1 / 17

Problem-Solving Techniques and Factors that Influence Effectiveness

Explore problem-solving techniques such as algorithms and heuristics, as well as factors that impact their effectiveness, including problem representation, mental set, and functional fixedness.

brianah
Download Presentation

Problem-Solving Techniques and Factors that Influence Effectiveness

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. WHS AP Psychology Unit 7: Cognition Essential Task 7-2: Identify problem-solving techniques (algorithms and heuristics) as well as factors that influence their effectiveness (problem representation, mental set and functional fixedness). 

  2. Algorithms Heuristics Representativeness Heuristic Compensatory Models We are here Decision Making Techniques Problem Solving Techniques Availability Heuristic Unit 6: Cognition Obstacles to Problem Solving Obstacles to Decision Making Biological Factors Memory Acquisition and use of Language Information Processing Model Encoding Storage Retrieval Cultural Factors Cognitive Factors

  3. Essential Task 7-2: Outline • Problem Solving Steps • Identify problem-solving techniques: • algorithms • Heuristics • Hill climbing • Sub-Goals • Working backwards • Means end analysis • Factors that influence their effectiveness • problem representation • mental set • functional fixedness • motivation

  4. 4 Problem Solving Steps • Define the Problem • Use that definition to decide what category a problem belongs to and then based on that • Select a solution strategy that would solve a problem in that category • Always evaluate progress toward goal

  5. Possible Solution Strategies • Trial and error • Works best with limited number of choices • Information retrieval • Retrieve from memory information about how such a problem has been solved in the past • Algorithms • Step-by-step methods that guarantees a solution • Methodical, logical rules or procedures that guarantee solving a particular problem. • Math problems are an example of the type best solved using an algorithm • Heuristics • Rules of thumb that may help simplify a problem, but do not guarantee a solution. • They are quicker than algorithms

  6. Algorithms Algorithms, which are very time consuming, exhaust all possibilities before arriving at a solution. Computers use algorithms. S P L O Y O C H Y G If we were to unscramble these letters to form a word using an algorithmic approach, we would face 907,208 possibilities.

  7. Heuristics • In psychology, heuristics are simple, efficient rules, learned from experience, that people use to make decisions, come to judgments, and solve problems typically when facing complex problems or incomplete information.

  8. Heuristics Heuristics make it easier for us to use simple principles to arrive at solutions to problems. S P L O Y O C H Y G P S L O Y O C H G Y S P L O Y O C H G Y P S Y C H O L O G Y Heuristic at work: Y’s usually go at the end of a word.

  9. Hill climbing Move progressively closer to goal without moving backward Sub-goals Break large problem into smaller, more manageable ones, each of which is easier to solve than the whole problem Means-end analysis Aims to reduce the discrepancy between the current situation and the desired goal – subgoals not immediately in the solution direction are considered Working backward Work backward from the desired goal to the existing condition Heuristic Methods

  10. Hill Climbing Heuristic • Move progressively closer to goal without moving backward

  11. Sub-goals • Break large problem into smaller, more manageable ones, each of which is easier to solve than the whole problem

  12. Means-end analysis • Aims to reduce the discrepancy between the current situation and the desired goal – subgoals not immediately in the solution direction are considered

  13. Working backward • Work backward from the desired goal to the existing condition

  14. Obstacles to Solving Problems • Motivation • Desire to solve a problem • Mental sets • Tendency to perceive and approach problems in certain ways • Functional fixedness • Tendency to see only a limited number of uses for an object

  15. Motivation • If you don’t attempt to solve a problem you won’t.

  16. Mental Set • “We can't solve problems by using the same kind of thinking we used when we created them.” Albert Einstein

  17. Functional Fixedness • “I can only use it for this one thing!”

More Related