Expert and novice performance in solving physics problems

An operant analysis of problem solving

Behavior that solves a problem is distinguished by the fact that it changes another part of the solver's behavior and is strengthened when it does so. Problem solving typically involves the construction of discriminative stimuli. Verbal responses produce especially useful stimuli, because they affect other people. As a culture formulates maxims, laws, grammar, and science, its members behave more effectively without direct or prolonged contact with the contingencies thus formulated. The culture solves problems for its members, and does so by transmitting the verbal discriminative stimuli called rules. Induction, deduction, and the construction of models are ways of producing rules. Behavior that solves a problem may result from direct shaping by contingencies or from rules constructed either by the problem solver or by others. Because different controlling variables are involved, contingency-shaped behavior is never exactly like rule-governed behavior. The distinction must take account of (1) a system which establishes certain contingencies of reinforcement, such as some part of the natural environment, a piece of equipment, or a verbal community; (2) the behavior shaped and maintained by these contingencies; (3) rules, derived from the contingencies, which specify discriminative stimuli, responses, and consequences, and (4) the behavior occasioned by the rules.

Toward a triarchic theory of human intelligence

This article is a synopsis of a triarchic theory of human intelligence. The theory comprises three subtheories: a contextual subtheory, which relates intelligence to the external world of the individual; a componential subtheory, which relates intelligence to the individual's internal world; and a two-facet subtheory, which relates intelligence to both the external and internal worlds. The contextual subtheory defines intelligent behavior in terms of purposive adaptation to, shaping of, and selection of real-world environments relevant to one's life. The normal course of intelligent functioning in the everyday world entails adaptation to the environment; when the environment does not fit one's values, aptitudes, or interests, one may attempt to shape the environment so as to achieve a better person-environment fit; when shaping fails, an attempt may be made to select a new environment that provides a better fit. The two-facet subtheory further constrains this definition by regarding as most relevant to the demonstration of intelligence contextually intelligent behavior that involves either adaptation to novelty, automatization of information processing, or both. Efficacious automatization of processing allows allocation of additional resources to the processing of novelty in the environment; conversely, efficacious adaptation to novelty allows automatization to occur earlier in one's experience with new tasks and situations. The componential subtheory specifies the mental mechanisms responsible for the learning, planning, execution, and evaluation of intelligent behavior. Metacomponents of intelligence control one's information processing and enable one to monitor and later evaluate it; performance components execute the plans constructed by the metacomponents; knowledge-acquisition components selectively encode and combine new information and selectively compare new information to old so as to allow new information to be learned.

Précis ofDeduction

How do people make deductions? The orthodox view in psychology is that they use formal rules of inference like those of a “natural deduction” system.Deductionargues that their logical competence depends, not on formal rules, but on mental models. They construct models of the situation described by the premises, using their linguistic knowledge and their general knowledge. They try to formulate a conclusion based on these models that maintains semantic information, that expresses it parsimoniously, and that makes explicit something not directly stated by any premise. They then test the validity of the conclusion by searching for alternative models that might refute the conclusion. The theory also resolves long-standing puzzles about reasoning, including how nonmonotonic reasoning occurs in daily life. The book reports experiments on all the main domains of deduction, including inferences based on prepositional connectives such as “if” and “or,” inferences based on relations such as “in the same place as,” inferences based on quantifiers such as “none,” “any,” and “only,” and metalogical inferences based on assertions about the true and the false. Where the two theories make opposite predictions, the results confirm the model theory and run counter to the formal rule theories. Without exception, all of the experiments corroborate the two main predictions of the model theory: inferences requiring only one model are easier than those requiring multiple models, and erroneous conclusions are usually the result of constructing only one of the possible models of the premises.

A conditional model of evidence-based decision making

RATIONALE, AIMS AND OBJECTIVES

Efforts to describe how individual treatment decisions are informed by systematic knowledge have been hindered by a standard that gauges the quality of clinical decisions by their adherence to guidelines and evidence-based practices. This paper tests a new contextual standard that gauges the incorporation of knowledge into practice and develops a model of evidence-based decision making. Previous work found that the forecasted outcome of a treatment guideline exerts a highly significant influence on how it is used in making decisions. This study proposed that forecasted outcomes affect the recognition of a treatment scenario, and this recognition triggers distinct contextual decision strategies.

METHODS

Twenty-one volunteers from a psychiatric residency programme responded to 64 case vignettes, 16 in each of the four treatment scenarios. The vignettes represented a fully balanced within-subjects design that included guideline switching criteria and patient-specific factors. For each vignette, participants indicated whether they endorsed the guideline's recommendation.

RESULTS

Clinicians used consistent contextual decision strategies in responding to clearly positive or negative forecasts. When forecasts were more ambiguous or risky, their strategies became complex and relatively inconsistent.

CONCLUSION

The results support a three-step model of evidence-based decision making, in which clinicians recognize a decision scenario, apply a simple contextual strategy, then if necessary engage a more complex strategy to resolve discrepancies between general guidelines and specific cases. The paper concludes by noting study limitations and discussing implications of the model for future research in clinical and shared decision making, training and guideline development.

Reviving inert knowledge: analogical abstraction supports relational retrieval of past events

We present five experiments and simulation studies to establish late analogical abstraction as a new psychological phenomenon: Schema abstraction from analogical examples can revive otherwise inert knowledge. We find that comparing two analogous examples of negotiations at recall time promotes retrieving analogical matches stored in memory-a notoriously elusive effect. Another innovation in this research is that we show parallel effects for real-life autobiographical memory (Experiments 1-3) and for a controlled memory set (Experiments 4 and 5). Simulation studies show that a unified model based on schema abstraction can capture backward (retrieval) effects as well as forward (transfer) effects.

Cognitive emulation in expert system design

Cognitive emulation is an expert system design strategy which attempts to model system performance on human (expert) thinking. Arguments for and against cognitive emulation are reviewed. A major conclusion is that a significant degree of cognitive emulation is an inherent feature of design, but that an unselective application of the strategy is both unrealistic and undesirable. Pragmatic considerations which limit or facilitate the viability of a cognitive emulation approach are discussed. Particular attention is given to the conflict between cognitive emulation and established knowledge engineering objectives, detailed over 12 typical expert system features. The paper suggests circumstances in which a strategy of cognitive emulation is useful.

Cognitive emulation in expert system design

Cognitive emulation is an expert System design strategy which attempts to model System performance on human (expert) thinking. Arguments for and against cognitive emulation are reviewed. A major conclusion is that a significant degree of cognitive emulation is an inherent feature of design, but that an unselective application of the strategy is both unrealistic and undesirable. Pragmatic considerations which limit or facilitate the viability of a cognitive emulation approach are discussed. Particular attention is given to the conflict between cognitive emulation and established knowledge engineering objectives, detailed over 12 typical expert System features. The paper suggests circum-stances in which a strategy of cognitive emulation is useful.