). CC-licensed images: mental map photo by michale. Bird-chess photo by striatic. Sailing image by A Siegal. The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental models (that's this post) Step 7: procedural info, or, how to handle routine

On a long-ago training assignment, I was told that Amtrak (my employer at the time) was moving to SNA/SDLC architecture. We never covered that in English Literature before 1500, so I asked one I.T. guy what that meant. "Systems network architecture, synchronized data link control." So I asked another guy.  "That means you can get to any of our mainframe computers from any of our terminals." So, learning at work isn’t always straightforward.  Both answers have been useful to me: the second as a clear explanation, the first as a metaphor for unhelpful precision.  Granted, nearly 30 years later, I can still recite the tech definition.  But I’d argue this mainly demonstrates the relatively low value of definition as opposed to application.  Most of the time, on the job, it’s not what you call things, it’s what they do. Both explanations were brief, like a tweet on Twitter.  Tweets are like darts: they move quickly, and what’s important is the destination.  That’s either destination in the sense that you’re nudging another person or a select group in "public," or destination in the sense that what counts isn’t the tweet but what it points to. A couple of months back, Marcia Connor, Clark Quinn, and a few other people started #lrnchat.  This is a schedule but informal Twitter-based conversation around learning.  (Thursday evenings, 8:30p - 10p Eastern time; "about" stuff here.) When Marcia and I talked about this (on Twitter), I was skeptical, but decided to participate in a couple of the chats. Very dart-like, but in a good way.  There’s often a proposed theme to the conversation, but no topic police.  To me, the conversation is like the end-of-day chatter of people at a conference: energetic, more concurrent than liner, and without ribbons for board members, speakers, or eminent gurus. (Here’s the transcript for the #lrnchat of 5-28, to give you an idea.) I find Twitter helpful, not essential.  My phone isn’t all that smart, and I don’t spend weekends in from of my computer, so especially on weekends, I’m not on Twitter, and I don’t spend much effort catching up.  That’s kind of like trying to catch up on the tides that happened the week before you got to the beach. "Essential" isn’t the real issue, though.  For me, one question is: how can I connect with other people, especially if their work relates in some way to mine?  I’ve done that face-to-face, of course.  I’ve done it through professional organizations.  I’ve done it through email.  And, more recently, I’ve done it through my blog, through Facebook, and through Twitter. Eventually the connection transcends the medium: you start thinking about what you discussed with Cammy or with Harold, not about where.  I will concede, however, that today is different.  Some people I’ve only connected with online are in DC for a conference today, and we’ll be meeting tonight at the east coast’s largest purveyor of Guinness.  Twitter’s great, but I plan to do more than link to a pint. Custom (Dodge) Dart detail by o2b.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » Ten Steps to Complex Learning says that complex skills have aspects that you apply differently for each task (the non-recurrent skills) and aspects that you apply in the same way each time you use them (recurrent skills). Heck, even I’ve said that a time or two in this series.  I bring it up again because Step 7, design procedural information, marks the move into the third of the four components in van Merriënboer and Kirschner’s model: the procedural information component into which those recurrent skills fit. (You can click the image to see the complete chart with all four components and all ten steps.) vM&K see three types of procedural information: Just-in-time (JIT) display of information (prerequisites, rules, procedures) Demonstrations of applying the information Corrective feedback about errors The heart of this chapter is that when you’re dealing with recurrent skills like formatting a document or processing a mortgage or digitizing video, you want to help the learner acquire these skills-compile the knowledge, in the book’s terminology.  As he does so, he creates his own specific cognitive rules, and then can perform without the need for a cognitive schema (which would be needed for a non-recurrent skill). Take reading: English has a complex grammar and vocabulary, so learning to read it is a complex skill.  That skill includes many recurrent aspects.  As you read this paragraph, you’re not sounding out the individual syllables; you’re scarcely aware of individual letters unless your attention is drawn to them.  That’s because you’ve automated rules for recognizing a word and relating it to those around it. Sections in this chapter of the Ten Steps: Providing JIT displays Giving examples of JIT information (okay, so the book says "exemplifying") Presentation strategies Corrective feedback Procedural information in the training blueprint Just the steps, just in time One definition of a job aid is something that tells you what to do and when to do it, in order to reduce the need to memorize.  