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Communication of complex thoughts and emotions |
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meaning (level of language) |
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smallest meaningful unit (example: the s in "dogs" means more than one dog) |
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smallest significant sound unit |
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grammatical structure (level of language) |
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Defining properties of language |
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Structured (multiple levels), arbitrary, and generative |
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sound has no relation to meaning |
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can create infinite numbers of new sentences |
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Dictionary in your brain; around 50,000 words |
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large database of spoken language |
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language impairment after brain damage |
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can't come up with words; difficulty speaking |
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semantics and syntax problem |
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Hold sounds in STM, recognize wordss and retrieve from LTM, understand structure of sentence to get meaning, make inferences about the meaning |
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usually more than one possible interpretation; a main challenge of language |
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perceived phoneme is synthesis of visual and auditory input (ga, ba, da exmaple) |
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Phoneme restoration effect |
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perceive noise as phoneme consistent with word (legislature example); example of top down effects in speech perception |
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Word recognition (for where one word ends and the next begins) |
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Look for familiar patterns; more frequently used words are more easily recognized |
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Word recognition (for choosing which ambiguous word to use) |
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Activate all meanings of ambiguous words briefly, but quickly use context to resolve ambiguity |
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determining the syntax (grammatical structure of a sentence) |
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starts out with one structure, but then turns out to have another (The old train the young.) |
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a meaningful grouping of things |
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an individual member of a category |
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the mental representation that corresponds to knowledge of a category |
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categorizing things in the world |
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process of classifying that allows us to identify similarities and differences |
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Consequence of categories line experiment results |
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Rated lines in different groups as more different in length than they really are |
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Howard and Rothbart consequences of categories experiment |
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Two groups are told some good and some bad things about each group; people remember more bad things about other groups |
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Three theories of representing categories |
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Classical, probabilistic, and exemplar |
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Mental representation (classical view) |
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description of defining properties shared by all category members; anything with these properties is automatically considered a category member |
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Strengths of the classical view |
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Most efficient and clear category boundaries |
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Weaknesses of classical view |
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Hard to specify defining features (define chair example) and some things are more typical of category (represent category better than others |
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Prototype (probabilistic view) |
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average representation of a concept that includes all typical properties |
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Family resemblance (probabilistic view) |
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category members tend to share sets of features (each has some part of set) |
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Weaknesses of probabilistic view |
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Fuzzy category boundaries and "best" exemplars are supposed to be most typical category members but aren't in all contexts |
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Strengths of probabilistic view |
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Accounts for typicality effects (typical instances of a category are verified more quickly than less typical instances) |
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concept is a collection of known category members (exemplars) and representation is separate description of all exemplars; no average representation |
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Strengths of exemplar view |
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Can explain why classification is influenced by context and correlations |
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Weaknesses of exemplar view |
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Requires lots of memory and time to search through all stored exemplar; intuition (people are aware of having prototypes); doesn't explain how and why exemplars are grouped together into category; not very efficient |
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concepts can be based on goals; how well an object fits with the goal determines categorization |
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concepts are a part of our general knowledge; our theories about the world organize concepts; knowledge tells us which features are relevant for categorizing |
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want to attain some goal but don't know how to get there |
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starting condition (what you know at the outset) |
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Means of transforming conditions |
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steps you can take to get from givens to goal |
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situations/events preventing you from easily obtaining goal |
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clear initial conditions, well-specified goal, set of known means of transforming conditions |
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one or more aspects of the problem are not completely clear |
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one or more aspects of the problem are not completely clear |
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difficulty thinking about familiar objects in a non-standard way |
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changing representation of problem |
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systematic procedure guaranteed to lead to correct solution (time consuming, often too many possibilities) - ex. maze |
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strategy to guide search so that solution is likely but not guaranteed (less time consuming) |
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at each step try to find a move that takes you immediately closer to the goal |
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Working Backwards heuristic |
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find the last move the directly leads to the goal and then find the move before that and so on |
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Means-end analysis heuristic |
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compare your current condition with the goal, look at the difference (subgoal), then look at remaining difference and repeat |
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a similarity between features of two things that allows a comparison |
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very skilled performance in a particular domain (area of knowledge) |
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Chase and Simon chess experiment |
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Experts did much better on actual game positions but similar to the beginners on random positions; this showed that experts don't have a greater memory, they just use chunking |
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category for type of problem; structured knowledge for identifying problems of a given type; associated procedures for solving them; allows rapid categorization of problem type (top down processing) and working forward; (novices work backward from goal, experts work forward from problem schema) |
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generate lots of different types of ideas |
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Remote Associates Test (RAT) |
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tests fluency and flexibility (surprise line birthday example) |
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Four stages of the traditional view of creativity |
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preparation, incubation, illumination, verification |
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study area and formulate problem |
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put unsolved problem aside; unconscious problem solving |
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achieve insight into problem |
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make sure solution works; sometimes insights are wrong |
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how people should make decisions; rational |
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assign value (+,-) to each attribute; select choice with highest sum of values (class example) |
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pick an attribute, pick a criterion for that attribute, eliminate choices that don't meet the criterion, if choices still remain pick another attribute and repeat (restaurant example) |
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pick a subset of choices and pick the one in the subset that best meets your criteria (beer example) |
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If there is a lot of time use... |
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If there is time pressure use... |
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elimination by aspects or satisficing |
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for each choice, you calculate its expected value (value in the long run); EV = (Pi*Vi) |
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how a choice is presented |
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people make decisions based on utility of outcomes rather than value, framing (viewed as gain vs loss), and overestimation of rare events |
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Which types of decision making are normative? |
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additive model and expected value theory |
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Which types of decision making are non-normative? |
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elimination by aspects and satisficing |
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Says that people are sensitive to how a problem is framed, that people calculate utility rather than value, and that people overestimate rare events |
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elimination by aspects and satisficing |
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