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Concept Acquisition - Lecture Notes | PSY 304, Study notes of Psychology

Material Type: Notes; Professor: Waddill; Class: Psychology Of Learning And Memory; Subject: PSY Psychology; University: Murray State University; Term: Fall 2009;

Typology: Study notes

Pre 2010

Uploaded on 12/15/2009

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Inductive learning: Forming inferences. Not really conditioning.
What we learn from induction: Concepts, Categories, and
Language
CONCEPT ACQUISITION
When we learn concepts, (concept of food, what doggieness is
etc.) how do we learn it? Is it similar to associative learning
(conditioning)?
Yes (Hull, 1920): its just like simple associative learning, we come
to associate a particular response with a particular stimulus.
People learn rules of classification without realizing it. CC is the
same in that people are conditioned without realizing they are
being conditioned.
Ex. Hull’s Study: 6 lists of Chinese characters. Used non-
Chinese speakers. Each list exemplified a character based on
a particular radical (concept), which was like a shape that
was also seen in each list but had other stuff added to it.
Kind of like “Where’s Waldo.” Subjects were eventually able
to classify very accurately but they didn’t know why. They
didn’t know what rule they learned. In conditioning, you can
be conditioned without realizing it.
No (Bruner, 1956): It’s more complex than classical conditioning.
We use other kinds of things like hypotheses, we make
inferences, we test our hypotheses, and in conditioning, we don’t
do that.
Ex. Bruner’s Study: Did not tell his subjects that these were
all organized according to a particular radical. He used 81
different cards. The stimuli on the cards varied on 4
dimensions. They varied on the shape that was in the middle
of the card, by the color of the shape (3 different colors), and
the number of shapes in the middle of the card, and the
number of borders drawn around the edge of the card. When
you combine all those combinations, you get 81 different
combinations. He wanted to see how well people were able
to figure out what the rule was and classify them in the right
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Inductive learning: Forming inferences. Not really conditioning. What we learn from induction: Concepts, Categories, and Language CONCEPT ACQUISITION When we learn concepts, (concept of food, what doggieness is etc.) how do we learn it? Is it similar to associative learning (conditioning)? Yes (Hull, 1920): its just like simple associative learning, we come to associate a particular response with a particular stimulus. People learn rules of classification without realizing it. CC is the same in that people are conditioned without realizing they are being conditioned. Ex. Hull’s Study: 6 lists of Chinese characters. Used non- Chinese speakers. Each list exemplified a character based on a particular radical (concept), which was like a shape that was also seen in each list but had other stuff added to it. Kind of like “Where’s Waldo.” Subjects were eventually able to classify very accurately but they didn’t know why. They didn’t know what rule they learned. In conditioning, you can be conditioned without realizing it. No (Bruner, 1956): It’s more complex than classical conditioning. We use other kinds of things like hypotheses, we make inferences, we test our hypotheses, and in conditioning, we don’t do that. Ex. Bruner’s Study: Did not tell his subjects that these were all organized according to a particular radical. He used 81 different cards. The stimuli on the cards varied on 4 dimensions. They varied on the shape that was in the middle of the card, by the color of the shape (3 different colors), and the number of shapes in the middle of the card, and the number of borders drawn around the edge of the card. When you combine all those combinations, you get 81 different combinations. He wanted to see how well people were able to figure out what the rule was and classify them in the right

category. Sometimes he made it really easy, sometimes more complicated. He tested them on a variety of different kinds of concepts or rules. He found that people were able to determine what were members of the category and what weren’t. He found that people would form hypotheses and test them out. Bruner said that is NOT associative learning (conditioning), because in associative learning, you are simply learning stimulus response. Yes (Gluck & Bower, 1988): said Hull was right. They looked at concept learning from a neural network model (association strengths, spreading activation). They developed mathematical learning. They said that when things are associated with a particular concept, we get a stronger relationship in that semantic network, therefore we do have a network and when one thing lights up, it lights other things up (associations). Final Answer: It depends on what kind of concept you’re studying, and how you study and the material you study. How We Study Concept Acquisition (p.340) Selection Paradigm: Subject behaves more like a scientist and can select instances to test their current hypothesis. A set of items and say this belongs to a category, this does, this doesn’t, this does etc. Subjects pick a card at random and decide which category it goes in. Subjects begin to formulate an idea of what they think the answer is. This is a lot like 20 questions. Instances- Things that illustrate the concept. (+) Non-instances- things that don’t illustrate the concept (-) Reception Paradigm: Ss encounter instances and non-instances with little control over which they encounter. Participant sits there and has to receive the info from the researcher. Have very little control over what happens. Note: More real world concept learning because we don’t have a lot of control over what we encounter. Learning Concepts: Hypothesis Testing

