Cognition. Prof. Mike Dillinger

Transcription

1 Cognition Prof. Mike Dillinger 1

2 2

3 Inside LTM What does knowledge/meaning/information look like when it s IN LTM? Mental representation See Chapters 5, 6, 7, 8, 9 in the text [only 6, 8, 9 on exam] 3

4 Outline Kinds of long-term memory (LTM) - described in Ch 5, but important for the exam Kinds of long-term memory (summary Ch. 5) For facts Semantic memory For experiences Episodic memory For skills Procedural memory For images Visual memory Others? 4

5 Memory Codes Dual coding theory (Ch. 7) Paivio (1969, 1971): both verbal and visual codes are used to represent information Levels-of of-processing theory (Ch. 6) Craik & Lockhart: A mix of physical and conceptual codes are used to represent information 5

6 Inside LTM What does knowledge/meaning/information look like when it s IN LTM? Again, but now in more detail Focus on Explicit memory Methodologically easier to study Focus on Semantic memory Facts are basic units of knowledge In the bucket view of memory Concepts are the building blocks of facts A good place to start Very different from the behaviorists! 6

7 Semantic Memory (Ch. 8) Categorization Remembering by categorization Facts about categories Individual X is a (member of) category Y (true or false) LTM is a web of categories Semantic encoding / associative memory / semantic memory Bruner et al. (1956) Benefits of forming concepts / categories Reduces the complexity of the environment Identification Reduces need for constant learning Allows decisions re appropriate actions Enables structuring of knowledge 7

8 Semantic Memory (Ch. 8) What are concepts? ideas that refer to common characteristics of groups of individuals, not individuals Philosophers discuss two common ways of describing a concept: theintension [sic] of a concept (list of attributes) You give a conceptual definition, list of attributes, etc. and the examples are implicit theextension of a concept (list of individuals) You give or show some examples; the definition is implicit 8

9 Ch 8 Outline (1) I. Five Benefits of Forming Concepts (Bruner, Goodnow, Austin, 1956): A. Reduces complexity of the environment B. Identification C. Reduces need for constant learning D. Allows decisions re: appropriate actions E. Enables structuring of knowledge 9

10 Semantic Memory (Ch. 8) Concepts categories Hierarchical arrangement of categories Terminology Alert! higher categories = more abstract, more general, more common attributes superordinates, hyperonyms lower categories = more concrete, more specific, fewer common attributes subordinates, hyponyms Subsumption set-inclusion or contains relation: higher categories subsume/contain lower categories Semantic memory is a SEMANTIC NETWORK = A network of concepts/categories linked by subsumption (or is-a relations) [and probably other relations, too] 10

11 More general Edible things, Parts of plants, etc. Subordinates Superordinates Apple Fruit Pear Subsumption Subsumption Bosc Pear Bartlett Pear Red delicious apple Fuji apple More specific 11

12 H: If memory is organized hierarchically, then hierarchically organized presentation should make recall easier. organized presentation random presentation organized presentation random presentation Bower,

13 Ch 9 Outline (1) I. Organization and Recall Recall of Hierarchical Information: Bower, Clark, Winzenz, & Lesgold s (1969) hierarchical organization experiment Subjects were given the same information about minerals, plants, body parts, and instruments presented either in randomly organized hierarchies or in meaningful hierarchies. One of the meaningful hierarchies is shown on p. 216 of the text. Students remembered substantially more of the information when it had been presented in a meaningfully organized hierarchy. Meaningful: they remembered 65% after first trial and 100% after three study trials Random: they remembered less than 65% even after four study trials Chase and Ericsson's (1979) subject chunked random digits into units of 3 to 4 digits each (that represented running times) and increased his digit span to 70 items. 13

14 More general Are concepts / categories at a given level easier to remember or use? Superordinate category Basic categories are easiest to classify, except for domain experts. Fruit Basic category Domain experts can label things in basic or Apple subordinate categories just as quickly. Pear Subordinate category Fuji apple Red delicious apple Bartlett Pear Bosc Pear More specific 14

15 Semantic Memory (Ch. 8) Natural categories (~ natural concepts) Based on continuous dimensions not binary: not totally true/totally false Category membership is fuzzy Instead of in category or out of category.. family resemblance: more attributes in common So, some members of a category are better exemplars than others (ostrich vs. robin) ~ typicality Prototype Theory (Eleanor Rosch) Categories / concepts are arranged hierarchically (organized by subsumption) in the mind 15

