My theories on intelligence can be divided in two parts: the theory of successful intelligence and the theory of practical intelligence (common sense).
Augmented Theory of Successful Intelligence
The traditional view of intelligence is that it comprises a single general ability (g), under which are hierarchically arranged successively more specific levels of abilities, such as fluid ability (the ability to think flexibly and in novel ways) and crystallized ability (cumulative knowledge).
The augmented theory of successful intelligence, in contrast, suggests that intelligence is more complex than this. Successful intelligence is defined as one’s ability to set and accomplish personally meaningful goals in one’s life, given one’s cultural context. A successfully intelligent person accomplishes these goals by figuring out his or her strengths and weaknesses, and then by capitalizing on the strengths and correcting or compensating for the weaknesses. Strengths and weaknesses are in terms of four kinds of skills: creative, analytical, practical, and wisdom-based. In particular, the individual needs to be creative in order to generate novel and useful ideas; analytical to ascertain that the ideas he/she has (and that others have) are good ones; practical in order to apply those ideas and convince others of their value; and wise in order to ensure that implementation of the ideas will help ensure a common good through the mediation of positive ethical principles.
Although intelligence is viewed as of various kinds, the mental processes involved in creative, analytical, practical, and wise thinking are the same. Metacomponents, or higher order executive processes, plan, monitor, and evaluate courses of thinking and action. Examples of metacomponents are recognizing the existence of a problem, defining the nature of the problem, and mentally representing information about the problem. Performance components implement the instructions of the metacomponents. Examples of performance components are inferring relations and applying relations. And knowledge-acquisition components learn how to solve problems in the first place. Examples of knowledge-acquisition components are selective encoding (deciding what information currently available in a problem is relevant for one’s purposes) and selective comparison (deciding what prior information stored in memory is relevant for one’s purposes).
My colleagues and I have tested the theory of successful intelligence, in its various phases, using a variety of converging operations, including reaction-time analysis, cultural analysis, factor analysis, correlational analysis, predictive analysis, and instructional analysis, among other methods. The results have been, for the most part, highly supportive of the theory.
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Sternberg, R. J. (2011). The theory of successful intelligence. In R J. Sternberg & S. B. Kaufman (Eds.), Cambridge handbook of intelligence (pp. 504-527). New York: Cambridge University Press.
Practical Intelligence (Common Sense)
Practical intelligence, or common sense, according to a theory I developed with Richard Wagner, is based in large part upon tacit knowledge, or what one needs to know to succeed in a particular environment that is not explicitly stated and often that is not even verbalized. What are the characteristics of tacit knowledge, a concept first proposed by Michael Polanyi?
First, tacit knowledge generally is acquired on one's own with little support from other people or resources. It usually is acquired, for example, without the support of formal training or direct instruction. When knowledge acquisition is supported, certain processes underlying that acquisition are facilitated. These processes include selective encoding (sorting relevant from irrelevant information in the environment), selective combination (integrating information into a meaningful interpretation of the situation), and selective comparison (relating new information to existing knowledge). When these processes are not well supported, as often is the case in learning from everyday experiences, the likelihood increases that some individuals will fail to acquire the knowledge. Additionally, because its acquisition usually is not supported, tacit knowledge tends to remain unspoken, underemphasized, and poorly conveyed relative to its importance for practical success.
Second, tacit knowledge is procedural in nature. It is knowledge about how to act in particular situations or classes of situations. But as is the case with much procedural knowledge, people may find it difficult to articulate the knowledge that guides their action. In particular, tacit knowledge is a subset of procedural knowledge that is drawn from personal experience and that guides action without being easily articulated. In other words, we consider all tacit knowledge to be procedural, but not all procedural knowledge is tacit.
Third, tacit knowledge often is expressed in the form of complex, multi-condition rules (production systems) for how to pursue particular goals in particular situations (e.g., rules about how to judge people accurately for a variety of purposes and under a variety of circumstances). These complex rules can be represented in the form of condition-action pairings.
Fourth and finally, a characteristic feature of tacit knowledge is that it has practical value to the individual. Knowledge that is experience-based and action-oriented will likely be more instrumental to achieving one’s goals than will be knowledge that is based on someone else’s experience or that does not specify action. For example, leaders may be instructed on what leadership approach (e.g., authoritative vs. participative) is supposed to be most appropriate in a given situation, but they may learn from their own experiences that some other approach is more effective in that situation.
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