Sunday, November 13, 2005

Cognitive efficiency and cognitive load theory instruction

As more and more of us CHC-types integrate CHC abilities within an information processing framework, it is becomming clear to me that recent developments in Cognitive Load Theory (CLT) may have particular importance to helping us design instructional methods to better match the CHC/information processing characteristics of learners. In particular, anecdotal reports on various clinical listervs, as well as empirical research I've completed (as well as others - click here 1; click here 2), suggests that a person's "cognitive efficiency" (the combination of Gs and Gsm-Wm [working memory]) may have a major bearing on learning efficiency.

As I read the CLT literature, I can't help but see a connection between individual assessment information regarding a person's cognitive efficiency and the development of instructional approaches/materials based on CLT. Click here to read a good overview of CLT (the article listed below).


vanMerrienboer, J. J. G., & Sweller, J. (2005). Cognitive load theory and complex learning: Recent developments and future directions. Educational Psychology Review, 17(2), 147-177.

Abstract

Traditionally, Cognitive Load Theory (CLT) has focused on instructional methods to decrease extraneous cognitive load so that available cognitive resources can be fully devoted to learning. This article strengthens the cognitive base of CLT by linking cognitive processes to the processes used by biological evolution. The article discusses recent developments in CLT related to the current view in instructional design that real-life tasks should be the driving force for complex learning. First, the complexity, or intrinsic cognitive load, of such tasks is often high so that new methods are needed to manage cognitive load. Second, complex learning is a lengthy process requiring learnersrsquo motivational states and levels of expertise development to be taken into account. Third, this perspective requires more advanced methods to measure expertise and cognitive load so that instruction can be flexibly adapted to individual learnersrsquo needs. Experimental studies are reviewed to illustrate these recent developments. Guidelines for future research are provided.

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