16 A cup or a bowl? (Labov, 1973) 16

17 Which ones are cups? Which ones are mugs? Labov (1973) 17

18 What s beauty? 18

19 Ch 8 Outline (3) III. Natural Categories A. The Hierarchical Arrangement of Categories. 1. The highest level of the hierarchy, Superordinate categories, like "furniture" and "vehicles" are the most general. (Category members have little in common.) These categories are largest. 2. The next level in the hierarchy is the basic level. (Category members share many features and have few features in common with members of other basic level categories.) a. Basic-level categories are most differentiated. b. They are the first learned, and the most used in language (single words). c. Object verification is fastest for basic-level labels, e.g., Chair except for experts in their area of expertise. In area of expertise, equally fast at verifying subordinate membership as basic membership. d. Objects in categories can be represented by prototypes (average of category members). Averaged pictures of basic-level category members are identifiable. 3. At the lowest level in the hierarchy are subordinate categories. (Category members share lots of features with one another and they also share lots of features with other subordinate categories.) These categories are smallest. For example, "living room chair" and "dining room chair" are subordinate categories. B. Typicality and Family Resemblances 1. Typicality = how well a category member represents a category a. Typicality due to Family Resemblance b. More typical members have more in common with other members of category. c. Least typical have fewest attributes in common with other category members. 2. Not relevant to goal-derived categories (family resemblance does not predict goodness of membership; satisfaction of goal/ideal does) 3. Clinical diagnosis relies on these ideas about natural categories. a. Diagnostic categories are comprised of large sets of overlapping attributes -- patients are more or less typical of disorder. b. Encourages clinicians to expect diversity among patients with same diagnosis and to respond appropriately to individual differences. C. Person Perception -- Stereotypes are the result of exaggerated within-group similarity. D. Loss of Categorical Knowledge 1. Selective loss of knowledge of living vs. nonliving categories appears to be a result of loss of visual features vs. functional features. 2. Selective loss can occur within the category of living things, e.g., loss of ability to name animals while retaining ability to name fruits and vegetables. 19

20 More general Categorization Edible things, Parts of plants, etc. Fruit? Apple Pear Bosc Pear Bartlett Pear Red delicious apple Fuji apple 20 More specific

21 Semantic Memory (Ch. 8) Concept identification (~concept learning) How do people learn how to classify? Give information about in/out of category Given attributes > figure out the rule (rule learning) Ex: size and shape > large or a circle Given the rule type > figure out the attributes (attribute learning) Ex: conjunctive rule (~ and rule) > size and shape Give nothing > figure out both Assumes an individual either is or is not an exemplar of a concept. Based on simplistic, logical categories Categories / concepts are arranged hierarchically (organized by subsumption) in the mind 21

22 Ch 8 Outline (2) II. Concept Identification & Concept Learning A. Discovering Rules and Attributes - People solve concept identification problems by evaluating hypotheses - Hypotheses are abandoned when they are contradicted and new hypotheses are generated that fit the known information - Rule Learning (given relevant attributes, figure out the rule) - Attribute Learning (given a logical rule, figure out the attributes) B. Critique of the Concept Identification Paradigm 1. Artificially constructed categories consist of a small number of dimensions and a small number of attributes on each dimension. 2. Category membership is perfectly defined by one of several logical rules. 3. Thus, an exemplar could be classified unequivocally as either a member or nonmember of the artificial category. 4. Eleanor Rosch and her colleagues 's a. Traditional concept formation research "missed the boat" in one especially critical way, having to do with the nature of the concepts people were expected to acquire in traditional experiments. b. Natural categories tend to be composed of continuous dimensions and are hierarchically organized. c. Natural categories are not composed of equally good members (some members are more representative of the category than others). 22

23 Concept learning (Reed, 1973) < category 1 (extension) < category 2 (extension) What categories do these go in? 23

24 Concept learning How do people do this categorization task? 24

25 Concept learning Theory-based categorization Using intensional descriptions Coherent categories Have features or attributes that can be related easily Easier to learn Relations between features are important ~ Structural theories of perception ~ Structural theories of knowledge/information 25

