Leture 4 - part: problem solving

Question 1

behaviorism approach - problem solving

Answer 1

• Edward Lee Thorndike
• > cat experiment, cat has to escape
• > problem solving by trial and error
• > criticism: random process (reproductive thinking)

Question 2

gestalt psychology - importanant early result

Answer 2

• Wolfgang Köhler
• WW1 -> monkeys on island he experimented with
• > provided them with 2 sticks to reach a banana
• > sticks to short
• > sticks had to be sticked together to reach banana
• > understanding it -> insight

Question 3

main hypothesis - gestalt

Answer 3

• problem solving requires productive thinking! (insight)

- > reorganzing/restructuring of problem situation’s elements to provide a solution

Question 4

Barriers to problem solving

-gestalt

Answer 4

• mental set -> using familiar strategy with past success when it is inappropriate
• functional fixedness -> inability to detach form object’s usual function when needed (2 string tasks)

Question 5

how to overcome barriers

Answer 5

-through getting hints

Question 6

remote associates test

-gestalt

Answer 6

• having 3 words

- they have to link with a single word, that has something in common with the 3 words

Question 7

strength gestalt approach

Answer 7

• interesting phenomena (e.g.insight etc.) which animated further research
• some concepts still applicable today (e.g. Design thinking)

Question 8

weaknesses gestalt approach

Answer 8

• no explanations of underlying mechanisms (from example insights)
• focus on very artificial problem situations (string task)
• disregards intuitive, reproductive problem solving

Question 9

problem space hypothesis -prior history

Answer 9

• Newell and Simon
• > information processing approach to problem solving
• mind works like computer
• developed problem solver (computer)

Question 10

main hypothesis - problem space

Answer 10

• problem situation represented in problem space
• initial state, goal state, mental operators, intermediate states
• human mind: limited processing capacity!
• > use of heuristics

Question 11

hill climbing VS Means-end analysis (heuristics)

Answer 11

hill climbing

• > strategy is very simple
• > doing everything that gets you closer to the hill/goal
• > works for ill defined problems

Means-end analysis

• > note difference to goal
• > form subgoal to reduce difference
• > select mental operator
• > for well-defined problems

Question 12

progress monitoring

Answer 12

• monitor progress
• slow progress
• strategy change
• very adaptive
• good for ill defined problems

Question 13

strengths problem space hypothesis

Answer 13

• proposes mechanisms how to solve problem -> detailed explanations
• applicable to many scenarios

Question 14

weaknesses problem space

Answer 14

• cannot explain insight problem solving (from gestalt)

- general problem solver (computer) is very different from real world human problem solving

Question 15

representational change theory

Answer 15

-insight through change of problem representation

Question 16

ways to change representations

Answer 16

1) constraint relaxation
- > if blocked , the ‘block’ is removed
2) re-encoding
- > re-structure/organize
3) elaboration
- > something is added

Question 17

R.C in comparison to gestalt

Answer 17

• like Gestalt
• > stresses insight in Problem solving
• unlike Gestalt
• > provides detailed explanation of mechanisms

Question 18

R.C. in comparison to problem space

Answer 18

• like Problem space
• > assumes information processing (kind of)
• unlike
• > productive thinking
• > solution