Imagery and Problem Solving 4

Question 1

Mental Imagery

Answer 1

Internal representation of items that are not currently being sensed
- Hard to investigate, because of:
No control, introspection unreliable, etc

Question 2

Analog Code

Answer 2

Mental image stored that closely resembles physical perception
eg) Mental Rotations
- Subjects had to decide wether display had similar shapes
- Functional equivalence in physical shape
–> greater the angle of rotation, the longer the reaction time

Question 3

Propositional Code

Answer 3

Language like representation
- Image shown with verbal labels
-> participants distorted images to fit labels

Less likely to influence image representation when created from scratch, or ambigious

Question 4

Propositional Representations

Answer 4

Using propositions (relationship among concepts) to represent.
eg)
Before[Cube,Cylinder]

Other types of representations:
Type of relationship, verbal representation, Imaginal Representation

Question 5

Functional-Equivalence Hypothesis

Answer 5

Construct images that are functionally equivalent to perception.
1. Mental Rotations
2. Image Scaling (takes longer to describe details of smaller objects compared to larger)
3. Image Scanning (linear relationship between distance to scan and actual reaction time)

Question 6

Problem Solving

Answer 6

transformation of a given situation into a desired situation or goal

Question 7

Understanding

Answer 7

Mental representation of problem

Question 8

Organisation of problems

Answer 8

1. Symbols
2. Matrixes
3. Diagrams
4. Visual problems

Question 9

Types of problems

Answer 9

1. Well Structured
   - clear path to solution
   eg) math problems
2. Ill Structured
   - Dimensions of problem are not specified or easy to infer
   eg) finding an apartment, writing a book, etc

Question 10

Characteristics of Problem Solving

Answer 10

1. Goal Directedness (problem solving behavior is directed toward attainment of goal)
2. Sequence of operations (sequence of steps)
3. Cognitive Operations (Application of processes to situation, that transforms the current state to a closer goal state)
4. Setting of subgoals (Each step produces a subgoal, that works its way to the solution)

Question 11

Strategy to solve problem

Answer 11

1. Algorithms
   - Systematic procedure guaranteed to find a solution
2. Heuristics
   - Useful rule of thumb based on experience
   - Efficient, but does not guarantee a correct solution.

Question 12

Problem Solving Strategies

Answer 12

1. Analogy Approach
2. Working Forward (start at initial)
3. Working Backward (start at goal)
4. Means-end analysis (Breaking down into subgoals, seeing which action brings closer to goal state)
5. Generate and test (trial and error)

Question 13

SOAR

Answer 13

State Operator And Result
- works in state space, with:
State: Represents current knowledge
Operator: Rules or procedures for transforming current into new state
Result: Outcome of applying operators onto state, leading into the new state

• used in tasks, such as AI

Question 14

Hill Climbing

Answer 14

Finding best solution by iterative improving on current solution.

Question 15

Methods for studying problem solving

Answer 15

1. Error Analysis/Reaction time
2. Verbal protocols
3. Computer simulation

Question 16

GPS

Answer 16

General Problem Solving
- Framework that uses Means-end analysis, a state space and heuristic information to problem solve.

Question 17

Obstacles in Problem Solving

Answer 17

1. Mental Set (solving a problem in a “fixed” way, mindset(fixed vs growth) )
2. Functional Fixedness (Inability to assign new functions and roles to elements of a problem)
3. Incorrect/Incomplete Representation
4. Lack of domain knowledge

Solved by:
1. Incubation
- time away from a problem, to provide new insights
- recovery from fatigue