JIT display of information is like that. For a given set of tasks (meaning, ones with similar difficulty), the procedural information is likely the same, and so you’d provide that information for the first task.  You might gradual reduce or fade the amount of procedural information as the learner continued with additional tasks. The two forms of JIT information correspond to the next two steps in the book: the cognitive rules that you follow (Step 8), and the prerequisite information necessary to apply those rules (Step 9). As I read this chapter, it occurred to me that a lot of organizational training often tries to treat non-recurrent tasks as recurrent, and vice-versa. Take the supposed soft skill of interviewing a job candidate.  Some aspects of that skill are recurrent: reviewing the requirements for the job, reading the candidate’s resume, arranging a time and place for the interview, making a checklist of items to verify, using both open and closed questions. So in "how to interview" training, you could provide a checklist to help prepare and conduct an interview. The actual conversation, though, is always going to be non-recurrent: you’re not interviewing the same person over and over.  Generic training on "interview skills" can’t just give you a checklist of ten questions and five phases.  As noted earlier, for non-recurrent skills, there’s no single right answer. What makes for successful just-in-time display of procedural information? First, a modular structure with small steps.  You want the information to have a clear goal that the performer can easily accomplish: "How to change page orientation" is vM&K’s example.  The small size and straightforward goal minimize cognitive load.  Prerequisite knowledge (e.g., definitions of landscape and portrait) can appear as callouts or hyperlinks. And when it comes to procedural information, nice-to-know isn’t. Next, a focus on entry-level users.  A key difference between a procedure and a systematic approach to problem-solving is that procedures are virtually mechanical (vM&K say "algorithmic"): if you follow these steps, you get this result. Third, you want to avoid splitting the learner’s attention.  That means minimizing any requirement for the learner to shift back and forth between the actual task and the supporting information. Here’s an example of those two items being closely joined (in this case, how to test the resistance of conductors in wiring):  (This diagram and some other examples of the split attention effect appear in section 5.8 of  this article by Dr. Graham Cooper of Australia, "Research into Cognitive Load Theory and Instructional Design at UNSW.") Sometimes you can’t help splitting attention-a person might need to consult a procedure separately from the immediate task.  You can’t easily assemble machinery while holding the manual, and you can’t always label the parts with the steps. One approach is to put parts of the task into the reference (through diagrams and illustrations); another one, just on the horizon, is to adapt the environment-e.g., a heads-up display that makes the steps visible through a special pair of glasses. JIT: know it when you see it One way to present just-in-time information is through demonstrations, like the "show me" options in help systems that demonstrate how to, say, create a chart in Excel. vM&K strongly urge using relevant, whole tasks for such examples.  Let’s say the specific procedure is getting a set of PowerPoint slides to start with a specifed number.  One demonstration could have a person who’s created two files and wants to start numbering one set whether the other left off.  The larger context is someone who wants two files (Part 1 and Part 2), and the specific example is getting Part 2 to start numbering at, say, 45. That places the renumbering skill in a concrete setting.  A later example could have someone wanting to start numbering after the title slide (so the title doesn’t have number, and so the second slide is numbered 1).  The same procedure as the other example, but a different demonstration with a different real-life context. A second way to deliver JIT information is through what the Ten Steps call instances, meaning examples.  Here you might provide the learner with an example (an instance) of concepts or principles of the skills being learned.  For a researcher, you might provide descriptions of different types of databases.  Again, you’d want to do so in a context that relates to the task being learned-databases relevant to science if the research is in a scientific setting. Finally, you may need to provide a range of demonstrations or instances.  In vM&K’s example of changing page orientation, you might change from portrait to landscape, and vice-versa.  You might change the layout of a multi-page document.  And you might change the layout of one section in a multipage document, and then change back afterward. That’s enough for one post.  Next time: presentation strategies for procedural information (some of which surprised me), corrective feedback, and probably a few remarks about knowledge compilation. The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental modelsStep 7: procedural info, or, how to handle routine (that's this post) Procedural in practice

