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A cognitive approach is the study of how knowledgebased systems acquire and use information in their interactions with the environment. Any reality that is able to be depicted as a knowledge-based system is open to a cognitive approach. Psychology understands the human mind as such a knowledge-based system, an active mind that acquires, transforms, and uses information by a variety of basic (cognitive) processes, such as attention, perception, memory, language, and reasoning. These active minds are assumed to be able to tune those processes to different contexts and to learn in a very flexible way. The cognitive approach is now, clearly, the dominant approach in different areas of psychology.

Conceptual Overview

Although a cognitive approach is not restricted to the field of psychology, it is here that its impact is most relevant to organization studies. By emphasizing mental processes, the development of this approach was historically placed in opposition to behaviorism, which largely ignores mental processes. Today, the cognitive approach has overtaken behaviorism in terms of popularity.

Several names are associated with the development of this approach; however, Herbert Simon and Allan Newell are recognized as two of the most important contributors. The level of Simon's contribution to the understanding of decision making was such that in 1987, he won the Noble Prize in economics. His work on decision making, summarized in his book entitled Administrative Behavior, is an example of how the cognitive approach is highly relevant to the field of organization studies. The cognitive approach was established as such around 1956, and is defined according to its fundamental assumptions and basic concepts.

Fundamental Assumptions of the Cognitive Approach (CA)

The cognitive approach assumes that information is mentally represented and processes are defined according to such representations. Information is mentally represented in terms of symbols (for example, a number may represent a quantity). As Neil A. Stilling and his collaborators remind us, processing is defined independent of the meaning associated with those symbols, as simple manipulations/transformations of those symbols (following some rules or algorithms—like the way “multiplication” is a rule able to transform numbers). To define a process is to identify the algorithms (the formal procedure) that underlie those transformations. The CA has no assumption regarding the nature of these representations Some theories see them as explicit and localized (as schematic representations, such as the ones theorized by authors like Roger Schank and Robert Abelson) while others see them as distributed over many memory locations, defining connectionist models that describe mental phenomena by interconnected networks of simple units (a work represented by authors such as David Rumelhart and James L. McClelland). Different kinds of information may also be assumed to have different kinds of representations. For example, perceptual and conceptual information may be assumed to have distinct modes of representation, or this visual or tactile information may be assumed to have the same type of codification as conceptual information. Thus, what characterizes the CA is the focus on the understanding of those representations, assuming that processing relies on their transformation. This focus on representation and process relates empirical hypothesis testing in a CA to measures such as reaction times, recall or recognition, error rates, and so forth.

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