26 Ch 8 Outline (4) IV. Categorizing Novel Patterns A. Categorization Models 1. Nearest-neighbor rule = compare new stimulus to all members of relevant categories, assign to category containing most similar member. Disadvantage is that although the new stimulus is compared to all other category members, only one is used to make decision. 2. Average-distance rule = compare new stimulus to all members of relevant categories, compute similarity to each member of each category, sum similarities to each category, divide by number of comparisons, assign to category with highest average. a. Advantage = uses all category members as basis for decision b. Disadvantage = must compute average similarity as well as comparing novel stimulus to all category members 3. Prototype rule = For each category, create a mental representation of a prototypical ("best") member of the category and compute similarity between prototypes and novel stimulus. Assign to category that has the most similar prototype. a. Advantage = only a few comparisons are necessary b. Disadvantage = how to handle noncontinuous attributes, e.g., marital status? 4. Feature-frequency rule = Compare a novel stimulus to all members of relevant categories. Count how many features each category member and the novel stimulus have in common. Add up feature counts for each category and assign to category with highest feature count. a. Disadvantage = lots of calculations b. Advantage = no problem with discontinuous dimensions Hayes-Roth and Hayes-Roth (1977) have found that the feature frequency model is a good predictor of classifications. B. Evaluation of Categorization Models 1. Nosofsky s goal is to explain all categorization effects using exemplar models. 2. Other theorists place emphasis on how the categorization task influences people s strategies. Category experience influences whether a prototype or exemplar classification rule is applied. C. Theory-based Categorizations 1. Using theories about real-world to make categorization decisions 2. People tend to pay more attention to features that provide causal explanations for category membership. It is easier to learn to classify objects that appear to be coherent (make sense given prior knowledge of the world) than objects that appear to be incoherent (don t make sense given what one knows about the world). 26

27 from LTM Getting information OUT OF LTM ~ retrieval from LTM (to WM) remembering Retrieval Recall tasks Free Recall» What did you see? Probed, cued or prompted recall» What fish did you see?» Neutral questions vs leading questions» Massaging the data on output, too 27

28 Retrieval (Ch. 5) Tip-of-the-tongue Phenomenon I know, but I just can t say it yet. Cues help (sounds like, first letter is ) More frequent with age (not a sign of dementia!) Activation without retrieval Eyewitness Identification Unreliable: frequency of previous pictures/information leads to false positives Cognitive interviews are more informative Techniques to promote retrieval Remember the situation, report everything (without interruptions), recall the events in different orders, recall from different points of view Recall under hypnosis is controversial 28

29 Encoding ~ retrieval Working Memory Central Executive Encoding Long-term Memory Auditory Sensory Store (Phonological loop) Short-term term The Encoding Specificity Principle Memory Transfer-appropriate processing Visual Sensory Store (visuo-spatial sketchpad) Search Sensation Perception Attention Retrieval 29

30 Ch 6 Outline (3) IV. Encoding Specificity and Retrieval A. Encoding Specificity Principle 1. Some retrieval cues are better than others. a. Memory traces differ in the kinds of information they contain. b. Even if encoding is held constant, differences in recall occur. c. Encoding and retrieval interact (must match for best recall). 2. Mood-dependent memory is an example. B. Interaction between Encoding and Retrieval Operations 1. Thompson and Tulving s (1970) demonstration that recall can exceed recognition a. Students were asked to memorize paired associates in which the cue words were only weakly associated with the target words, e.g., country OPEN. b. Next they were given a list of words which are strongly associated with the original target words, e.g., shut (a close associate of "open") and asked to write down the first four words they thought of for each of the strongly associated cues. c. Then they were asked to circle all of the associates they had generated which had appeared as targets on the original list. - Recognition was poor. The change in context/elaboration failed to serve as an effective cue for accessing the stored information. d. Last, the subjects were provided with the original cues/weak associates and asked to recall the original TARGET words. - Recall was excellent. Reinstating the initial context/elaboration made recall better than recognition. 2. Light and Carter-Sobell's (1970) recognition experiment a. Adjective-noun pairs were capitalized in sentences, e.g., The TREE had dappled BARK. b. Recognition test required subjects to determine whether a noun had been on the sentence list. c. At test, the nouns were presented alone, with the same adjective or with a different adjective (e.g., dog bark). d. Recognition was best with the same adjective and worst with the different adjective. 3. Fisher and Craik's (1977) study of the effect of similarity between encoding context and retrieval cue was directed toward answering the question -- does deeper encoding always result in better memory? a. Subjects were given an incidental learning task that emphasized either semantic or phonemic encoding of words. b. At retrieval, subjects were either presented with the identical context in which they had encountered the word earlier, e.g., "Associated with boot?" or "Rhymes with blue?;" a similar context, e.g., "Associated with sandal?" or "Rhymes with grew?;" or a different context, i.e., phonemic if semantic originally or vice-versa. c. On average, recall in the identical context was greater than recall in the similar context which, in turn, was greater than recall in thedifferent context. 30

31 Take-away for Semantic Memory Semantic memory is made up of (in part!): Categories (or concepts) True/false categories, or Fuzzy ( natural ) categories (Prototype theory) Exemplars are more or less typical That are organized hierarchically One category includes (or subsumes) another Based only on the inclusion or subsumption relation between categories/concepts The process of linking an individual with its category (called categorization ) Promotes long-term memory Ex: Fido is a dog Is a basic fact Semantic memory is like a network of facts 31

32 Questions? 32