Language and Thought

1. Language andThought

2. Language • Language is a form of communication in which sounds and symbols are combined according to formal rules • Phonemes are the basic speech sounds (English has 40-50 phonemes) • Morphemes are the smallest meaningful units of language • Grammar provides rules for a language • Syntax refers to the rules for word order in a sentence • Semantics refers to a system of using words to create meanings

3. Language & Thought • Whorf’s linguistic relativity hypothesis theorizes that language determines our perceptions of reality • Researchers suggest that language influences the nature of one’s thought

4. Language Development • Prelinguistic stage- begins with reflexive cry, then crying becomes more purposeful • Cooing- producing vowel-like sounds • Babbling- adding consonants to vowels • Linguistic stage- babbling begins to sound more like the language in the child’s home • Overextension • Telegraphic speech • Overgeneralization

5. Theories of Language Development • Is language capability innate or learned (Skinner v. Chomsky… Behaviorism v. Nativist)? • Language Acquisition Device- an innate mechanism, hypothesized by Chomsky, that enables a child to analyze language and extract the basic rules of grammar • Most researchers believe that language acquisition is a combination of nature and nurture (Interactionist).

6. Animal Language • Animals are capable of limited communication • Language in animals is not comparable to human language • Apes lack appropriate vocal cords for generation of speech • Apes can be trained to use non-vocal sign language • Washoe acquired American Sign Language • Dolphins can be trained to respond to hand signals and to vocal commands • Animal language lacks complexity and syntax

7. Language and the Brain • There may be critical periods of language development • Broca’s area is involved in speech and language production • Supramarginal gyrus combines word meaning with the production of words

8. Thinking • The processing of information to solve problems and make judgments and decisions

9. The Journey… • Problem Solving • Thinking Under Uncertainty • Intelligent Thinking

10. Problem Solving PROBLEM: • A situation in which there is a goal, but it is not clear how to reach the goal • A well-defined problem is one with clear specifications of the start state (where you are), goal state (where you want to be) and the processes for reaching the goal state (how to get there) • An ill-defined problem is a problem lacking clear specification of the start state, goal state, or the processes for reaching the goal state

11. Problem Solving Involves two steps... Interpreting the problem Trying to solvethe problem

12. Blocks to Problem Solving Interpretation blocks • Fixation is the inability to create a new interpretation of a problem • For instance, in the 9-dot problem, the directions do not say one cannot go “outside” the mental square formed by the 9 dots

13. Blocks to Problem Solving Interpretation blocks • Functional fixedness is the inability to see that an object can have a function other than its typical one • For example, if you need a screwdriver but don’t have one, a dime could be used to serve the purpose of a screwdriver • Limits our ability to solve problems that require using an object in a novel way • To combat functional fixedness, you should systematically think about the possible novel uses of all the various objects in the problem environment

14. Blocks to Problem Solving Strategy blocks • Our past experience with problem solving can lead us to mental set, the tendency to use previously successful solution strategies without considering others that are more appropriate for the current problem • Sometimes when searching for new approaches to a problem, we may experience insight, a new way of interpreting a problem that immediately gives you the solution

15. Overcoming Blocks • To combat the blocks in problems solving, ask yourself questions such as: • Is my interpretations of the problem unnecessarily constraining possible solutions? • Can I use any of the objects in the problem in novel ways to solve the problem? • Do I need a new type of solution strategy?

16. Solution Strategies Algorithm Heuristic

17. Algorithm • A step-by-step procedure that guarantees a correct answer to a problem • For example, using multiplication correctly guarantees you the correct solution to a multiplication problem

18. Heuristic • A solution strategy that seems reasonable given your past experiences with solving problems, especially similar problems • May pay off with a quick correct answer, but it may lead to no answer or an incorrect one

19. Types of Heuristics • Theanchoring and adjustment heuristic uses an initial estimate as an anchor and then this anchor is adjusted up or down • For instance, when meeting a new person, your first impression forms an anchor of that person, and you may not process subsequent information about that person as fully as it should be processed

20. Types of Heuristics • The working backwardheuristic is attempting to solve a problem by working from the goal state backward to the start state • For instance, consider the following situation: Water lilies growing in a pond double in area every 24 hours. On the first day of spring, only one lily pad is on the surface of the pond. Sixty days later, the entire pond is covered. On what day is the pond half covered?” • If you work backward with the fact the pond is completely covered on the 60th day, you can solve this question easily…half of the pond must be covered on the 59th day.

21. Types of Heuristics • Themeans-ends analysis heuristic is breaking down the problem into subgoals and working toward decreasing the distance to the goal state by achieving these subgoals • For example, when trying to write a major term paper, students should be encouraged (and perhaps shown) how to break down this big task into smaller tasks that, when completed, will result in a final, large term paper

22. The Tower of Hanoi Problem

23. Algorithms vs. Heuristics • When going through a new grocery store looking for pickles, you could go up and down every aisle, examining each product until you found the pickles • This would be using an algorithm • Or, you could look at the signs above the aisles and look for the word “Condiments” and assume that pickles will be on that aisle • This would be using a heuristic

24. Probability and Uncertainty • The probability of an event is the likelihood that it will happen • Probabilities range from 0 (never happen) to 1 (always happens) • An event with 0.5 probability of occurring is maximally uncertain because it is equally likely to occur and not to occur • In addition to judging the uncertainty of events in our environment, we attempt to reduce our uncertainty about the world by trying to find out how various events are related to each other

25. Judging Probability Two main heuristics we use to make judgments about probabilities... The Represen-tativeness Heuristic TheAvailabilityHeuristic

26. The Representativeness Heuristic • A rule of thumb for judging the probability of membership in a category by how well an object resembles (i.e., is representative of) that category • The more representative the object is, the more probable • You hear about a person who likes to write, read, and interpret poetry. Is it more likely that this person is: • A hockey fan? OR • An English professor who likes hockey? • We tend to use the representativeness heuristic because the mind categorizes information automatically

27. The Conjunction Fallacy • The conjunction rule states that the likelihood of the overlap of two uncertain events cannot be greater than the likelihood of either of the two events because the overlap is only part of each event • The conjunction fallacy, which can occur when we use the representativeness heuristic, is incorrectly judging the overlap of two uncertain events to be more likely than either of the two events