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Problem solving

Problem solving. Problem solving: cognitive processes focused on achieving a specific goal. Strategies of problem solving: Trial and error, algorithms and heuristics Ill-defined vs. Well-defined problems. Heuristics vs. algorithms.

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Problem solving

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  1. Problem solving Problem solving: cognitive processes focused on achieving a specific goal. Strategies of problem solving: Trial and error, algorithms and heuristics Ill-defined vs. Well-defined problems.

  2. Heuristics vs. algorithms • Heuristics: general problem solving strategies that are often useful but not always effective (in football: control line of scrimmage, avoid turnovers, in chess: control center of board.) • Algorithms: step by step procedures guaranteed to solve a specific problem (recipe to bake a cake, formula to solve for area of triangle)

  3. Examples of Heuristics • 1. Means-end analysis: breaking problem down into series of sub-problems. • 2. Analogies: using past experience as model for current problem-solving • Research on use of analogies (past experience) contradictory.

  4. When is past experience harmful? • Dunker (1945) Make a lamp problem.

  5. 2. Functional Fixedness: thinking of an object as only functioning in its usual way Can you use these supplies to mount the candle on the wall so that it can be lit in a normal way without toppling over? Thinking—Five Key Barriers to Problem Solving

  6. To overcome functional fixedness, think of the matchbox, tacks, and candle all functioning in new ways. Thinking—Five Key Barriers to Problem Solving (Functional Fixedness Continued)

  7. When is past experience harmful? • Mental set: retaining a old successful problem-solving procedure even though it is not effective in its current context. Water jar example here!

  8. Experimental testing for mental set: Luchin’s (1942) water jar problem:

  9. When is past experience helpful to problem solving? • 1. Gick & Holyoak (1980) studies of problems solving with and without past experience • 2. Chi’s (1985) studies of expertise and problem solving

  10. Problem solving in Physics professors vs. students: Problem categorization

  11. Problem solving in Physics professors vs. students: Problem categorization

  12. Problem solving in Physics professors vs. students: Problem categorization

  13. Newell & Simon: General problem solver (GPS); first attempt at a software program designed as an all purpose problem solver. • Key concepts: • Problem space • Means –end analysis • Current state vs. desired state

  14. Thinking—Creativity • Creativity :ability to produce valued outcomes in a novel way • Three elements of creativity: • Originality • Fluency • Flexibility

  15. Thinking—Creativity • Divergent Thinking: ability to produce many alternatives or ideas; linked to creativity (e.g., reordering the letters “grevenidt” to form many new words) • Convergent Thinking: attempting to find one correct answer; linked to conventional, non-creative thinking (e.g., 2 + 2 = ?)

  16. Experts and brain level • fMRI of experts (A) and novices (B) engaged in face portrait drawing task.

  17. What Is Intelligence? Historical views of intelligence: 1. Single ability or general factor called “g” (Spearman) 2. Multiple abilities (Thurstone and Guilford) 3. Single ability with two types of g,fluid and crystallizedintelligence (Cattell) 4. Multiple abilities (Gardner and Sternberg)

  18. Intelligence as processing speed • Also can be measure with Posner task A-a match time Low IQ take 25-30ms longer • First Inspection time=sensory discrimination • Second Posner time=stm/ltm access Test stimulus 30-200ms Mask – L or R? shortest time needed to reliably make distinction?

  19. Intelligence Models • Gardner • Sternberg

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