9 How Much and What Type of Guidance is Optimal for Learning ...

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How Much and What Type of Guidance is Optimal? 1630123456789012345678901234567890123456form of procedures that accomplish goals and that declarative knowledge issometimes useful to fill in the missing steps of already- learned productions.ACT- R also suggests that with use over time, productions become automatedand unconscious but declarative knowledge is processed in working memorywhere activity is consciously recognized. ACT- R specifies that whenever we recognizethe conditions that reflect a performance goal, performance is initiatedthat draws on available productions. When the goal is to learn or solve aproblem, we apply the goal- directed productions we have available and if availableproductions are incomplete or inadequate we use declarative knowledge tofill in the missing steps. If instruction provides the necessary steps to fill the gap,learning occurs faster and more effectively (e.g., with fewer performance errors)than if we must fill in the gaps using declarative knowledge (Velmahos et al.,2004; Clark & Elen, 2006). Yet our awareness of performance is limited to thedeclarative knowledge we have processed in working memory because productionsare automated and unconscious so that they circumvent the limits onworking memory (see, for example, an engaging discussion of this process in achapter on consciousness by Kihlstrom, 1987, and in Sweller’s 2006 descriptionof Cognitive Load Theory).Self- awareness is, in part, the capacity to observe our thinking about andremembering declarative knowledge. Yet we are only indirectly aware of our constantuse of automated, unconscious procedural knowledge, which we canobserve only by noticing the consequences of its operation. For example, mostadults, when asked for the product of 6 × 108 will respond “648” without anawareness of how they solved the problem. Only the unautomated portions ofthe solving procedure are conscious and therefore open to conscious inspection.Some readers may have multiplied 100 by 6 and added the automated product of6 times 8 to get the solution; others may have immediately realized the answer“648.” Those who performed the operation in two conscious steps are morelikely to be aware of their cognitive processing than those who have automatedthe entire solution process for this type of problem.Important to this discussion is recent evidence that the declarative componentsof learning or problem solving may only be the “tip of the iceberg.” It islikely that the teaching and learning of most tasks and the solving of complexproblems require an understanding of a large number of task- specific automatedprocesses that support the handling of the conscious components oftasks. These unconscious components may be unknown and/or ignored byinstructional researchers, teachers, or trainers. Because of the severe limits onour working memory, it is likely that most mental processes supportingproblem solving and learning are automated and unconscious (Cowen, 2001;Clark & Elen, 2006; Sweller, 2006; Feldon, 2007). One way to interpret the evidencefrom the past half- century of research on discovery learning (Mayer,2004) is that the type of learning that most effectively supports performance oncomplex tasks is almost completely procedural and that experts are largelyunaware of how they perform tasks and solve problems because expertise islargely automated and unconscious (Clark & Elen, 2006; Clark, Feldon, vanMerriënboer, Yates, & Early, 2007).
164 R. E. ClarkExperts Are Largely Unaware of How They Perform—The 70% PrincipleOne component of instruction is a curriculum, which is, in part, a description ofthe knowledge required to accomplish a set of tasks. Experts who most oftenhave both practical experience and a formal education in the field to be taughtprepare curricula. When experts develop instructional materials they attempt toshare what they know about the tasks students must learn. Yet there is evidencethat while most experts are successful at solving even very complex problemswithin their area of expertise, they are largely unaware of the operation of theirown expertise (Besnard, 2000). For example, Feldon (2004) studied theself- awareness of personal research design strategies used by a number ofwell- published psychologists who teach research design. He found that theseexperts who serve as mentors for young researchers were approximately 70%unaware of the primary analytical strategies they were using when designingexperiments.Additional evidence for the hypothesis that expertise is largely automated andunconscious comes from studies of task analysis and other self- report protocolsconducted with experts. For example, Chao and Salvendy (1994) studied theerrors made by a number of top programming experts during systematictask- analysis interviews. The steps suggested by the experts to solve and debugspecific programs were collected and used to develop a master protocol. Theiranalysis suggested that the debugging strategies suggested by each expert wereonly approximately 31% accurate. These experts could debug programs but werenot aware of about 70% of the steps they used. Besnard (2000), Clark et al.(2007), and Hoffman, Crandall, and Shadbolt (1998) have described otherstudies that report similar data.Teachers and Trainers May Often Provide Wrong or IncompleteInformationThe evidence for our lack of awareness of our own automated procedural knowledgesheds doubt on many of our most closely held assumptions about instructionand learning. Teachers are selected for their expertise at all educational levelsfrom early schooling to the most advanced doctoral programs. Cognitive apprenticeships(Brown, Collins, & Duguid, 1989) and communities of practice (Brown& Duguid, 1991) are both popular strategies for teaching complex knowledge.Teachers, mentors, and collaborative colleagues are expected to “teach what theyknow.” If experts who teach are an average of 70% unaware of their proceduralknowledge, what might be the consequence for their students or collaborators?For the past half- century, studies examining the interaction between studentaptitudes and different forms of instructional treatments (most often called aptitudex treatment or ATI studies) have consistently reported that students withlower ability levels and/or less prior knowledge and/or lower motivation aremore vulnerable to learning difficulties when instruction is incomplete, unstructured,or gives inaccurate information (e.g., Cronbach & Snow, 1977; Kyllonen &Lajoie, 2003).1234567891111111111222222222233333333334444444
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