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The promise of cognitive apprenticeship

As a computer-based system, multimedia is frequently used to train people procedures for the use of computer systems and applications. Using multimedia to teach other kinds of skills can be much more challenging.

Consider, for example, principle-based tasks—such as sales or customer service—which require performers to exercise judgment and flexibility on the job: there's no one correct approach to such tasks, as there is with procedures. To be effective, sales representatives or customer service agents must adjust their approach depending on the context, the issues at hand, the customer, their prior interactions with the customer, and other factors. They must exercise judgment at every turn. For them, each new customer interaction is a problem-solving situation.

Teaching problem-solving has always been more challenging than teaching procedural skills. Of the four architectures, the guided discovery approach is specifically designed to support this type of learning. The following paragraphs will describe and illustrate one type of guided discovery called the cognitive apprenticeship.

A cognitive apprenticeship is designed to build expertise. Chess masters such as the ones who participated in the Simon experiment described earlier have more than 50,000 chess situations stored in their long-term memory. It's estimated that it takes about 10 years of sustained practice to achieve such a store of knowledge. In fact, experts in all fields rely on patterns accumulated in long-term memory through years of experience. How can multimedia be used to accelerate the building of expertise?

For hundreds of years, the apprenticeship has been a favored method of training. The guild systems of the Middle Ages formalized the idea of the apprenticeship, and forms of apprenticeship are still in use today, notably in the building trades and crafts. And in all kinds of work settings, the idea of apprenticeship survives in the form of unstructured, on-the-job training. Apprenticeships provide training that's highly relevant and directly transferable to job performance. Apprentices more easily remember the job knowledge and skills they've learned because the learning has taken place in the job setting.

The problem with such apprenticeships is that they tend to be inconsistent and inefficient. Skills tend to be presented differently, depending on who's doing the training. In addition, apprentices necessarily learn what a job requires as it happens rather than in the sequence that's most efficient for learning. But a cognitive apprenticeship is different. It takes advantage of all the effective aspects of apprenticeships while avoiding their inefficiencies.

A computer-based tutor called Sherlock, designed by the University of Pittsburgh and the U.S. Air Force, is one successful (and well-documented) implementation of the cognitive apprenticeship model. Sherlock was developed to train Air Force technicians in troubleshooting the sophisticated equipment used to monitor electrical systems in F-16 jet fighters. An evaluation of the effectiveness of Sherlock found that apprentices who used the system for 25 hours acquired the performance capabilities of journeymen mechanics with four years of equivalent field experience.

Sherlock's acceleration of the process of developing expertise is impressive, but not magical. It demonstrates the power of multimedia to compress time by means of high-fidelity simulations. In the normal course of events, the Air Force's electrical monitoring equipment doesn't malfunction very often. Even when it does, the malfunctions aren't consistent—the same problem may or may not reappear for months. And a given repair often requires new parts, so hours or days may go by before the technicians can determine whether in fact the solution they have in mind will work. And, of course, real-world problems don't present themselves in any structured or predictable sequence. The most difficult problems are just as likely to occur early in an apprentice's experience as later on.

To overcome such real-world problems in training new technicians, the Sherlock cognitive apprenticeship system presents a systematic sequence of problems for a new troubleshooter to solve—a sequence of problems designed to build knowledge effectively. Learners attempt a simulated repair, and within seconds they get feedback about whether they've succeeded. Tailored coaching built into the system provides learners with hints and guidance that fit their individual needs.

A good example of cognitive apprenticeship design is found in the award-winning multimedia course, called the Fair Lending Challenge, which was developed by Interworks. The goal of the multimedia course is to teach fair lending practices to bank loan officers and to reinforce the need to make loans that are secure and profitable. In the course, learners are presented with a series of loan applicants on a laptop computer on their desks. When an applicant is selected, an interview is conducted where information that is present on the loan application and credit reports can be clarified. A reference guide provides neighborhood advantage guidelines and other information needed in determining the loan. Eventually, the learner indicates whether the loan should be approved or disapproved, and explains the reasons for the decision. Following the interview, the bank lawyer provides immediate feedback if fair lending practices have been violated by the types of questions asked. At the end of the game, the branch manager gives the learners a performance appraisal. A week at work is compressed into two hours of game time, thereby allowing much experience to be rapidly gained.

The learner acting as a loan officer interviews a loan applicant. Courtesy of InterWorks

Feedback from the lawyer if fair lending principles are violated. Courtesy of Interworks.

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