It is better to know some of the questions than all of the answers. — James Thurber When you work independently, sometimes the project you accept wouldn’t be your first choice, but you don’t have much in the way of other choices. Some of my work last year fit into the latter category.  For quite a while I was writing or rewriting standard operating procedures in a manufacturing facility-not as exciting as it sounds. Opportunities lately pique my interest more, either because of the client’s business itself or because of how that business connects to the outside world. That’s the "work worth doing" part-when what you’re working on seems to have a larger value than the compensation you receive for that work. Someone who seems to enjoy his work is Jeffrey Levy, a On a different track, I’ve been finding out more about government and social software tools.  On Twitter, I follow Jeffrey Levy (@levyj413).  He’s director of web communications for the Environmental Protection Agency. I’m very interested in how the government will make use of new tools, and Levy’s approach makes  a lot of sense to me: Remember: mission first, choose the right tool, measure and evaluate, and then teach the rest of us. Thanks to Levy’s messages, I find useful ideas and smart people like Gwynne Kostin, whose blog, Gwynne on dot-gov, asks, "How do we use technology and communications tools to make government more useful, more efficient, and more transparent?" As with her post, Open data: compare and contrast.  It highlights some of the constraints government works under-for example, implications of the Privacy Act, which bars agencies from releasing records without a request from, or the consent of, the individual to whom the record pertains. No answers, but good questions to think about before everyone’s entire data history is available online to everyone else.

Until this morning, I didn’t know about Ada Lovelace Day, which seems to have resulted from a pledge/challenge by Suw Charman-Anderson.  The idea was to highlight women in technology. Looking at my feedreader, my Twitter stream, and my Facebook page, I see quite a few women whose work hinges on some way in technology.  But the first name that came to mind is someone not all that well known any more. In her later years, she was known as "Mother COBOL."  Typing that reminds me that COBOL isn’t all that well known any more, either. Grace Murray Hopper taught mathematics at Vassar in the 1930s while earning her PhD at Yale.  She resigned her position late in 1943 to join the Navy Reserve WAVES.  As a lieutenant with the Bureau of Ordinance, she was assigned to work on the Mark I computing machine, for which she eventually produced a 500-page manual of operations. The Navy used the Mark I for gunnery and ballistics calculations.  It was 55 feet long, 8 feet high, and contained over 750,000 parts.  It was the predecessor to several other early computers such as UNIVAC. Hopper invented the compiler-the program that translates computer programs into machine language.  She claimed that she did so because she was lazy; the compiler did the grunt work and allowed her to focus more on mathematics.  Her FLOW-MATIC compiler so greatly influenced COBOL that she’s known as the mother of COBOL. In 1997, the Gartner Group estimated that 80% of the world’s business ran on COBOL. After World War II, Hopper tried to transfer to the regular Navy, but was turned down because of her age (she was 38).  She remained in the Navy Reserve until 1966, retiring as a commander.  She was recalled to duty "for a six-month period" that lasted four years, and after retiring again was asked to return once more. When she finally retired for good, Rear Admiral Grace Hopper at age 79 was the oldest officer in the Navy.  The ceremony was held on board the Constitution, the oldest ship in the Navy. Hopper died in 1992, at 85, and is buried in Arlington National Cemetery. In 1969, Hopper won the Data Processing Management Association’s first "man of the year" award. The Association for Computing Machinery has an annual Grace Murray Hopper Award for young computing professionals. The USS Hopper, a guided missile destroyer, is only the second U.S. Navy warship named for a woman. (I added the following very late in the day.) Information about Hopper from the Naval Historical Center in Washington, DC, including this image.  It’s a page from the log book for the Mark II Aiken Relay Calculator used at Harvard University.  The entry, for Sept. 9, 1945, explains that a moth was found at Relay #70, Panel F. "First actual case of bug being found."  Reportedly, the moth was taped into the log book, and the entry made, by Grace Hopper.

Series: Ten Steps to Complex Learning • Next post in this series » I’ve been (slowly) reading Ten Steps to Complex Learning, by Jeroen J. G. van Merriënboer and Paul A. Kirschner.  The subtitle explains why: A Systematic Approach to Four-Component Instructional Design. I read a lot about the death of instructional design, the end of training, and the New Jerusalem of learning that’s due any day.  Certainly a lot of superstition and nonsense gets daubed with the label "instructional design," like a kind of cognitive Clearasil.  Still, I can’t help think that few people are going to learn to manage power-generation stations, conduct clinical trials, sell aircraft engines, or produce FEMA-acceptable flood elevation certificates solely through self-guided learning. So I decided to plow through this book, which I’ve described with a bit of humor as being written in a language very much like English: the prose is dense, and very academic.  So far it’s worth the effort, and I’m going to summarize key parts here. (Key part: something I pay enough attention to that I make a note on paper as I’m reading.  This is an ancient custom among my people.) Van Merriënboer and Kirschner aren’t shy: The fundamental problem facing the field of instructional design these days is the inabiliity of education and training to achieve transfer of learning. Which is something like AIG not being able to actually insure anything, isn’t it? One point the authors make is that most complex skills require the learner to coordinate from a range of "qualitatively different constituent skills."  That last phrase is important to them: not only is the whole of a complex task more than its parts, but the constituent skills are not parts of the larger task but aspects of it.  They’re not sub-skills, which you add together to make up the Big Skill. Which, they argue, makes the analytic approach of many traditional instructional design approaches counter-productive.  For example, what they call the transfer paradox comes into play: the instructional methods that work best for isolated objectives often work poorly for integrated objectives. To make that plainer: we spend too much time fiddling around with nice, clear, low-level objectives.  Then we lack time and money (and, perhaps, the will) to develop integrated learning.  Then we wonder why the training/learning function has such a dismal reputation. But those isolated ones are what we tend to grab onto, because it’s easier to design around them, easier to create test items, and easier to cram them into an LMS ("Lessons Mean Simplicity"). Learning to use the Amtrak reservation system is a complicated task, but maybe not all that complex.  Learning to act on traveler’s questions is also complicated.  Developing training for either set of skills is inherently less difficult than developing holistic training for an effective Amtrak reservation agent-but that’s what Amtrak’s really looking for. The usual answer to the problem often seems to be "watchful waiting." The performers go from training to the job, and we hope that their random encounters with reality end up filling the gaps. Van Merriënboer and Kirschner want to grapple directly with such complex learning problems.  The model they advocate sees four main components to a learning blueprint: The learning tasks that someone needs to master.  (Strictly speaking, I’d say these are the on-the-job tasks which the person currently doesn’t know how to do, but it’s not my model.) The supportive information that comes into play when you’re working with skills that are performed differently from problem to problem.  These skills, which they call schema-based, benefit from things like mental models of the overall domain (e.g., pharma research) and cognitive strategies for working in that domain. The procedural information that guides those skills that are performed the same way from problem to problem.  This is the how-to knowledge (e.g., using the clinical trials database) that’s a routine part of the overall task. Part-task practice to strengthen and automate certain "recurrent constituent skills." Van Merriënboer and Kirschner argue that people can only perform certain constituent skills (which are aspects of the larger task, remember) if those people have a certain level of knowledge about the larger domain.  "Select an appropriate database," as they point out, doesn’t make any sense if you don’t know what makes databases appropriate to the search you’d like to perform. To foster integration and avoid compartmentalization, their model includes an emphasis on inductive learning: you as the learner work with specific problems so you build and improve mental models for the principles behind those specific problems. …all learning tasks [should] differ from each other on all dimensions that also differ in the real world, such as the context…in which the task is performed, the way in which the task is presented, the saliency of the defining characteristics, and so forth.  This allows the learners to abstract more general infromation from the details of each single task. That’s how we learn a great deal of what we know.  And, yes, a good deal of that happens informally, though I don’t see that as an argument for not trying to create learning situations when the informal can happen more predictably and more rapidly. Related to this idea, the authors advocate always having learners work with whole tasks.  That might mean starting with simple cases or examples.  Other approaches include providing support (say, a process overview for the clinical-trial system) and guidance (a job aid for forming database queries).  They also make use of task classes, by which they mean categories of tasks.  In their ongoing database-query example, one task class has to do with performing searches when the concepts are clear, the keywords are in a specific database, when the search involves few terms, and where the result includes only a limited number of articles. I’d call that the "clear, simple search" class. You can imagine the other extreme: a poorly phrased request involving unclear concepts, with little knowledge of the appropriate databases, calling for complex search queries and producing large numbers of relevant articles which require further analysis. How many task classes do you need?  That seems to depend on the range of variation between the Clear Simple Search class and the Nightmare Search class. There’s a lot more going on; without intending to, I guess I’m starting another series. The posts in this series: Complex learning, step by step (that's this post) Complex learning (coffee on the side)Ten little steps, and how One grew

