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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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Definition
| 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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Definition
| 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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Definition
| 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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Definition
| 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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Definition
| 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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Definition
| 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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Definition
| additive model and expected value theory |
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| Which types of decision making are non-normative? |
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Definition
| 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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Definition
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Definition
| elimination by aspects and satisficing |
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