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Published byDerrick Eaton Modified over 9 years ago
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* Problem solving: active efforts to discover what must be done to achieve a goal that is not readily attainable
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* Problems of inducing structure: relations among numbers, words, symbols, ideas * Problems of arrangement: arranging parts of a problem to fit some criterion---solved through insight: sudden discovery of the correct solution following incorrect attempts based on trial and error
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* Problems of transformation: carry out a sequence of transformations in order to reach a specific goal
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* Well-defined problems: problems in which the initial state, the goal state, and the constraints are clearly specified * Ill-defined problems: one or more elements among the initial state and the constraints are unclearly specified
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* Irrelevant info * Functional fixedness: the tendency to perceive an item only in terms of its most common use * Mental set: when people persist in using problem solving strategies that have worked in the past * Unnecessary constraints
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* Algorithm: methodical, step-by- step procedure for trying all alternatives * Like trial and error * Heuristic: a guiding principle used in solving problems or making decisions * A “rule of thumb”
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* Forming subgoals: intermediate steps * Working backward: easy w/problem w/well specified end-point * Searching for analogies * Changing the representation of the problem: change the way you look at a problem
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* Field dependence-independence: tendency to rely primarily on external versus internal frames of reference when orienting yourself in space * Field dependent rely on external frames of reference * Field independent can restructure problem more easily
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* DEF: evaluating alternatives and making choices among them * Theory of bounded rationality: asserts that people tend to use simple strategies in decision making that focuses on only a few facets of available options and often result in “irrational” decisions that are less than optimal
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* Decisions involve choices about preferences * Additive strategy: list attributes that influence a decision * Compensatory decision models: allow attractive attributes to compensate for unattractive attributes * Involve elimination by aspects strategy * Noncompensatory decision models: do not allow some attributes to compensate for others * Used when more options and factors are added to a decision task
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* Risky decision making: making choices under conditions of uncertainty * Expected value: do you expect to gain or lose * Subjective utility: is it personally worth it to you * Subjective probability: sometimes you need to rely on your personal estimates of probabilities
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* Availability heuristic: involves basing the estimated probability of an event on the ease of with which relevant instances come to mind * Recalling specific instances of an event
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* Representativeness heuristic: basing the estimated probability of an event on how similar it is to the typical prototype of that event
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* People underestimate risks or probabilities * “It won’t happen to me”
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* DEF: when people estimate that the odds of two uncertain events happening together are greater than the odds of either event happening alone
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* DEF: when people’s belief about whether an outcome will occur changes depending on how alternative outcomes are distributed, even though the summed probability of the alternative outcomes is held constant
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