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » Ten Steps to Complex Learning says that plans for such learning should always include the learning tasks, supportive information (for skills you apply differently from problem to problem), procedural information (for skills you apply the same way each time), and part-task practice for skills that demand a high level of automaticity. Components: how you put complex learning together The components work to integrate rather than compartmentalize skills, to coordinate the application of skills with associated knowledge and attitudes, and to differentiate between the methods that help people learn different kinds of tasks. In his comment on the previous post in this series, Dave Wilkins talked about call center workers who could either use the software well, or connect well with customers, but not both-because their training never integrated the two. That doesn’t mean you try to teach everything at once.  You can, and should, present realistic problems that start by presenting a simplified version of everything at once… a whole task with a great deal of scaffolding (as Van Merriënboer and Kirschner call it). "Whole task," to me, doesn’t mean the entire job (Amtrak ticket agent, trauma center nurse, Starbuck’s store manager).  It’s a flexible term, like "relatives,"  and it makes sense in context. Even if, like me, you’ve never worked at a Starbuck’s, you can imagine some high-level whole tasks for the store manager: Keep the store equipped and supplied. Keep the store staffed. Comply with company policies and procedures. Serve customers. Where to begin?  In one sense, it doesn’t matter. The Ten Steps model is systematic (there are inputs, processes, outputs; the outputs from one area become inputs to another) and systemic (activity in one part influences another). Manage learning so they learn to manage Here’s one way I see this in action: let’s say you begin with "keep the store staffed" tasks for that Starbuck’s manager-to-be.  Constituent tasks might include hiring, scheduling, training, and coaching. (You’ve already noticed that training and coaching have connections to that "serve customers" cluster of tasks, and probably to the "comply with policies and procedures" one, haven’t you?) I’m not going to do a whole store-manager analysis (unless Starbuck’s is dazzled by my insight); I’ve just chosen this as a complex learning problem. You can picture specifics in the "staff the store" area: identify staffing needs, recruit candidates, interview candidates, hire employees, train employees, schedule employees.  (Task analysis, by the way, is a prerequisite but lies outside the Ten Steps framework.  Can’t teach tasks if you don’t know what they are.) How do staffing problems vary? Simple learning problem with lots of scaffolding: "Carla is sick; she won’t be here at 2." "Okay, let me check her shift and see who’s off today."  Carla: 2 - 6.  Roster: Tomas, Junelle, and Van are off; Ben came in at 10 and leaves at 3; Paula comes in at 4. That could be the beginning of a full case study (on paper, in video, whatever) about which the learner would answer questions or make judgments.  You add richness by pointing out that Carla is a barista, but Paula hasn’t yet learned to make all the drinks-so Paula can’t fill in for Carla. A variation might include information about the skills of other people scheduled to work.  "Irene can make the drinks, and I’ll put Paula at the register." The most-difficult case is what vM&K call a conventional task: a situation and an outcome to reach, period.  Like, "The new store opens on the 15th.  Staff it." Example of supportive information: principles for asking (or telling) people to work overtime; guidance for offering extra hours.  You’d make these appropriate to what vM&K call the task class (a group of equivalent learning tasks with roughly the same level of difficulty).  You’d also present the supportive information ahead of time, because it interferes with on-the-job performance. By contract, procedural information is helpful when it’s just-in-time.  One definition of a job aid is "an on-the-job guide that tells you what to do and when to do it."  Imagine a scheduling tool that displays hours per day and per week for each employee, so the manager could see at a glance that Jeff’s got too many hours to be a substitute for the ailing Carla. As for part-task practice, you might want to strengthen the new manager’s ability to quickly and accurately track hours in the store’s scheduling and payrolls systems. That’s because applying rule-based procedures successfully strengthens the use of those procedures. (Please don’t mistake these speculations as actual advice for training managers of coffee shops.  They’re hypothetical examples—like metaphors, but you can charge more.) Meanwhile, back on the job… Van Merriënboer and Kirschner say that the fundamental problem of instructional design is the failure to transfer learning to job performance.  The Ten Steps approach tries to avoid that failure in several ways: Whole-task learning helps integrate skill, knowledge, and attitude, which means you’re more likely to connect a new situation to things you already know. A progression from easy to difficult tasks builds your ability to coordinate the various skills, knowledge, and attitudes in context.  In the olden days, we talked about "increasing approximations of on-the-job behavior." Combining rule-based information (for skills you perform the same way each time) and schema-based information (for skills you apply in different ways each time) has a double effect: Automaticity frees up cognitive resources.  You’re not analyzing individual letters or grammar structure as you read this post because your reading-text skills are automated. A mental model  (a schema) helps you interpret new situations in terms of the structures you already know. Another benefit of using a schema: you learn to monitor and adjust your own performance.  When I was trying to learn CSS, time and again I’d try one of the problems in Head First HMTL (which, in case I haven’t said so this month, is a fantastic example of complex learning in action) only to have my solution fail. But I’d made enough progress that I could study the problem and my code.  Eventually, I’d say "Ohh!" with a combination of insight and exasperation.  I saw what the mistake was, and I  connected the situation (what I wanted to do) with the solution. Next time, I promise, I’ll start talking about the ten steps.  Be warned, though: vM&K fibbed in the title. Though there are-theoretically-ten steps which could be followed in a specific order, in real-life instructional design projects, switches between those activities are common, yielding zigzag design behaviors. To compensate, you’ll get a bonus learning theory at no extra cost. CC-licensed "coffee learner" photo by Earl - What I Saw 2.0. CC-licensed "self-awareness" photo by jasoneppink. The posts in this series: Complex learning, step by stepComplex learning (coffee on the side) (that's this post) Ten little steps, and how One grewProblem solving, scaffolding, and varied practice

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » You’ve probably said to yourself, "Is obair-latha tòiseachadh." No?  Maybe you’ll agree that getting started is a day’s work.  Part of what I’ve worked on (or fretted about) the past few days was how to move from the overview chapters in Ten Steps to Complex Learning to those deal.ing with the actual steps. So here’s a chart I made, showing the four components for complex learning (boxes on the left), and the steps aligning with each component.  Remember, the application of the steps is not necessarily linear, but the diagram is, and the discussion will probably be. Whew.  On to Step 1… Admit it: sometimes you think it’s the content. Van Merriënboer and Kirschner claim, maybe a bit simplistically, that "traditional" instructional design starts with the subject matter and adds practice items.  The Ten Steps, in contrast, start with "whole-task practice tasks" which become the backbone for everything else. "Whole-task practice tasks" isn’t a felicitous phrase, but by now the idea is clear: meaningful tasks that look like a complete element within the overall complex job.  "Interview a job candidate" is a meaningful task; "ask open and closed questions," in my opinion, is not-it’s one of those constituent skills that make sense to the learner in the context of the whole task (interviewing). We’re talking about complex learning here.  In real life, it’s hard to figure out a complex problem; it’s hard to be sure the solution will work.  In fact, recognized experts will disagree about the best solution.  (How do you prevent traffic jams?  How do you unravel an existing jam?) Using real-life tasks as the basis for learning tasks…[confronts] learners with…the constituent skills that make up complex task performance….it [engages] the learners in activities that directly involve them with the constituent skills…as opposed to activities in which they have to study general information about or related to the skills. So the French were right:  en forgeant, on devient forgeron. By working at smithing, you become a blacksmith.  You sometimes see this translated as "practice makes perfect," but that’s not the case.  Practice can reinforce what you’re doing, but on its own doesn’t guarantee you’re doing the right things, let alone doing them right. vM&K advocate that the learning tasks you design put learning before performance.  By that they mean: have learners focus their attention on the cognitive processes for learning, rather than simply on performing the tasks. I think that may be one of the biggest challenges in this model.  We’re not accustomed to thinking about how we learn.  We’re not used to stepping back and watching ourselves as we perform.  This isn’t going to please the training-as-sheepdip crowd. For people who actually want to encourage complex learning, though, the fact that it’s not simple isn’t a deterrent.  They want to know ways to make whole-task learning effective- like by changing the environment in which they perform the tasks, and by providing support and guidance. Environments: getting real about simulation You can learn many complex skills in the real work environment.  But often, the on-the-job setting hinders learning.  You can’t provide the necessary support (no expert available; no place to put her; she has no time).  You can’t present the right task at the right time (because useful Problem X doesn’t occur predictably).  It’s expensive, inefficient, or dangerous for someone to learn on the job. Finally, the amount of detail in the real-life setting can overwhelm the novice. Thus, simulation.  And I’ll bet you’re thinking of high-tech machinery or immersive online environments.  Not bad, but not the only way to go.  vM&K argue that simulations can differ from real life in two important ways-physically (looks like the real job) and psychologically (feels like the real job).  And it’s the psychological fidelity that’s more important.  A setting with too much physical realism often provides "seductive detail" that distracts the learner. That explains why you hate those fatheaded computer simulations where you have to walk through doorways and press elevator buttons and open doors.  You already know how to do that stuff-what you want to know how to do is do a real-life complex task like manage a project or negotiate with a vendor. Support with the problem, guidance with the process To design effective learning tasks, you need not only the real-life problem with its situation and details, but also an acceptable solution and, ideally, the problem-solving process that generated the solution.  This means you’ve got a worked example (which provides the task support) and the process-related information (the guidance). vM&K give an example task: controlling air traffic.  Worked examples  might include radar and voice information about a particular problem situation (the "given"), similar information showing a safe resolution of the problem (the goal), and actions necessary to reach or maintain safety (the acceptable solutions). Guidance helps the learner approach the problem through useful approaches and heuristics-for example, strategies to help reach or maintain safe air traffic situations. Setting aside the process stuff for a bit, what you have is a kind of high-level recipe for learning tasks.  Each task has a given state, a goal, and one or more acceptable solutions.  Varying those elements gives you different types of tasks: A reverse task presents a goal and an acceptable solution.  The learner has to figure out the given.  (The images on your web page, which looked fine yesterday [example A], are messed up and look like this [example B].  How come?) An imitation task give you a case study (given, goal, solution) and a "conventional task" (given and goal); you work from the case study to solve the new problem.  (If you need to sell this to clients, it’s "case-based reasoning.") Tasks with non-specific goals push learners to explore the problem area-to move past solving the immediate problem and think about how problems get solved.  In vM&K’s ongoing research example, the learner receives a research question and a highly specific goal.  The task: come up with as many research queries as possible that could be relevant, and make those queries. Completion tasks provide the givens, criteria for a goal state, and partial solutions.  These require learners to study the partial solutions.  Completion tasks, the authors claim, are especially useful in design-oriented task areas. All these approaches encourage the learner to think about the problem, the solution, and useful steps.  That means they’re also abstracting like crazy, mining the solutions and using induction to build cognitive frameworks. For those complex, non-recurrent skills, this means more than lots of the same type of practice.  "The bottom line is that having students solve many problems on their own is often not the best thing for teaching them problem solving." Or: extra work doesn’t make you better at math; it just makes for extra work. Speaking of work, there’s enough of it in this post.  I’m not quite done with Step One, and so the next post in this series will touch on tools for problem solving, guidance, and induction. CC-licensed mockup of computer app by striatic. The posts in this series: Complex learning, step by stepComplex learning (coffee on the side)Ten little steps, and how One grew (that's this post) Problem solving, scaffolding, and varied practice