  1. Schema: Generalized representation of a concept. Abstract rules for learning. We develop schemas from our experiences. Schemas are like the gist. WHEN WE DEVELOP SCHEMAS, WE USE A POWER FUNCTION. Schemas develop gradually. Prototype: the best representation of a certain thing. If something fits the prototype really well, it’s easy to decide if a dog is a dog or a cat is a cat etc etc. if it doesn’t fit, it takes longer to decide if it’s a member of a category.
  2. Exemplar (“example”) Theories: Not a prototype. Specific category instances that we have encountered that are stored in episodic memory. Ex. Your dog Fido is an exemplar of the category dog. Exemplars are like the exact detail. Exemplars can be recent. a. Ex. Judges who watch gymnasts warm up give them lower scores than judges who didn’t watch the warm up. They made exemplars of the individual persons performance in the warm-up. They compare your performance to the warm up performance and if you screwed up during the warm up, they will give you lower points during the real performance even if your real performance was perfect. How we know when things belong to a category: we search our episodic memory to find an exemplar that is similar to the new instance. Then we assume that the current instance belongs to the same category that best matches it. If there are several exemplars, the one that best matches the current instance, that’s the one that wins. In certain kinds of categories, you have to make exemplars (physicians, gymnastics judges, like a judge will score a gymnast with a 10 and then compare every other gymnast based on that first gymnasts score because the first gymnast is the example). Schema Theories: People represent the defining features of a category. Categorization: Compare current instance with schema Category inferences are bi-directional, two-way.

Causal Inference: We make assumptions about cause effect. We are trying to figure out what events lead to other events. Cause- Effect is directional. Ex. Susan is crying. Her boyfriend broke up with her. Cause-effect = Susan’s boyfriend broke up with her so she is crying. We are always trying to figure out why. If you assume there is always a cause for something, then you think you can figure out the cause and avoid it or produce. Unfortunately not everything is cause-effect. 3 categories of cues

  1. Statistical Cues: Contingency (if-then), if you do this, then this will happen. The probability that there will be a particular effect, given that the cause has occurred. Things that have higher probabilities of being preceded by another event we assume there is a causal effect relationship.
  2. Contiguity Cue: Closeness in the environment (spatial contiguity – two events occur close together in space because one of them is the cause of the other). Temporal contiguity- cause and effect occur close together in time because one of them caused the other to happen. Ex. Dog has just run through the kitchen, and you walk into the kitchen and see the garbage all over the floor. You assume it was the dog because he ran into the kitchen and you heard a crash. It might have been the dog. It could’ve been the cat or your son. But you assume that because 2 things are closely together in time, one thing caused the other. It doesn’t mean we are right about our assumptions on the cause of the effect. Researchers use both contingency and contiguity cues and one type is not always more important than the other. They are both very valuable.
  3. Kinematic cues: the cause and effect about certain kinds of information in the environment. Relative to movement or physics kinds of properties, change in the appearance of something. Look for things that would be expected in the laws of physics. This allows us to interpret what goes on in our world in a 2-D way.

Children often mispronounce to correction “Fis phenomenon” WR- sound is hard W for R “Wabbit” Language learning can occur without direct exposure speed of acquisition Bulk of acquisition occurs in about 3-4 yrs. Pattern of first language acquisition Single words used in meaningful ways (approx 1 year old) 2-word utterances (approx 18 mos) Telegraphic Speech: “milk all gone” “daddy bye bye” More Complex sentences emerge by 4yrs. Order unique to children acquiring