Cognitive Psych: Exam #3 Flashcards
Semantic memory definition
a vast repository of knowledge, facts and general information
Benefits of categorization
1) reduces the complexity of the environment
2) reduces the need for constant learning
3) can guide you on what your next actions should be
4) enables the ordering and relation of classes of projects and events (ex: superordinate / subordinate)
Superordinate definition
broader category
- items at this level have few features in common
Subordinate definition
more specific
- items at this level have lots of features in common
Categorization task definition
Items appear on a screen and you have to sort them into categories - you are not told the rule but receive feedback on whether you are correct or wrong.
Types of rules
1) disjunctive: use the logical “OR” to relate stimulus attributes (ex: a bird has feathers or can fly)
2) conjunctive: use the logical “AND” to relate stimulus attributes (ex: a bird has feathers and can fly)
Rule learning definition
Give participants the relevant attributes and have them learn the rule
Attribute learning
Give participants the relevant attributes and have them learn the rule
Critiques of the Categorization Task paradigm
1) task if artificial: things do not fit into perfect boxes in the real world
2) many items within a category share some attributes but not all
3) categories vary along continuous dimensions
4) Doesn’t capture hierarchal information
5) doesn’t capture typicality
Characteristics of natural categories
1) hierarchal
2) typicality
Study on natural categories and hierarchies
participants listed features for items presented – wanted to see how many features you could come up with at the superordinate, basic and subordinate levels
results: very few shared attributes at the superordinate levels but it increases as you move down the hierarchy (get more specific) – it is hard to come up with features that encapsulate ALL elements of a category
Basic level categories are…
The most differentiated: avoid the extreme of sharing too many or two few attributes
- we probably learn these first
- carries the most information: best cognitive economy and highest cue validity (it is what we think of first when we think of the category – we say “dog” when presented with a picture of a dog not the specific breed or the general category “animal”)
Role of expertise in categorization
if you are more experienced with items presented you are faster in all category levels (basic is usually fastest but here is basic AND subordinate)
Typicality definition
some items are more representative of a category than others
Hypothesis for typicality of categories
typical exemplars share many features of the category
- Study: items rated most typical share the most features with other members
- good for discrete categories but not continuous
Multidimensional scaling
rate how similar the following pairs are – map results onto a graph (more similar items are closer)
benefits of multidimensional scaling
1) typically outperforms the standard similarly ratings
2) provides a visual depiction that may lead to new insights
prototype definition`
category example that has the average attribute values (best representation of a category member)
Prototypes and phenomes
phonemes: variation across how we say syllables
study: you have to say when a sound switches from I to Y
conditions:
- P condition: comparison contains the prototype
- NP: comparison does not contain the prototype
results: if you play the prototype (P condition) you are not able to detect the change
Animals and prototypical representation
they do not do this - only humans
Exemplar rule of protoypes
You store every item of the category you have seen and compare it across the stimulus
- we do not use this method
Prototype rule
a strategy that selects the category whose prototype is most similar to the classified item
- only retrieving the prototype
- downside: lose breadth of the category (only retrieving the average)
- we use this method
When is each rule of prototypes used?
prototype rule: used more in early learning – when introduced to new things, usually only exposed to more prototypical patterns
- once you get better, you switch to exemplars to see the depth of a category (might be only used when the number of exemplars is relatively small)
Goal derived categories
a category that is formed to fulfill a specific goal
Theory -based categorization definition
The importance of features for category membership depends on the role those features play in the theory underlying membership
Theory -based categorization study
Given 2 features (remove X, Y, or Z) and see if the participants can still guess the category
Conditions:
-Given no background information
-Given a background story that connects X→ Y → Z
Results:
-When you are missing X (the first feature) in the background condition you are likely to say it is not a member of the correct category
- You have stored that the first feature is the critical and leads to the other ones (root principle)
we expect features to fit together in a meaningful way
How should we learn categories?
Study:
-Center condition: shown things close to a prototype (average of features)
-Coverage condition: Shown things from all around the spectrum → define little clusters along the extremes and pick from the center of those clusters
Results:
1) Your are best when given what you previously saw (if you saw something in coverage, you are better with a coverage rock and same with a center rock)
2) You do better overall when you had the coverage condition: you want to see all the items and how variable the category is
Categorization and age
5-8: usually pick the most extreme example
9-adults: pick the average followed by most diverse most often → you are picking the average / coverage condition
As you get older, you try to sample the category as much as you can
taxonomic relations
organization of concepts based on their similarity of features
Thematic relations
organization of concepts that appear in the same context