The quick-and-easy definition of a job aid is something you use on the job to tell you what to do and when to do it, so you don’t have to memorize the information. Job aids often struggle against what Tom Gilbert called the great cult of knowledge.  How many times have you heard performance dismissed with, "He had to look it up?"  A senior executive at Amtrak resisted the use of job aids for the reservation system because people "are supposed to know this stuff." Fortunately for the ticket and reservation agents, that view didn’t prevail.  For what was the new reservation, we produced 137 separate job aids.  One of those, for the "availability" command  (used to check schedules), hads seven optional parts and 288 possible ways to combine them. So the question’s not "how does a person learn this entry?"  It’s "how does a person do the job?"  Job aids offload some of the alleged learning (memorization) so people can accomplished useful results. Learning by doing Yes, some on-the-job performance should be virtually automatic.  If you’re an Amtrak reservation agent, you used the availability entry a lot-but not all 288 forms.  As you worked, you came to memorize five or ten combinations that suited the requests you handled most often. You relied on the job aid for the oddball requests.  Or you used the standard entry because you’d learned there are only two trains on the route in question, and they’d appear in response to any of the 288 combinations.  (This knowledge, by the way, is a heuristic.) So one of the functions of a job aid is to serve as training wheels.  Job aids guide the novice so that he produces results similar to those of an expert without having to internalize all the knowledge the expert has. Repeated successful use of the job aid is reinforcing on two levels.  First, you come to trust the job aid; later, you tend to incorporate the job aid’s guidance into your own repetory of skill.  You don’t need the job aid any more, because you’ve learned the task through on-the-job performance. What not to learn In some cases, though, the organization doesn’t want you to learn the task.  Usually, that means there are high consequences to incorrect performance. We really don’t want you making a mistake because you relied on your memory.  Another reason to avoid memorization: the task frequently changes.  Instead of trying to teach you the new way once a month, the organization wants you to rely on the job aid. Job aids used like this-think of an airline’s preflight checklist-are a kind of guard rail.  The job aid protects you from incorrect or unsafe performance.  (In addition, the organization needs to foster reliance on the job aid, in part to overcome the I-know-this-stuff attitude.) In the photo above, the bicylist has training wheels to help her learn the basics of riding.  The bridge she’s crossing is wide enough for people to cross without having to have railings-but the risk of someone falling is far greater than the cost of having those railings. The railings are like performance support built into the overall system.  Long ago at Amtrak, if someone wanted to travel from Detroit to San Diego, you had to know that the trip required a change of trains in Chicago and in Los Angeles.  The computer system couldn’t figure that for you.  So lots of training time went into "route structure." Today, while it’s helpful for an Amtrak agent to have a mental model of the routes, she can enter a request with just the origin and destination cities.  Route structure and sensible connections are now built into the reservation system.  If the passenger wants to go by way of San Francisco, the agent can modify the entry (possibly with the help of a job aid) to get the system to figure this alternate route. Guard rails, training wheels: they both help you get where you want to go. CC-licensed training wheel photo by Magalie L’Abbé.

Old men forget. Yet all shall be forgot But he’ll remember with advantages what feats he did this day. (Henry V, Act IV, scene 3) April 1st is my dad’s birthday (he turned 96 today).  When we were kids, we had lots of fun with the April Fool’s aspect.  My youngest brother, who had a more easygoing relationship with Dad than any of the older kids, used to pull elaborate pranks.  He once slit the glue from the bottom of a paper lunch bag, knowing that in his ready-for-work morning routine, Dad would take that bag and casually toss in his deviled-ham-on-homemade bread sandwich. Dad’s world has gotten much smaller in the past two years.  His hearing has deteriorated, his vision is much poorer, and his memory-well, it fades here, and it’s missing over there, and in this other place it stops and dwells for a while. He doesn’t have dementia, but I thought about him this weekend as I heard a radio program on Alzheimer’s, Memory, and Being.  I learned of a writing workshop for people in the early stages of Alzheimer’s.  Psychologist Alan Dienstag was urged by novelist Don DeLillo to encourage such people to write their stories while they could. Writing, DeLillo said, is a form of memory.  Through writing, people in the workshop changed how they saw what was left of their conscious lives.  Instead of losing their memories, they were giving them away. My dad’s always been a great teller of stories.  They’ve tapered off, but one or two still emerge, pieces of his life that he gives freely. Those of us who work in areas of training, learning, and communications have tools of vastly more power and reach than the kitchen tables of Nova Scotia and Detroit, Calgary and Boston, where Dad talked while downing vats of tea.  But that power’s not infinite. I’m glad that, even without realizing it, Dad’s given away so many of his memories, and I’m sorry not to have kept more of them than I have.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » In the Ten Steps to Complex Learning, I’m still working through Step 1: Design Learning Tasks.  The previous post focused on support related directly to the learning tasks: the givens, the goal, and the solution(s).  A central idea for van Merriënboer and Kirschner is the primacy of working with whole tasks; by varying these factors (e.g., having learners work with a partial solution), you can provide richer learning experiences. Complex skills are, in vM&K’s terms, non-recurrent: you apply the skills differently to new problems.  To do so effectively, you need to build cognitive strategies.  You’re creating for yourself mental models for grappling with problems in this field.  Step 1 gives three examples of such guidance: modeling, process worksheets, and performance constraints. Modeling: learning by example One common form of on-the-job learning is seelou training-"See Lou?  Do what Lou does." The intention is good; Lou is (theoretically) a skilled performer, and if you could do what Lou does, you’d be one too. As Ten Steps points out, modeling as a form of learning guidance is more complex.  You need a skilled professional to perform the task and also to explain or think out loud as she does. Becoming this kind of model, like becoming a mentor, isn’t something that happens because the boss dubs someone an expert. Successful modeling requires not only a skilled and credible role model, but explicit attention to to the process of solving problems. I think it’s critical to prepare that skilled performer, both in terms of highlighting whole tasks and in terms of focusing on the process. (You can, of course, use virtual models, such as a recorded performance or even, in theory, a simulation of an actual performance, though that’s easier to say than to do.) One form might be what’s often called shadowing-following the skilled performer through the workday.  Without the explicit focus on how the skilled person approaches problem-solving, though, shadowing isn’t likely to teach the novice performer any complex skills. Process worksheets: cookbooks for chefs Ten Steps describes a process worksheet as way of guiding learners through problem-solving.  Here’s an oversimplified example to guide a paralegal in writing an internal memorandum of law.  The left column lists the task steps; a right column deals with the processes involved. vM&K favor using questions when the process worksheet is a training tool: "learners are provoked to think about the rules-of-thumb." You could provide this type of guidance at a much more elaborate and detailed level.  vM&K refer to SAPs (systematic approaches to problem-solving), of which the process worksheet is an example, and note that some SAPs include branching so that the learner goes to different subparts for different types of problems. And you’re right, that looks a lot like a performance-support system.  One difference I see is that we’re talking about learning, whereas the performance support system is about… well, performance.  So it tends not to deal explicitly with the cognitive processes behind the performance. Rolling right along: performance constraints A third way to guide learners is by constraining what they can do.  Ten Steps calls this the training wheels approach.  When a child’s learning to ride a bicycle, there’s a lot of skill to focus on: pedaling, steering, maintaining balance.  Training wheels remove balance from the equation; they constrain the performance.  The authors believe that performance constraints are particularly useful for early phases in the learning process. There’s a certain amount of relativism here.  It’s like the rhetorical question, "How long is a rope?"  If the overarching skill is riding a bicycle, what constitutes a whole task?  "Moving the bike along a path" might be one; the kid’s still moving along even when the bike has training wheels attached.  Removing the wheels creates a whole task (moving) with less support (moving and balance on your own). Which makes a good link to the final point in Step 1: scaffolding Scaffolding: support that fades "Scaffolding" is a technique that combines providing support to the learner (like modeling, process worksheets, examples) with gradually reducing or fading that support until the learner faces what vM&K call a conventional task ("here’s the problem; solve it"). Research on expertise reversal indicated that highly effective instructional methods for novice learners can lose their effectiveness and even have negative effected when used with more experienced learners…. There is overwhelming evidence that conventional tasks [meaning, those with no support] force novice learners to use weak problem-solving methods that bear little relation to schema-construction processes… Or: if you just have novices work at solving complex problems but don’t provide them support while they’re learning, they won’t know what they’re doing, and they won’t learn how to do better-at least not in any efficient way.  I think this explains why so much alleged on-the-job training does so poorly with complex skills: novices focus on externals, on what looks important (or on what Lou thinks is important). A corollary is that when someone’s already skilled, the support and guidance can actually hinder his performance.  The skilled performer has built her own mental models, and they work (or else she wouldn’t be skilled).  When you start providing other models to skilled performers, you’re struggling against what’s already there. And you’re probably losing. Scaffolding (support that gradually faces as you move through the training program) is a tool to replace external guidance with self guidance. Variation: the road from concrete to abstract vM&K talk about "variability of practice," though I think "variation" is a better word (not that they asked).  I’ve discussed this in earlier posts; mentioning it again stresses the emphasis that Ten Steps puts on inductive learning. Students construct general cognitive schemas of how to approach problems in the domain, and of how the domain is organized, based on their concrete experiences offered by the tasks. Variation in the tasks makes for richer learning experiences, which in turn makes for stronger schemas.  Generalization and discrimination are obvious ways that people build their cognitive maps.  So is mindful abstraction, deliberate efforts to generate alternative concepts or solutions. New to me was the concept of implicit learning.  Some tasks lack straightforward decision guides but have a lot of information.  Giving learners a wide range of positive and negative examples can help them derive useful schemas.  The situation that vM&K talk about involves showing air traffic controllers thousands of examples of control situations-some dangerous, some safe. A final recommendation: learning tasks adjacent to each other should have learners practice different versions of the constituent skills.  The higher "contextual interference" will actually help learners solve new problems better. Let’s say you’re working on effective writing.  Imagine three elements like using parallel structure, using personal pronouns, and avoiding passive verbs.  Low interference would come from a cluster of problems, each of which involves parallelism in email, followed by another cluster involving personal pronouns in email.  Eventually you get to a second batch: parallelism in reports, personal pronouns in reports, and so on. Higher interference would come from practice tasks that interspersing both the elements and the situation: parallelism in an email, then passive voice in a report, then personal pronouns in the comments section of a form. Since vM&K end the chapter with a warning, I’ll repeat its essence here: Novices don’t learn well from conventional tasks ("here’s the problem, what’s the answer?"). A randomized set of conventional tasks is even worse. High variability with ample support and guidance helps novices learn. High interference (how the variability is presented) also helps them learn. So, for novices learning complex skills: without support, your learning won’t hold up. CC-licensed dubbing photo by The Other Dan CC-licensed "I know this already" photo by orionoir. 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 practice (that's this post) Step 2: sequencing tasks, or, what next?Clusters, chains, and part-task sequencing

