Human intelligence: concepts, theories, and assessment methods

¶ … human intelligence in the context of the Developing Expertise Model. The author argues that the conventional view of what intelligence is and how it can be measured is incorrect. He puts forth an alternative perspective which views intelligence as a developing expertise and intelligence tests as measuring a limited aspect of developing expertise. The author concludes by stating that intelligence-related phenomena can be better understood using this new model.

Traditionally, intelligence has been viewed as a relatively stable attribute developed through an interaction between heredity and environment. Intelligence tests measure a variety of skills such as vocabulary, reading comprehension, an arithmetic problem solving. Furthermore, these test results are believed to predict one's future success. In contrast, developing expertise is defined as "an ongoing process of the acquisition and consolidation of a set of skills needed for a high level of mastery in one or more domains of life performance" (Sternberg, 1999, p. 359). Although people differ in rate of expertise development, the main constraint is not some fixed level of capacity; but rather, purposeful engagement, such as active participation, role modeling, direct instruction, and reward. That being said, this model does not rule out the potential for genetic factors to limit one's ability to develop a certain amount of expertise. Nevertheless, these genetic factors cannot be directly measured or even estimated. "Rather, what is measured is a portion of what is being expressed, namely, manifestations of developing expertise" (Sternberg, 1999, p. 360).

The Specifics of the Developing Expertise Model

The Developing Expertise Model has five key elements: metacognitive skills, learning skills, thinking skills, knowledge, and motivation. These elements are separated, yet they interact with and influence each other. Nevertheless, development in one domain does not necessarily lead to development in another domain.

Metacognitive skills refer to the way one understands and controls their own cognition. For example, what an individual knows about writing an essay, such as the steps involved and how these steps can be executed effectively, is an example of metacognitive skills. The seven major metacognitive skills are: problem recognition, problem definition, problem representation, strategy formulation, resource allocation, monitoring of problem solving, and evaluation of problem solving. Learning skills refer to knowledge acquisition and are divided into two categories: explicit learning skills (i.e. conscious efforts to learn) and implicit learning skills (knowledge acquired unconsciously). Examples of learning skills include selective encoding, selective combination, and selective comparison. Thinking skills refer to performance and include critical thinking skills (e.g. evaluating), creative thinking skills (e.g. inventing), and practical thinking skills (e.g. applying). Knowledge includes declarative knowledge (e.g. facts and concepts) and procedural knowledge (e.g. how something is done). Finally, motivation includes achievement motivation (e.g. strivers constantly trying to better themselves) and competence motivation (e.g. developing a sense of self-efficacy).

The g-Factor and the Structure of Abilities

Many intelligence theorists claim that the human intelligence is a relatively stable attribute based on the stability of the alleged general factor (g-factor) of human intelligence. However, this g-factor may instead be the result of an interaction between an individual's latent abilities and the forms of expertise they developed in school. From this point-of-view, the g-factor could be made stronger or weaker depending on one's type of schooling. In fact, the author of this article states that Western forms of schooling may have created the g-factor phenomena by teaching the skills intellectual tests measure.

An intelligence theorists would state that schooling develops crystallized intelligence (i.e. The ability to use knowledge and skills) not fluid intelligence (i.e. The ability to acquire and reason with information). Conversely, according to the Developing Expertise Model, both crystallized and fluid intelligence are equally susceptible to development through school or other aspects of an individual's environment.