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 integration 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.

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