One more chore when I’m galactic emperor:  suburban office buildings-you know the kind, with medical group practices  and title companies and other purveyors of services-would have to have visible house numbers. Visible as in, you can read them from a moving car on the opposite side of the street.  Before you pass the building. I’m opposed to capital punishment, so if you violated this edict, I’d handcuff you to a desk for a month. The desk would be inside It’s a Small World. This is really a rant (or a lament) on the gulf between theory and practice when it comes to how "services" deal on a practical basis with those they serve.  I was designated driver for someone who had to go to one of those stone-and-glass Skinner boxes.  I found myself thinking that some stakeholders-the designers, the builders, the landlords, or the tenants-have never visited the place as customers. Four floors of imaging centers, gastroenterology practices, OB/GYN partnerships, and so on-thus, likely attracting the ill, the concerned, and those concerned for them-and yet… One "house number", about eight feet off the ground, and about the size of the number on my own house.  You can barely see it from the curb, let alone the road.  Nearby: eight or ten other interchangeable buildings, all members of  "Who Needs Addresses?" Nothing to distinguish one side of the building from another; until you try the doors, you don’t realize that the east and west entrances are to individual businesses, not to the building lobby. Not a single public-area bench or seat, meaning that patients waiting near the door for rides have to stand. Something of the same lack of awareness at the office-level: practice’s receptionists did not greet patients so much as shove paperwork on clipboards at them.  Overheard phone call: "This is Dr. Whoozi’s office.  The doctor needs to have you come in 30 minutes early." I was reminded of a customer-service job aid I saw taped to the staff side of a cash register at a Wisconsin doughnut shop: Look at me. Listen to me. Smile at me. Thank me. An open invitation: Last month’s edition of the Working/Learning blog carnival was the largest and most-read yet.  Host for the next one (April 20th) is Dave Wilkins at The Social Learner. If you blog about anything that relates to how people work at learning, or how learning happens at work, I hope you’ll consider taking part.  Then let Dave know.  (Details on how to participate are here.) CC-licensed to-do photo by Great Beyond.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » Step 2 in Ten Steps to Complex Learning is "sequence task classes."  (The image on the right shows that this step is part of the "learning tasks" component in van Merriënboer and Kirschner’s model; click to enlarge.) You may recall that task classes (which vM&K say are also known as equivalence classes, problem sets, or case types) are categories of whole-task problems ("learning tasks") with the same degree of difficulty. A very short training program might have only one task class, though I’m having trouble picturing complex learning that you could accomplish that way.  Maybe specialized training for skilled people to increase their ability in a new but related area, like training computer technicians to troubleshoot a new type of equipment. This chapter of the book deals with sequencing task classes, learner support in task classes, and (gasp) part-task sequencing. The whole is more than the sum of the tasks The Ten Steps strongly advocate a whole-task approach to sequencing….on the premise that learners should quickly acquire a complete view of the whole skill that is gradually embellished during training.  Ideally, even the first task class refers to the easiest version of whole tasks that professionals encounter in the real world…. This provides learners the best opportunities to pay attention to the integration of all skills, knowledge, and attitudes involved, and to the necessary coordination of constituent skills. vM&K mention "global before local skills," a principle of cognitive apprenticeship, as well as Reigeluth’s metaphor of a zoom lens.  The idea is that you begin with the wide-angle view (the whole task), zoom in for detail (an early task class), zoom out again to see the part in relation to the whole, zoom in on other details, and so on. Sequencing through simplification One way to sequence task classes is to simplify conditions.  The learner works with all the constituent skills, starting with the easiest version of the whole task that professionals might encounter. Let’s say the whole task is for an Amtrak reservation agent to answer customer questions about schedules.  (As the subject-matter expert here, I’m deciding "schedule questions" is one task class and "fare questions" is another.)  Factors affecting the difficulty of the whole task might be the complexity of the route, the firmness of the dates, the available accommodations, and the number of trains satisfying the request. Those factors or dimensions act as a kind of recipe for building task classes.  In the easiest class, for example, the learner works with schedule requests where the routes aren’t complex, the dates are firm, there are few accommodation options, and there aren’t many trains to choose from. "Can I go from Memphis to Chicago next Friday?"  (There’s one train per day; no connection required; either a seat or a roomette.) In a complex-request class, you might get a request like: "I’m thinking of taking my husband and our grandson from Cleveland to Portland, Oregon, some time this summer.  I wonder if we can visit my sister in Denver and also get to see Glacier National Park?"  (Lots of routes, many possible accommodations, complex scheduling.) Sequencing through "emphasis manipulation" Another way to sequence task classes is to focus on different sets of the constituent skills in different classes. How’s that different from just teaching parts of the overall task?  Because although you’re shifting (or "manipulating") the emphasis between various constituent skills, you’re still working on the whole task. vM&K give an example of student teachers learning to teach lessons ("teaching a lesson" being the whole task in this example, no matter what you think teachers ought to be doing or not doing). A first task class might emphasize presenting the subject matter.  The next task class might involve teaching with an emphasis on questioning; another class, teaching with a focus on initiating and encouraging group discussion.  The final class would involve teaching (the whole task), with the idea that the student teachers integrate the skills of presentation, questioning, and discussion. Training for a supervisor in a pharmaceutical plant might have a whole task for preparing an employee to operate the cartoning machine.  One task class might emphasize safety; another, standard operation; a third, troubleshooting; a fourth, changeover for different products; a fifth, different levels of cleaning and maintenance. One drawback to "emphasis manipulation" is that it presents the learner with complex situations from the beginning.  Remember, you’re not simplifying the situation, only emphasizing certain constituent skills in the context of the whole.  This approach probably isn’t a good one for the early task classes of a highly complex task. Sequencing through knowledge progression A third way to build task classes is via the underlying body of knowledge.  If that sounds confusing to you, I’m glad to have the company. More seriously, vM&K suggest thinking about this as first determining the bodies of knowledge needed, and using those to determine task classes.  In other words: Analyze any progressions of cognitive strategies (approaches to problems), and Analyze any progressions of mental models (pictures of how the domain is organized). Those are Steps 5 and 6 in the model, which means I haven’t read those chapters yet.  We’ll get there. In the meantime, you can, of course, combine the types of sequencing.  You’ll likely use simplification first because it’s…less complex than emphasis manipulation. Speaking of simplicity and complexity, we’ve still got a straightforward topic (learner support) and a confusing one (part-task sequencing) to deal with in Step 2.  We’ll knock off the easy stuff and save the hard part for next time. Support as sawtooth You’ve probably figured already that scaffolding (diminishing support and guidance) applies within a task class.  So if your learning involves four task classes, you’ve got four sequences of scaffolding, each with high support and guidance in early examples, fading to none by the end of the class. For the task class "simple Amtrak schedule requests," a first learning task might involve a mini case study of someone handling a simple request.  The learner would explain what happened to make the response effective. The next learning task removes some scaffolding-for instance, giving a partial response, for which the learner must provide the missing pieces. As a last learning task in the "simple schedule" class, the learner would work what vM&K call a conventional task — given a passenger request, reach the goal. * * * The last part of this chapter deals with "part-task sequencing of learning tasks."  It’s complicated enough that (a) it would make this post too long and (b) I don’t yet know how to explain it.  That’s reason enough to leave it till next time. CC-licensed simplified camera photo by John Kratz. CC-licensed lens photo by Anders Ljungberg. My sawtooth image adapted from a CC-licensed leaf-edge photo by P/\UL. 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? (that's this post) Clusters, chains, and part-task sequencingStep 3: performance objectives (the how of the what)

