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Complex Learning Tasks
Chapter 12
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Concept Learning Concept For example, think of an airplane:
2 Concept A symbol that represents a class of objects or events with common properties. For example, think of an airplane: Have fixed wings Are heavier than air Are driven by a screw propeller or high velocity rearward jet Are supported by the dynamic reactions of the air against the wings These concepts allow us to easily identify these objects as airplanes.
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3 Concept learning significantly enhances our ability to effectively interact with the environment. Rather than separately labeling and categorizing each new event or object, we incorporate it into our existing concepts.
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Well Defined Concepts Types of Rules Attribute Rule
4 Attribute Any feature of an object or event that varies from one instance to another. Rule A rule defines the objects or events that are examples of a particular concept. Types of Rules Affirmative rule A rule that specifies that a particular attribute defines a concept. Negative rule A concept is defined by the rule that any object or event having a certain attribute is not a member of the concept.
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Studying Concept Learning in Humans
5 Smoke (1933) conducted studies examining concept learning in humans. He presented subjects with a large number of figures that differed in shape, size, number, and location of their dots. Subjects’ task was to learn the concept of DAX, which consisted of a circle with one dot inside and another dot outside.
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There are degrees to which particular items fit a concept.
7 Conjunctive rule The simultaneous presence of two or more attributes that define a concept. Disjunctive rule When the concept is defined by the rule that the concept can possess either or both of the two common attributes. Not all examples of a concept necessarily have all the attributes characteristic of that concept. There are degrees to which particular items fit a concept.
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Fuzzy Concepts Family resemblance Prototype
8 Family resemblance The degree to which a member of a concept exemplifies the concept. Prototype Object with the greatest number of attributes that are characteristic of the concept. Chair is the most typical prototype of furniture.
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Who’s sexier?
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A German Shepherd may fit the concept of dog more than a poodle.
10 A German Shepherd may fit the concept of dog more than a poodle. The more an object or event differs from the prototype, the more difficult it is to identify it as an example of the concept.
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Multiple Concepts 11 Two objects or events may share certain attributes but not be examples of the same concept. Although a robin and a bat both have wings, a robin is a bird and a bat is a mammal. We do not always know the boundaries that define a concept.
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Study of Concept Learning in Animals
12 Concept learning involves identification of the properties that characterize a concept as well as those that do not. Herrnstein et al. (1976) found that pigeons demonstrated concept learning. Trick is to use a large number of very different examples D’Amato and Van Sant (1988) found that monkeys could learn the concept of humans. Vonk and MacDonald found that a female gorilla could learn to discriminate between primate and non primate animals. Animals can also learn the concepts of same and different.
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Cook & Blaisdell (1996) 13
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Theories of Concept Learning
14 Hull (1920) envisioned concept learning as a form of discrimination learning. Said that concepts have both relevant and irrelevant attributes. As a result of reinforcement, response strength increases to the attributes characteristic of the concept. Same/Different judgements require an abstract code or rule, so the theory fails here.
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Abstract Concepts 15 Bruner, Goodnow, and Austin (1956) suggested that a concept is learned by testing hypotheses about the correct solution. If the first hypothesis is correct, the individual has learned the concept. If it is incorrect, another hypothesis will be generated and tested, and this will be repeated until the correct solution is discovered. Research by Levine (1966) suggests that individuals do engage in hypothesis testing of concepts.
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Two Ways of Knowing 16 However, a concept can be learned via associative learning or hypothesis testing, which are not necessarily mutually exclusive. A concept can be learned using either method, but a concept is learned best when both methods are employed.
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TOM Concept or Discrimination?
17 Theory of Mind: Understanding that others have mental processes that may differ from one’s own. Emotions Knowledge Visual Perspective 17
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Knowledge Attribution
19 Povinelli (1991) Knower – sees food being hidden Guesser – outside of room Stage 1: As above Stage 2: Knower wears hat Stage 3: Guesser stays in room with a bagged head 19
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Chimpanzees (Great Apes) Rhesus Monkeys (New World)
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Alternative 21 Did chimps discriminate between the two situations based on subtle differences in how the “guesser” and “knower” acted? Maybe they choose the one with eyes open during hiding?
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“Begging Experiment” Povinelli (1999)
22 Povinelli (1999) Beg from “seeing” vs. “nonseeing” Front vs. Back – Yes Pail Beside vs. Over Head - No Averted Eyes vs. Over Shoulder Look – No Blindfold Mouth vs. Blindfold Eyes - No 22
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“Chimps Fail Begging Experiment”
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“Elephants Pass Begging Experiment”
24 However, this doesn’t imply elephants can “mind-read” 24
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Mark Test 25 Gallup’s Mark Test (Great Apes) 25
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The Nature of the Problem
26 Problem A situation in which a person is motivated to reach a goal, but some obstacle(s) block the attainment of the goal. Thorndike (1898) proposed that animals and people solve problems by trial and error.
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Insight or Trial and error?
27 Kohler (1925) suggested a different view of problem solving Says that an animal internally or mentally explores the problem before exhibiting a specific response. The exploration involves considering and rejecting possible solutions and finally developing insight as to the correct solution. But…..only Chimps with certain past experiences solved the banana problem
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Insight: What is it? Insight Initial state Goal state
28 Insight A sudden realization of how to solve a problem. Kohler found that once the subjects solved the problem, they were able to quickly solve other similar problems. Initial state The starting point of a problem. Goal state The desired endpoint of a problem. Two additional processes: Identify the operations that solve the problem. Restrictions limit what you can do.
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Well or Ill? Well-defined problem Ill-defined problem
29 Well-defined problem A problem with clear initial and goal states. Ill-defined problem A problem with no clear starting or end point. Creating a set of manageable subproblems provides the structure for converting an ill-defined problem into a well-defined one.
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A Strategy for Solving Problems
30 After the problem has been defined, the next step is to develop a plan of attack. There are two major strategies—algorithms and heuristics—that can be used to solve problems. Algorithm A precise set of rules to solve a particular problem. Heuristic A “best guess” solution to problem solving.
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Working backward heuristic
31 Working backward heuristic A technique for finding the solution to a problem by starting with the end point and working back to the start point. Is often used in mathematical and other formal systems of analysis. Means-end analysis Breaking a particular problem into a series of solvable subproblems.
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Means Ends Analysis? Learning a) allows the bird to solve b)
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Consequences of Past Experience
34 Functional fixedness Difficulty recognizing novel uses for an object. Prior experience using an object to solve one problem makes it difficult to recognize that the same object can be used in a different manner to solve another problem. Reflects rigidity that can impair problem solving; however there are ways to overcome functional fixedness.
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Mental Sets 35 The tendency to use an established method for solving problems. Sets may blind people to fresh ways of exploring problems, which is unproductive when other solutions are more efficient.
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