How Experts Process Education

How Experts Process Education

by Marty Rosenheck | Chief Learning Officer

 

Cognitive scientists have spent years studying the characteristics of top performers and how they develop their expertise. Organizations can leverage the results of this research to design formal and informal learning processes that accelerate the development of proficient and even masterful performance. Three key principles from expertise research have direct implications for developing top performers in organizations.

 

Principle No. 1: Experts learn through experience, reflection and deliberate practice.

 

The research is clear - people develop expertise through experience. Cognitive scientists studying expertise say it takes 10 years to become an expert on something. In his book Outliers, Malcolm Gladwell says it takes 10,000 hours of experience to become an expert. But experience alone is not enough. People become master performers by working through a variety of problems, getting feedback on what they do and reflecting on it. For any complex job, whether it is sales, customer service, using computer systems or technical decision making, people become top performers through deliberate practice.

 

How can we shorten the path to expertise? By exposing learners to a systematically organized set of situations in a compressed timeframe. In a relatively short amount of time, learners get experiences it would otherwise take years to accumulate. For example, cognitive researchers Suzanne LaJoie and Alan Lesgold built a simulator for train technicians to learn to troubleshoot avionics on fighter jets. They were able to produce technicians in six months who were as proficient as those who had been on the job for four years.

 

As learning and development professionals, we can increase speed to proficiency by setting up a learning path that provides a wide variety of practice cases, problems or tasks. These can take many forms: online simulations, paper-based formats, classroom simulations, role play or on-the-job experiences. Begin with simple cases, and then build to more and more complex cases as the learners gain competence and confidence.

 

Likewise, begin with substantial scaffolding (support and guidance) and gradually reduce the degree of guidance. The more a learning activity is situated in the job context, the more it is retained and applied in future situations.

 

A key adjunct to experience is reflection; the process of thinking about what one has done or learned. The act of pausing to observe and reflect turns experience into learning that can be applied to new situations. Organizations can provide opportunities to reflect through coaching, discussion forums, virtual communities, blogs, and through the act of teaching or coaching others.

 

For example, a large government agency needed to increase the speed to proficiency of new customer service representatives whose complex jobs combined computer system usage, customer service skills and policy knowledge. To accomplish this, it replaced a formal presentational style of training with a learning-by-doing curriculum. It used an online learning path to guide people through simulations and practice using realistic cases, and then moved to a structured on-the-job training component where they worked on real cases and reflected on them with the support of mentors and colleagues in a virtual learning community, using online meetings, IMs and forums.

 

Principle No. 2: Experts organize their knowledge by how it is used to solve problems.

 

In a classic research study, cognitive scientist Michelene Chi and her colleagues examined the differences between experts and novices. The content area they focused on was physics, comparing novices (straight-A physics students) with expert physicists (academics with years of experience). The physics students did as well as the experts on comprehensive physics exams. But when the novices were given real-world physics problems to solve, they were not able to solve them. The expert physicists were able to solve these problems quickly.

 

The novices and experts both had the same amount of knowledge as measured by the physics exam. What did the experts have that the novices lacked? The researchers found that the major difference between novices and experts was not the amount of knowledge, but in how that knowledge was organized in their minds.

 

The novices organized their knowledge in a way that matched the organization of a physics textbook. The experts had reorganized their knowledge according to the way it is used to solve real problems. Experts recognize the salient cues in a situation or problem and make instantaneous connections from those cues to the knowledge they need to handle the situation effectively. They develop this implicit knowledge from years of experience, trial and error and reflection on that experience.

 

One implication of this research for developing top performers is to use master practitioners - people with expertise in actually doing the job - as the standard. The goal is to help learners organize their knowledge the way that top performers do, not the way a PowerPoint presentation does. A number of methods for eliciting this implicit knowledge have been developed by cognitive scientists and knowledge engineers. These methods can be useful for capturing the categories, constructs, implicit heuristics, principles and guidelines that experts use.

 

The card sort - a simple test in which subjects sort out a set of index cards with various terms written on them - is one method to get experts to reveal the way their knowledge is organized. The act of categorization gets experts to make judgments that uncover their implicit knowledge of their job, information that we would not get by just interviewing them. The categories that resulted from the card sort contain the cues for the solution to the problem. For example, this method was used with construction managers, who organized a set of situations and problems by how they are solved, using categories such as "communication problems with sub-contractors." The sorting task also enabled the construction of taxonomy of cases, where typical situations were categorized and sequenced from simple to complex to serve as a model for initial learning for less experienced construction managers.

 

We know that experts take years develop these direct mental links between the problems or situations and the knowledge they need to solve them. How can we speed up the process of forming those links in learners? Capitalize on the teachable moment.

 

As learners work through cases, there are points at which they are faced with a decision of what to do next, points where the user thinks, "Hmm ... I'm not sure what to do now." At that point, that teachable moment, people are motivated to learn because they need information to complete the task at hand. They are also likely to remember that information later on the job, because by getting information at the teachable moment, they create a mental link between the information and how it is used on the job. This means the information will be indexed in trainees' minds and they are more likely to be able to retrieve it when they need it in real life - just like an expert.

 

The takeaway is to provide cases or problems that are constructed to present a series of teachable moments that set up opportunities to learn key content. Make sure the appropriate content information is easily available to the learner when it is needed at the teachable moment. Use a knowledge base to provide the right amount of the right content at the right time. The same knowledge base used during training can also be used on the job for performance support.

 

It can contain:

 

a) Online reference.

b) Mini-tutorials.

c) Expert stories.

d) Video or audio clips.

e) A mentor or expert (available in person or virtually).

 

Principle No. 3: Experts develop in a community of practice.

 

Etienne Wenger, one of the originators of the concept of communities of practice, once said, "The community creates the social fabric of learning." A community of practice provides a context for people to reflect, reinforce and extend their knowledge by discussing it with each other, either in person or through distance technologies or social media.

 

Technology is not necessary for communities of practice to exist. They form when people with common interests and goals talk informally in the hallway, ask questions and share insights. However, technology - and especially Web 2.0 technologies like forums, wikis, virtual meetings, blogs, social networking tools (like Facebook or LinkedIn), and microblogs (like Twitter) - can extend reach, increase the number of possible connections, enable finding the right person or information and track the effectiveness of communities of practice.

 

In the formal learning mode, a community of practice meets regularly (physically or virtually) to discuss cases, support each other and ask questions. In the aforementioned government agency, trainees met regularly together with a mentor to present and discuss cases in a roundtable format. Talking about cases in a community of learners expands the range of case knowledge for everyone and helps people put the cases into a usable context.

 

These principles are just a sampling from the body of cognitive research on expertise and its implications for developing expert performance.

 

 

[About the Author: Marty Rosenheck is chief learning strategist at Cedar Interactive, a custom learning solution consulting and development company.]