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » (Note: this is a continuation of the previous post in this series. Together they deal with Step 2, sequencing the task classes.) Clusters, chains, and parts "In exceptional cases," van Merriënboer and Kirschner say in Step 2 of Ten Steps to Complex Learning, "it might not be possible to find a task class easy enough to start the training with."  They’re thinking of very complex training-like, say, complete programs for doctors or pilots. "If you are not dealing with such an exceptional case, you may skip this section." Thanks, guys. I’m extending this discussion of Step 2  ( "sequence the task classes" ) because, while vM&K say part-task sequencing is an exception to usual practice, I’ve used some of the techniques in less-than-complex situations. Parts: on the whole, they’re incomplete "Part-task sequencing" has a special meaning in the Ten Steps approach.  It refers to how you decide which clusters of constituent skills to deal with, in which order, because you see the overall skill-the whole task-as too complex to confront a learner with. A cluster is a group of interrelated constituent skills that make up an authentic real-life task, even if it’s not the complete task.  If you think of "diagnosing a patient" as the whole task, one cluster might involve conducting physical exams while another might involve reviewing test results and reports from exams done by others.  Each cluster makes sense on its own (it’s something a physician would do in the real world); each is a part of the whole task of diagnosis. I’m feeling a little sympathy for vM&K.  There’s lots of terminology like "task" that can apply at different levels.  The authors end up with lots of phrases like "whole task" and "part-task sequencing."  I suppose  the alternative is to try nailing a term to a particular level.  Good luck. One advantage to clusters is that they reduce difficulty: the learner has fewer things to attend to.  The tradeoff is that the clusters hinder integration (since you’re leaving out some of the skills) and limit opportunities to coordinate the skills. In a sense, that coordination is headquarters for "the whole is more than the sum of the parts."  The complex task is not simply what you get when you add up its constituent skills; you also have to retrieve and deploy combinations of those skills-coordinate them-on the job. Linking the tasks Imagine the job of a first-level supervisor.  For the sake of example, we’ll look at the managerial parts of the job (as opposed to industry-specific ones).  As a supervisor/manager/leader, you’ve got whole tasks like: Maintain a skilled team (e.g., make sure people have or acquire necessary skills; make sure they get to develop them) Manage the performance of your team Assess the performance of your team (monitor, provide feedback, conduct performance reviews) You might choose different clusters, and so might I.  You’ll likely agree that each of the three bullets at least implies a related group of skills, and that each cluster might itself be so complex as to need additional breaking down.  Concentrating on one of these clusters at a time, and training within that cluster, is what part-task sequencing means. And, yes, you’ll still have to integrate the clusters eventually.  Yes, that’s going to take time and cost money.  Complexity is complex. In forward chaining, you address the constituent skills in a logical order, typically the way they’re performed.  Take the task of "managing the performance of your team."  In forward chaining, you might work through these constituent skills: Communicate requirements and standards Monitor individual performance Discuss performance with individual Document results of discussion Backward chaining works in the opposite direction; you’d train tasks in this order: Document results of discussion Discuss performance with individual Monitor individual performance Communicate requirements and standards With either method, you can use snowballing.  You combine each subsequent task with what’s been taught before.  The forward version would have task classes like these: "Communicate" tasks "Communicate and monitor" tasks "Communicate, monitor, and discuss" tasks "Communicate, monitor, discuss, and document" tasks Van Merriënboer and Kirshner believe the most effective combination is backward chaining with snowballing.  Since you start near the completion of the task, you need to provide the learner with outcomes from earlier stages not yet covered: "Document" tasks (given: the outcome of "communicate, monitor, and discuss") "Discuss and document" given: the outcome of "communicate and monitor") "Monitor, discuss, and document" tasks (given: the outcome of "communicate") "Communicate, monitor, discuss, and document" tasks This last approach, they argue, should be the default mode for part-task sequencing, which in turn is an exception reserved for only highly complex whole tasks.  As for the other combinations: Backward chaining without snowballing is what you do when you lack time for including snowballing. Forward chaining with snowballing is only for part-task practice Forward chaining without snowballing is for part-task practice when you lack time. "Part-task practice" is another specialized term; it’s Step 10 of the Ten Steps, and it’s meant to develop automaticity for recurrent tasks.  That means the procedural stuff you do the same way each time.  It’s how you learned your times tables; it’s how you practice scales on the cello. Two more combinations Earlier we talked about whole-task sequencing: each task class presents the whole task, with the early task classes providing simple examples and the late ones providing complex examples.  This post looked at part-task sequencing, something you do when the whole task is too complex for a learner to tackle.  So, naturally, Whole-task sequencing and part-task sequencing may be combined in two ways, namely whole-part sequencing and part-whole sequencing. See why I broke Step 2 into two posts? It’s not as bad as it sounds-if I understand vM&K.  Here’s what I think they’re talking about.  Remember that constituent task for the supervisor, "Manage performance of your team?’  Its four skills (communicate, monitor, discuss, document) might apply in two contexts: coaching someone to improve current performance, and counseling someone to correct a deficiency.  Or "how to do even better" versus "you need to do better.") Here’s how I think that works on a whole-task class for the "manage performance" skill.  This class is made up of relatively simple, straightforward situations.  Individual task problems may involve coaching or may involve counseling. First skill cluster: documenting skill. Learning via backward chaining and snowballing, the supervisor is asked to document various simple counseling and coaching situations.   (The givens include the outcomes of communicating, monitoring, and discussing.) Second cluster:  the supervisor would now works on problems that involve discussing with an performance employee, then documenting the discussion. (Gives: communicating and monitoring.)  Again, some are coaching situations, some are counseling. And so on.  This is whole-part because the class involves the whole task ("managing performance"); within the class, we sequence by parts of the performance. vM&K say you could also have part-whole sequencing.  I take that to mean, in terms of this example, that you have a class where you document easy cases, then medium ones, then difficult ones, and then move on to a class where you discuss and document, and so on. Since their clear preference is for whole-part (if you have to have part-task sequencing), and since they didn’t provide any examples of their own, I’m going to tiptoe away from Step 2. Next in the series: Step 3, Setting Performance Objectives. CC-licensed image of Vasarely works by notalike. 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 sequencing (that's this post) Step 3: performance objectives (the how of the what)Criteria for objectives-also, values and attitudes

Another one of those multi-link paths today.  I had conversation with Ruth Seeley of No Spin PR, which led me to follow her blogroll to Fiona Walsh’s blog, where Walsh suggested a Marshall Goldsmith post on asking one tough question. That question, asked of people too busy to implement changes they said they wanted to make, was "What am I willing to change now?" I get uneasy around some coaches (and not just the ones in sports), so I was all the more surprised to read Goldsmith saying "do what you can do now…and make peace with what is." Each of those statements linked to yet other posts, so this was like three links out with a bonus.  I’ve been a bit frazzled lately, so it was good to be reminded of these things. My most recent project really energized me.  I got to work with a skilled expert who’s been thinking about how to increase the skills of new people coming into his field.  He doesn’t think he has all the questions, much less all the answers.  I hadn’t had that direct contact in a while, nor such a free-flowing exchange. So part of the "do what you can do" message is getting clear on what I’d like to be doing, or doing more of.   Stewart Friedman’s advice include being real (which I read as "true to yourself"), be whole, and be innovative. As for the being at peace, the second link cited by Goldman, Annie McKee is writing about dealing with pressure and building things into your life to spark both psychological and physical renewal: Listen to life’s quiet wake-up calls.  Maybe they’re just the small sound life is making in another room.  What’s happening (or not happening) while you want for Something to Happen? Practice mindfulness.  This one’s hard for me.  I sometimes fell like Bill Blazejowski in Night Shift ("What if you mix the mayonnaise in the can, with the tuna fish? Or… hold it! Chuck! I got it! Take live tuna fish, and feed ‘em mayonnaise! Oh, this is great.")  I have to work at building this, the way you have to work at building muscle strength. Find hope. The motto of Detroit is Speramus meliora-"we hope for better things." Hope is a vote for the future. Practice compassion. This isn’t a virtue widely prized in competitive culture, but it’s one I value. This was a good shift between reports I’m working on and books I’ve been reading.

Twitter’s a stream, not a bookshelf.  Comments, ideas, and links flow past.  You can’t follow up on each one.  I have, however, come up with a homemade version of a clipping service. A couple of times a day, I skim tweets and click on promising links.  Each link opens a new tab in Firefox.  Usually I end up with six or eight tabs, ideal for quick browsing. Skimming, round two, involves those tabs.  I’ll start reading the link and do a kind of cognitive triage: close; read and close; read, tag (in Delicious), and close. One such tweet led to an article on usability principles in social networking, posted by Verne Ho at creative briefing. Ho’s main topic is putting usability ideas to work specifically on social network sites. Social networks differ from regular websites in 3 fundamental ways: Activities and content are fully (or at least mostly) driven by the users.  Users are expected to do things on the website — interact, post, vote, etc. Users are expected to come back to the website periodically and continue to do things. At least the first two points apply to learning: it’s the learner who does it, not the facilitator, designer, or the chief learning officer.  And for learning to happen, learners have to do stuff. That’s a bit of a tangent, and Ho’s points are worthwhile in their own right.  I like how he handled some possibilities: "…Basic usability principles…dictated righter from wronger (sometimes there was no strictly right or wrong answer)." A quick rundown of some of his principles: Show only relevant information. Emphasize important actions. Provide visual feedback…(and make wait times feel shorter). Use the five-second text. That test: "ask people to list what they can recall after viewing your site for five seconds."  Not a bad principle to apply to, say, visuals in a presentation.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » In Ten Steps to Complex Learning, van Merriënboer and Kirschner’s third step is set performance objectives.  (Click for a diagram of all ten steps and the four components into which they fit.)  The main sections of the chapter are: Skill decomposition (or, academic language rides again)-figuring out the constituent skills of the whole task Creating performance objectives Classifying performance objectives Performance assessment The authors emphasize one point so often, I’m putting it first: Many instruction design models use performance objectives…as the main input for the design decisions to be made….Instructional methods are selected for each objective, and each objective has its corresponding test item(s)…. This is certainly not true for the Ten Steps.  In complex learning, it is precisely the inegration and coordination of constituent skills described by the performance objectives that must be supported by the training program. In other words, you can’t tie your instructional methods to a specific objective; you have to connect with interrelated sets of objectives. I’m willing to ride at least part of the way with vM&K, even though there’s some risk of semantics here.  The subject is complex learning, not how to set up a Facebook page.  Many criticisms of traditional instructional design and of formal learning result from the failure of training interventions to address the whole of a complex skill. That said, much traditional organizational learning has glossed over the reality that complex things are complex.  For every death-by-PowerPoint three-day workshop, there’s a senior executive somewhere who believes that talking is teaching.  He doesn’t want "paralysis by analysis," though his fervent belief in Best Practices (especially if they come from outside his organization) is often a case of faith without good works. Skill decomposition, or, what does it take? The Ten Steps assumes you’re doing a needs analysis (and if you’re not, how the hell do you know what you should be doing?).   Two additional assumptions follow: …There actually is a performance problem that can be solved by training …[and an] overall learning goal…a statement of what the learners will be able to do after they have completed the training program. Since the Ten Steps is iterative, the goal helps you break down the complex skill, and the constituent parts of the skill help you refine the overall goal.  As you identify the learning tasks (Step 1) and sequence them (Step 2), you’re uncovering information about the relationship of the constituent skills. The top-level goal can be elaborate, like their example for patent examiners: After having followed the training program, the learners will be able to decide upon the granting of patent applications by: Analyzing the application Searching for relevant prior documents Conducting a substantive examination Delivering a search report where the relevant documents that have been found are cited and their relevancy is acknowledge on the basis of the substantive examination, and Communicating the result of the substantive examination to either The examining division so that a patent can be granted immediately, or The applicant so that, at a later stage, a reply can be filed by the applicant and a patent granted, or the application is refused. vM&K list several approaches to filling out the set of constituent skills.  A hierarchy is an obvious approach: what specific skills are necessary in order to perform the more general skill?  In my earlier example of supervisor skills, "monitoring individual performance" is a prerequisite for the overall skill of "managing performance." If you want to know whether to expand the skills on the same (horizontal) level, there are temporal relationships (skill A must be performed before skill B), simultaneous ones (you perform C and D at the same time, like shifting gears and steering the car through a turn), and transposable ones (perform skills E and F in any order). I’m not sure why this amount of detail appears here.  My guess (and that’s all it is) is that the relationship information will come into play with the cognitive strategies and rules. The chapter mentions heterarchical (peer-to-peer) relationships between skills on the same level, and also what vM&K call reitiary but others seem to call retiary relationships-networks of skill or "competence maps." The thumbnail on the right links to a competence map for cognitive behavioral therapy, a form of psychotherapy, though the elements on the map aren’t interconnected. Data: gaining as you gather Analyzing the skills helps highlight which are similar.  Similarity may facilitate learning or may impede it (when "similar" means "with tiny but important differences").  vM&K recommend observing skilled performers as they work first on simple whole tasks, and then on more complex ones. So, no, you don’t sit down and just have the subject-matter expert tell you about things.  As Tom Gilbert often noted, to figure out her tennis skills, you have to watch Martina Navratilova’s feet. Martina has lots to say that’s useful, but the whole skill is serving, not just foot-placement or racquet-holding. And the expert performer is often unaware of how she applies complexes of skills. This chapter offers suggestions for gathering data.  The authors refer to objects-things that the performer focuses on or changes.  A shift from one object to another suggests a shift in constituent skill.  If the supervisor checks the project schedule and then a worker’s weekly report, the shift might be from "determining individual’s goals" to "tracking individual’s progress." Another source of data: the tools the performer uses.  The chapter gives an example of a patent examiner switches from a highlighter to a search engine to a word processor as he works on a report.  Possible constituent skills are "analyzing applications" (the highlighter), "performing searches" (the search engine), and "writing results of pre-examination" (the word processor). In addition to working with skilled professionals who demonstrate the desired performance, there’s value in working with deficient performers as well.  The gap between optimals and actuals (as Allison Rossett phrased it) helps target performance-improvement efforts. The (A)BCDs of building performance objectives Van Merriënboer and Kirschner see four elements to a performance objective: the action, the tools and objects, the conditions, and the standards. Not that difference from ABCD objectives (actor, behavior, condition, and degree).  True, they left out "actor," but I’d say it’s pretty obvious. The action verb part is what you’d expect.  No "understand," "know," or "be aware of" allowed. You specify the tools and objects for several reasons.  One, if they’re used on the job, they’re part of the task, and learners need to learn them.  (In designing training, naturally, you might come up with simple or low-fidelity versions of some of the tools or objects, especially for the early stages.)  In addition, if some of these items change often, you’re forewarned; you know that the training may have to change as well. Conditions play a major part in complex learning-think of the military surgeon who must perform not only in a well-equipped hospital but also in suboptimal conditions closer to the front. In the Ten Steps approach, the final element, standards, involves not only criteria, but also values and attitudes.  That’s where the next post in the series will begin. Martina Navratilova image adapted from a CC-licensed photo by Chip_2904. 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) (that's this post) Criteria for objectives-also, values and attitudes