My dad left a small Canadian town for Detroit in 1951; my mother, my brothers, and I joined him a year later. With Chrysler so much in the news (he spent 24 years at the Warren Stamping Plant), I’ve musing about how he managed to build a vibrant life in a new country starting at age 38.  Call it "Networking with Hughie."  These come to me as echos of how he talks. "What’s new, strange, or startling?" That’s what Dad says to someone he hasn’t seen for a while.  You can read it just as "what’s new," but I also see it as an invitation to open an experiential door or two: What’s going on in your world that you haven’t figured out yet?  (As Asimov said, the key phrase in science isn’t "Eureka!" but "That’s funny…") What’s surprised you lately?  (Surprise to me is a sign that your expectations weren’t quite up to reality.  Could be good, could be bad, but certainly not predictable.) "Ciamar a tha thu?" When someone answers Dad’s phone call, he’ll reply this way-if they’re in his vast circle of friends and family from Cape Breton Island.  The phrase is Scottish Gaelic (kimmer a hah oo, "How are you?") . When he was growing up, Gaelic was common; his father and his father’s best friend preferred it to English. On one level, he’s just saying hi.  At the same time, he’s being playful (which is a pretty good networking technique).  Dad can’t hold a conversation in Gaelic, and with one or two exceptions, neither can anyone else he knows. He’s also re-activating the connection.  Not heavily, not tediously; he’s not mourning the loss of Cànan Nan Gàidheal. What he’s doing, I think, is lightly making explicit one link he has with the other person. "Going back to God’s country" Hemingway said that Paris is a movable feast; for Dad, the feast has always been Cape Breton.  But he’s an immigrant, someone who moves to stay, and not a sojourner, who longs to move back. That’s true even though he’s probably made more than a hundred trips back home. Planning the trip, he’d tell friends and coworkers about getting ready to go to God’s country.  And once back, he’d cheerfully tease those who’d never been (on what their lives were lacking). None of this was in a whiny, it’s-so-much-better-back-there way. To me, that’s like "be here now." Cape Breton is a grounding for him, but it isn’t the entire world.  It’s part of what makes him authentic, part of what he brought to his circle of friends. And what a circle.  Dad was an auto worker, a UAW member-but his closest friends included an attorney, a CPA, the owner of a tool and die business, the manager of a jewelry store, and a top administrator in the Detroit school system. He’s always been at ease with who he was, and curious about things in worlds outside his own.  How else are you going to find the new, the strange, or the startling? CC-licensed images: Startling Stories cover by Tohoscope; photo of the Margaree River by luvmycrows.

Series: Ten Steps to Complex Learning « Previous post in this series • The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental modelsStep 7: procedural info, or, how to handle routineProcedural in practice (that's this post)

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental modelsStep 7: procedural info, or, how to handle routineProcedural in practiceStep 8: cognitive rules, or, when there IS a right way (that's this post) Step 9: prequisites, or, ya gotta start somewhereStep 10: part-task practice (getting better at getting faster)

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental modelsStep 7: procedural info, or, how to handle routineProcedural in practiceStep 8: cognitive rules, or, when there IS a right wayStep 9: prequisites, or, ya gotta start somewhere (that's this post) Step 10: part-task practice (getting better at getting faster)You? Auto? Practice.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental modelsStep 7: procedural info, or, how to handle routineProcedural in practiceStep 8: cognitive rules, or, when there IS a right wayStep 9: prequisites, or, ya gotta start somewhereStep 10: part-task practice (getting better at getting faster) (that's this post) You? Auto? Practice.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grewProblem solving, scaffolding, and varied practiceStep 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudesStep 4: supportive info (by design)Learning to learn (an elaboration)Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental modelsStep 7: procedural info, or, how to handle routineProcedural in practiceStep 8: cognitive rules, or, when there IS a right wayStep 9: prequisites, or, ya gotta start somewhereStep 10: part-task practice (getting better at getting faster)You? Auto? Practice. (that's this post) Media’s role in complex learning