Series: Ten Steps to Complex Learning « Previous post in this series • Note: this is a continuation of the previous post in this series, because I can’t seem to summarize and comment on one of the Ten Steps to Complex Learning in a single post.) Step 3 is "set performance objectives."  As the introduction and first section of this chapter emphasize, this is an iterative process, not a linear one.  The real-life tasks in which you perform the complex skill help to determine the overall learning goals and the specific tasks that will help achieve them. In turn, these help refine understanding of the complex skill and the constituent skills that it embodies. After analyzing (or "decomposing") the skills, you create performance objectives.  I’ve discussed Van Merriënboer and Kirscher’s actions and the tools and conditions that apply to the objectives.  It’s a bit tough to talk about standards as they describe them. Keeping to the standards The Ten Steps sees standards as having four elements: criteria, values, and attitudes.  Criteria means what you think: minimum requirements for things like accuracy, speed, quality, and so forth. Values indicate that the constituent skill conforms to some set of rules or regulations.  Two examples vM&K offer: "without violating traffic rules" and "taking the ICAO safety regulations into account." My feelings are mixed.  I can see the value of this as shorthand ("wiring for this remodeling must meet the National Electrical Code").  Is there a little game of gotcha on the side?  Or are we acknowledging that in complex learning, there are areas of performance that matter, even if we’re not going to provide instruction related to them? I really can’t say; this just feels a bit like a junk drawer in the conceptual cabinet of the Ten Steps. Feelings about attitudes If values are the junk drawer of instructional design, attitudes are like scribbling "Get organized!" on a to-do list.  The Ten Steps doesn’t define "attitudes," but says they’re "subordinate to, but fully integrated with" constituent skills. Apparently we’ll know them when we see them.  However, they won’t be things like "have a client-centered attitude."  vM&K say this is a non-example: a research librarian doesn’t need to have such an attitude outside of work, nor does he need to have it when doing tasks that don’t involve clients. So, whatever an attitude is, it’s not an enduring part of your personality.  I actually think there is such a thing as attitude; I just don’t think  you can influence it directly very well.  The Ten Steps seems to agree: It is only necessary to specify the attitude in the performance objective for these relevant constituent skills. If possible, all observable behaviors that indicate or demonstrate the attitude should be formulated or specified in a way that they are observable!  The standard "with a smile on your face" is more concrete, and thus more observable, than "friendly;" "regularly performing checks" is more concrete…than "punctual…" "With a smile on your face?" This is an unsatisfactory nod toward a complex issue.  Think of medical professionals interacting with patients (so-called bedside manner).  Can it be that helping a surgeon demonstrate interest in the person and not just the condition-"Dr. Manoogian, your gall bladder’s in room 5″-might require this close a focus? Classifying Objectives Three dimensions apply to the objectives you develop (remember, these are objectives for the constituent skills that make up the overall complex skill): Teach, or not? Non-recurrent, or recurrent? Make automatic, or not? The easy part is sorting out the objectives you’re not going to include in your training-either because the typical performer already has these skills, or because the objectives are covered elsewhere.  Those that remain fall into four groups. Non-recurrent skills, you’ll recall, are applied differently to different problem situations.  They involve schema-based problem solving and reasoning.  They require supporting information like cognitive maps during the training, which is the topic for Step 4. Recurrent skills are those you apply the same way to different problem situations.  They’re the rule-based skills.  In training, these require procedurall information. vM&K state that any prerequisite skills for a recurrent skill are by definition recurrent.  "A recurrent constituent skill," they says, " can never have non-recurrent aspects!"  Since they say with with both italics and the second exclamation point in two pages, they must mean it. The same skill, they go on, could be non-recurrent in one training program, but recurrent in another.  Repair of military aircraft in peacetime might be a non-recurrent skill, because there’s time for diagnosis.  In wartime, one of the criteria is to repair or replace as quickly as possible, which could mean that repair becomes a more procedure-driven and thus recurrent task. Some recurrent skills require a high level of automaticity.  This involves the part-task practice discussed in Step 10.  Some jobs don’t require this type of automaticity (for example, the recurrent patent-examiner task).  Factors that suggest automaticity include: Enabling other skills higher in the hierarchy. Musicians practice scales, even after achieving a high level of skill, in order to automate basic skills and enable more fluid performance of higher skill. Simultaneous performance with many other skills. Process operators in manufacturing and air-traffic controllers are two types of jobs where the individual reads displays automatically as she analyzes and responds to dynamic sistuations. High risk in terms of cost, damage to equipment, or danger to life. Pilots and flight attendants practice emergency procedures. Ten Steps makes a point that not all routine skills need automation.  There’s a cost/benefit consideration — you don’t memorize all the addition possibilities of two numbers from 0 to 999; you do (eventually) automate the skill needed to keep a car moving in a straight line. Twofers "Rare situations" exist, according to vM&K, when you’d choose to automate a non-recurrent skill.  They use "double classified" for what seems to be combinations of recurrent and non-recurrent skills, like their example of shutting down a power plant in an emergency. The shutdown can occur in many ways, depending on circumstances (non-recurrent), but must follow specific procedures (recurrent).  This is an expensive decision and often requires high-fidelity simulation.  In addition, the authors say that learners should be explicitly told that they’ll switch from automated mode to problem-solving mode at times. The things you left out Remember that "category" of objectives that you won’t be teaching? If learners have already mastered a particular constituent skill in an isolated manner, this is no guarantee that they can carry it out in the context of whole-task performance.  Performing a particular constituent skill in isolation is completely different from performing it in the context of a whole task, and automaticity of a constituent skill that has been developed through extensive aprt-task practice is often not preserved in the context of whole-task performance. Which is to say that when Bruno gets a perfect score on the loan-application system, it doesn’t necessarily mean he can use it while interviewing a live loan applicant at the bank branch. Objectives and assessment It’s pretty obvious that clear, observable objectives relating to clusters of constituent skills that make up the complex skill have many benefits.  You can develop tools to help learners do self-assessment.  You can provide support for a peer, who can help identify areas of improvement (and whose own performance can benefit from helping the other person). IN assessment, values and attitudes are usually measured narratively, or through qualitative scales (very poor, poor, acceptable, good, excellent). vM&K acknowledge the potential burden of a highly-detailed assessment, which is virtually a necessity for complex sills.  They recommend self-assessment and peer assessment.  They also suggest a development portfolio, a collection of assessments for all learning tasks. This details what the learner’s done and how well he’s doen.  He can choose his next learning tasks based on this information. In the next post, we’ll (finally) move from the learning task component to the supportive information component.  The corresponding steps are designing supporting information (Step 4), analyzing cognitive strategies (Step 5), and analyzing mental models (Step 6). 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 attitudes (that's this post)

1066 and All That states (sensibly, I think) that history is what you remember.  More than that; at least for me, history is how you respond to what you remember-and perhaps what those responses lead you to. You can turn inward, recalling only the good things and staying inside the value equivalent of a walled garden, or you can move outward, using what you know to help figure out other things. I’m descended from Highlanders.  I remember my father talking to our upstairs neighbor in Detroit, who was (of course) also from Cape Breton.  Frank said to my dad, "Wouldn’t it be great, Hughie, if we could go back to Scotland?" I don’t think anyone in Frank Gillis’s family had been within a thousand miles of Scotland for two hundred years, except perhaps during two world wars-but this was Frank’s attitude (and my dad’s).  Scotland for them was like Paris for Hemingway: a moveable feast, only with more MacDougals. I treasure this connection to a small place, though not as a Celtic Disneyland frozen in time.  I know a little of how my ancestors came to Canada, and then my parents to the States.  That knowledge, I think, helps me connect a little with the origins, the journeys, and the memories held by others. I don’t see Bonnie Prince Charlie as a noble hero, but today’s the anniversary of the last battle on the island of Britain.  Jacobite forces under Prince Charlie were crushed by the army of the Duke of Cumberland, son of King George II, on April 16, 1746.  The site is known by two names: Drumossie and Culloden. So here’s Deanta with Mary Dillon, singing Alastair McDonald’s Culloden’s Harvest.

There’s an image on the Citizenship and Immigration Canada website: An amendment to the Citizenship Act went into effect today.  I took the quiz that the image links to, even though I knew how it would turn out: Have you ever renounced your Canadian citizenship?   Nope. Was your Canadian citizenship ever revoked for fraud?   No. Where were you born? The Inverness hospital-oh, "in Canada." When were you born? (In my case, the right answer is: "Between January 1st, 1947, and February 14, 1977.") At the time of your birth, were your parents foreign diplomats in Canada?   No (unless under really deep cover). So I passed. Under the new law, "Citizenship will be automatic and retroactive to the day the person was born or lost citizenship, depending on the situation."  So I’ve zipped back to 1958 when my parents became naturalized U.S. citizens.  At the time, I gained U.S. citizenship through them and automatically lost my Canadian citizenship. Oh, there it is.  And retroactive, too, so I’ve been Canadian all along.  (You had doubts?)  I read once that Stephen Hawking claimed time travel would never be possible.  He offered as proof the fact that we haven’t been invaded by tourists from the future.  (I used to think, well,  maybe we’re just the time-travel equivalent of someplace no one wants to visit. )  I guess Canada and I have showed him.

This post is my contribution to the April 2009 Working/Learning blog carnival, hosted by Dave Wilkins at his Social Enterprise blog.  (I updated this note when Dave’s "host post" appeared on April 30.) Conversation in a learning chat on Twitter last Thursday included this from Shanta Rohse: Doctors have "do not harm" I wish IDers had an equivalent. I always thought this phrase was part of the Hippocratic Oath, but it’s apparently much more recent. That spoils the analogy a bit, but not the idea of the duties of a learning professional. The UK’s General Medical Council has published the duties of a doctor. I used those to think about my responsibilities as a learning professional.  Here’s the result: Learners and clients must be able to trust learning professionals with their time, with their goals, and with their desire to learn. To justify that trust you must show respect for learning and you must: Respect the goals and the business of the clients and learners with whom you deal Protect and promote the right of each person to learn Provide a good standard of practice and care Keep your professional knowledge and skills up to date Recognize and work within the limits of your competence Work with colleagues in the ways that best serve learners’ interests Test your assumptions, question your preferences, and seek evidence to support the effectiveness of approaches to learning Treat learners as individuals and respect their dignity Treat learners politely and considerately Respect learners’ right to confidentiality Work in partnership with your clients Listen to them and respond to their concerns and preferences When you believe their plans or preferences will not accomplish their goals or facilitate learning, provide reasons and alternatives in a collegial, constructive manner Work in partnership with learners Listen to them and respond to their concerns and preferences Give them the information they want or need in a way they can understand Respect their right to reach decisions with you about their learning Support them in managing learning for themselves to improve and maintain their knowledge and skill Be honest and open and act with integrity Act without delay if you have good reason to believe that you or a colleague may be putting patients at risk Never discriminate unfairly against learners or colleagues Never abuse your learners’ trust in you What are your thoughts?

Frank Zappa once defined rock journalism as "people who can’t write, interviewing people who can’t talk, for people who can’t read." I think there’s a related phenomenon for bloggers who blog about blogging, and so I try to avoid that.  Today’s an exception, though if you don’t have a blog of your own you can skip and come back another day.  (I’m nearly ready for another post on Ten Steps to Complex Learning, which has taught me that "step" is a very flexible concept.) Sometime on Sunday, my blog was hacked.  And really hacked-more that a dozen of the behind-the-scenes files were altered, with code inserted in them that ended up taking orders from a server in Latvia.  (There are over 600 files that make up WordPress-a lot of scenery to hide behind.) At least on my own computer, that led to random redirects: I’d click a link in Google and jump past the target to some crummy aggregation site, from which I’m sure hacking-through-Latvia folks were getting reimbursement. I found some other malware on my own computer, though I don’t know if it’s connected to the blog hack or just a depressing coincidence.  As a result, I’ve spent the best past of two days doing search-and-destroy (or search-and-feel-befuddled), along with a lot of testing and attempts at cleanup. This is the dark side of the networked, interlinked world: we take our tools for granted, the way we don’t think about counterweights in elevators or the airframe on our flight to Dallas.  And the confluence of complexity with multiple vendors and extreme specialization means that when things go wrong, it’s damned hard to figure out where, let alone how to resolve it. Like this advice: The easy way to [protect your MySQL database] is to put the database access passwords in a file with a .inc.php extension (such as config.inc.php), and then place this file in a directory which is above the server’s document root (and thus not accessible to surfers of your site).  Then, refer to the file in your PHP code with a require_once command. I actually understand about 85% of that, which is more than I can usually say for household wiring.  Still, it leaves me pessimistic; working with PHP code is like working with that wiring, where I’m thrown as soon as I find three wires rather than just two (and, no, I’m not counting the ground wire). Caveat blogger. CC-licensed wiring photo by playbeasy.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » Getting to Step 4, "design supportive information," feels like a new stage in Ten Steps to Complex Learning. As the diagram shows, the first three steps relate most closely to learning tasks; steps 4, 5, and 6 relate to the supportive information component of van Merriënboer and Kirschner’s blueprint. [Supportive information] bridges the gap between what learners already know and what they should know to fruitfully work on the non-recurrent aspects of learning tasks… Remember, "supportive information" always mean support for non-recurrent aspects of complex skills-the things you do differently when handling different problems.  (The things you do the same each time fall under "procedural information."  It’ll be a few more posts before I get there.) So what is supportive information?  First, it’s information about how to solve problems in a particular domain (including how the domain is organized).  It includes examples that illustrate such information.  And it includes cognitive feedback on the quality of the learner’s performance. You could call it the theory for a field.  In fact, this is where well-meant complex training often goes bad.  "We don’t have much time, so we can’t do any hands-on.  Let’s concentrate on the theory." The main parts of the chapter: Providing systematic approaches and domain models Illustrating those approaches and models Presentation strategies Cognitive feedback Supporting information in the training blueprint Strategies and models: teaming up for learning A systematic approach to problem-solving (SAP) is a cognitive strategy; it helps you perform tasks and solve problems in a given field-systematically.  vM&K will go further into SAPs in the next chapter.  For now, in terms of learning complex skills, a learner might study an SAP, or might work with a process worksheet that guides him through a task. Mental models also provide support.  They explain the arrangement of the field-via conceptual models, structural models, and causal models. The two work together: a cognitive strategy isn’t any good if you don’t have a good mental model of the field; and the mental model’s no good unless you have an effective way to solve problems in that field. The goal of SAPs is to help the learner establish meaningful relationships among new pieces of information, and to establish meaningful relationships between those new elements and what she already knows.  Suggestions from The Ten Steps: When discussing phases, the learning methods should stress sequence and consequence.  You do job aid analysis after task analysis, because you need to know details about the tasks; you do job aid analysis before designing learning material, because job aids eliminate memorization. When discussing rules of thumb (a significant part of many cognitive strategies), the learning methods should stress cause-effect relationships-effect being the goal of the learner, and cause being what the learner needs to do to bring about the effect. Those seem closely related to me.  My guess is that the first bullet ("temporal organization" in vM&K’s terms) has to do with broader processes, while the "change relationship"  deals more specifically with decisions and actions.  That at least aligns with the idea that you have both high-level or global SAPs and more detailed ones. Keeping the model in mind If SAPs are how experts do things, mental models are how they see things. Conceptual models help answer the question, "What is this?"  A financial advisor needs to understand the difference between stocks, CDs, options, bonds, mutual funds, 401Ks, 403Bs, IRAs, SEPs, and other types of investment forms and structures.  Some instructional methods to facilitate this: Analyze a particular idea into smaller ideas (what kinds of tax-deferred accounts are there?). Describe main features or characteristics (an SEP is a tax-deferred retirement structure for self-employed people; a mutual fund is a form of indirect investment). Present a more general idea or organizing framework (connect principles of web page design to overall user-interface design). Compare and contrast similar ideas (an ordinary web site compared with a blog). Since we’re comparing and contrasting, structural models answer the question, "How is this organized?"  The typical focus is on the spatial or temporal relationship of parts.  What-happens-when models (which vM&K call scripts) might include things like life cycles (for organisms or for processes).  What’s-where models (templates) explain how things fit together. Among methods for aiding learning: Explain the relative location of elements in time and space.  (What are the components of a memorandum of law?  Of a court brief?) Rearrange elements and predict effects.  (What if you move elements within the style sheet?  Will digitized video of an actual performer aid or detract from learning? Causal models focus on how elements affect each other.  These models hlep learners interpret processes and make predictions.  They answer the question, "How does this work?"  The simplest form is a principle (for example, the law of supply and demand).  An interrelated set of principles is a theory (for natural phenomena like evolution) or a functional model (for human-built systems).  Methods for presenting causal models stress relationships: Make a prediction of future states.  (What will happen if we post federal earmarks, with locations, amounts, and sponsoring legislator?) Explain a particular state of affairs.  (Why is customer satisfaction o much higher in District Five than in Districts Three and Four?) Expertise: you can’t practice theory The eight bullets above, suggesting ways to present cognitive strategies and mental models, are expository.  They don’t provide any practice.  The bulk of this chapter of the Ten Steps deals with how to illustrate strategies and models, and how to activate prior knowledge and elaboration. In other words: the support needs to make things concrete, and needs to put learners to work. In instructional materials, modeling examples and case studies are the external counterparts of internal memories, proving a bridge between the supportive information and the learning tasks. For providing supportive information, modeling examples illustrate SAPs and case studies illustrate domain models, while these same two approaches may be seen as learning tasks with maximum task support. One criticism of much advanced training is that it’s too theoretical.  vM&K would say, "Well, duh!"  (Perhaps they’d say something more diplomatic.)  Real cognitive strategies combine theory (strategies and models) with real-life practice; otherwise you’re dealing only with abstractions. Modeling examples (you remember them as part of learning tasks) bring out the expert performer’s hidden mental processes.   One valuable form is seeing how the expert responds when things don’t work out.  How does she respond to the problem?  What does she see, what does she try?  Psychologists in training, for example, study videotaped sessions in which experienced therapists demonstrate specific techniques and strategies. Case studies, according to the Ten Steps, embody the types of models mentioned earlier.  A programmer might examine a successful interface to develop models for concepts like user-friendliness, metaphors, dialog boxes, and so on.  A structural-model case study might have architects exploring a building and analyzing how well the materials used fit the original purpose. I’m going to stop here.  Next time, I’ll look at how to match models and case studies with specific types of presentation.  I’ll also go into elaboration, a key requirement for supportive information, and into the way that supportive information in general fits into the Ten Steps blueprint. CC-licensed sales-strategy image by bschmove. CC-licensed affinity diagram by Rosenfeld Media. CC-licensed bridge photo by tour of boring. 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) (that's this post) Learning to learn (an elaboration)

Andrew Maynard, an expert on new scientific technologies,  has a post reprising the notion of the two cultures (science and humanities, with a chasm between them).  He offers a one-question poll and sees the results as indicating that the chasm isn’t necessarily that vast. Ruth Seeley offers a similar poll from the humanities side. I liked both polls, though as I commented to Ruth, I’m not sure her topic is necessarily comparable Andrew’s. Ruth knows this isn’t a serious disagreement; we’ve had several enjoyable exchanges. The two polls did give me an excuse to test a polling plugin (a piece of code for WordPress blogs like this one). Other than messing around in the tool aisle, I was shooting for a question like Maynard’s that touches on more fundamental concepts. Note: There is a poll embedded within this post, please visit the site to participate in this post's poll. Okay; now you can scroll down to the comments and check. Then, if you would, the bonus round: a second poll to help analyze the answers: Note: There is a poll embedded within this post, please visit the site to participate in this post's poll.

For some time, I’ve been using CC-licensed images on my blog posts and elsewhere as well.  CC Search makes that easy, as does Compfight. I’m using far less text and far more images when I create presentations or workshops.  Here, you still get lots of text.  So it goes. I think it’s important to give credit to the people who offer the images, and so I try always to make the image itself a link back to the source.  And I try to include a credit (like at the bottom of my posts), linking to the photographer’s profile. One other thing I’ve been doing is writing a brief note to the photographer.  I thank him for sharing. I include a link to the photo (so he knows which one I’m talking about), and I include a link to the blog post (in case he’s curious about how I used the image). I’m often surprised by the associations I make based on the images.  Even if my contact with the photographer is a one-time thing, it reminds me that there aren’t events-but there are connections. By the way, the April edition of the Working / Learning blog carnival has arrived, hosted at Dave Wilkins’ Social Enterprise blog.  It’s worth a visit. If you don’t think you can contribute this time around, Kevin Jones of Engaged Learning will host the May edition.  (Wanna host in June?) CC-licensed hoto of phone photo by Dave.Hull.

WordPress code is freshly scrubbed; database is tidy; posts and images are back where they should be (I think).  Glad I didn’t lose my head. CC-licensed photo of my favorite female in France by wilth.

Series: Ten Steps to Complex Learning « Previous post in this series • Next post in this series » As with the previous post in this series, I’m on Step 4, "design supportive information," of van Merriënboer and Kirschner’s Ten Steps to Complex Learning. To recap briefly, supportive information includes cognitive strategies (different ways that experts go about dealing with problems in a domain) and mental models (the conceptual maps showing how parts of the domain are organized). This post will summarize the four remaining topics in Step 4: Presentation strategies-how to help people learn by providing supporting information Elaboration-what it is and why it matters Cognitive feedback-another element in learning to learn Positioning-when to provide the theory, when to provide feedback Deduction, induction-your thoughts? A deductive approach moves from the general to the specific.  As vM&K note, it’s the default for a lot of technical training: the theory of widgets, the principles of negotiation, Maslow’s hierarchy. Deduction is hard for novices.  I’d say it’s nearly impossible.  Since by definition they’re new to the field, they have little if anything already in their mental inventory to connect with the new information. If you wanted to learn Scottish Gaelic and I began by explaining lenition, slenderization, and epithentic vowels, that’d be taking a deductive approach. Not only would you likely be confused, you couldn’t go into a pub on Lewis and order a drink in Gaelic. Deductive approaches make sense, the Ten Steps suggest, in certain circumstances: Limited time Learners already knowledgeable about the domain No need for deep knowledge (which certainly applies to my own skill with Scottish Gaelic) Inductive learning: the specific start Inductive approaches start with concrete examples and work toward general cases.  Where the deductive approach is exposition ("principles of widget design"), the inductive approach is inquisitory ("What do you like about the layout of Amazon’s home page?  What do you like about the layout of Zappo’s?").  Examples and models are like stepping stones to the more general concept. What’s going on is that the specifics help to activate what the learner already knows, since it’s easier to grasp a concrete example than a general case.  Using analogies and models, the learner makes connections between what she’s already learned and the new information at hand. Inductive approaches are inevitably more time-consuming, especially if there’s a great distance between the examples and the broad concept they’re part of.  A short-distance example might be seeing photos or videos of different dogs in order to come up with the broad concept of dogs.  That’s less challenging that seeing examples of behavior and coming up with the concept of "justice." Even so, the Ten Steps advocates making induction the default strategy for complex learning. Guided discovery: you’re on your own Guided discovery is a third approach.  There’s no presentation; the learner independently identifies and articulates the general information.  vM&K make a distinction between pure discovery and guided discovery; the latter has leading questions and other prompts. You can see how a detailed serious game, simulation, or virtual world could serve as a vehicle for guided discovery-the structure of the environment, the information available, the decisions to make can all provide opportunities for the learner. When to consider this approach? Ample time Learners with well-developed discovery skills A need for deep understanding This chapter discusses ways to promote "activation of prior knowledge" as well as elaboration of new information-for example, through epistemic games (here’s an article; here’s a commercial website). ("Epistemic forms" have to do with how knowledge is organized and how different facts and concepts are related. ) Let’s do more with elaboration vM&K say (again) that supportive information-those cognitive strategies and mental models-provide abridge between what learners know already and the new information they’re working with.  Along with induction, a key learning process is elaboration. This means in part that the learner searches his memory for ways to understand and connect with the new information.  "Oh, that’s kind of like when I…"  This links what he already knows to the new material, and does so consciously. The theory is that elaboration aids learning because the more connections that exist (within the parts of the new material, and between the new and what’s already known), the more readily he can retrieve and apply what’s new. Which also means that a person can learn to elaborate-for example, to deliberate work at incorporating new information, to ask how it might apply in other contexts, and so forth. Elaboration and induction can produce new cognitive schemas to guide problem-solving and reasoning about a domain.  Usually that guidance is specific, as if you’re following a mental checklist.  ( "I saw a problem like this five years ago-let me think, that was for an executor who was transferring funds from a 403(b)…") Performers sometimes activate certains schemas often enough that they become automatic.  vM&K don’t think this is all that common, but it may produce the tacit knowledge we think of as the specialist’s knack. People constructed advanced schmas through elaboration or induction, and then form cognitive rules of these as a function of direct experience.  Afterwards, the schemas quickly become difficult to articulate because they are no longer used as such.  The cognitive rules directly drive performance, but are not open to conscious inspection. To me, this makes sense, and helps explain the notion that it takes around 10,000 hours to become an expert.  That amount of time-the equivalent of five years at a full-time job-allows for increase range and depth in a field, and thus for richer elaboration. Of course, some people don’t have five years’ experience; they’ve got one year that they repeat five times. Cognitive feedback’s not for correcting Feedback on the quality of performance, in the Ten Steps, is cognitive feedback.  It refers only to the non-recurrent aspects of the tasks, and provides information (such as prompts, cues, and questions) to help the learner construct or reconstruct cognitive schemas so that future performance is improved. Such feedback encourages the learner to reflect both on the problem-solving process and on the solution found.  vM&K say the purpose is not to detect and correct errors but to encourage self-reflection. This, they say, relates to the concept of double-loop learning put forth by Chris Argyris and summarized in a blog post by Ed Batista. How can you encourage this? Ask learners to compare their own problem-solving processes with those in systematic approaches to problem-solving (SAPs), or with those of other learners, or with mdeling examples. Ask learners to compare their own solutions (or partial solutions) with those in case studies, with expert solutions, with those of other learners. Provide counter-examples. In that last case, vM&K give the example of a medical student who decides that a patient has a particular disease based on the particular symptoms.  The instructor provied a hypothetical patient who has the same symptioms, some of which may have arisen as side-effects of medication (rather than from the disease in question). What goes where? Van Merriënboer and Kirshner suggest that in a deductive approach, general information (the theory) appears in the form of lectures, textbooks, and other preset formats.  In an inductive approach, learners often have to search for the theory; they start with the specific examples. And in a guided discovery approach, the general information is never presented in a present form; the learners must articulate it for themselves. Meanwhile, cognitive feedback makes no sense until learners have finished a learning task.  You can’t see how you did until you’ve done something.  (Note, as vM&K do, that immediate feedback does make sense for the recurrent aspects of tasks, as we’ll see in a later post.) CC-licensed photo of a Manly NSW street sign by Jeff Croft. Image of Ma’at, ancient Egyptian "concept of justice," from Wikimedia Commons. CC-licensed "strategies" photo by Old Shoe Woman. 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) (that's this post) Step 5: cognitive strategies (when you don’t know what to do)Step 6: (thinking about) mental models