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Lesson 2

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MLG College of Learning, Inc

This document provides an overview of long-term memory (LTM) including: - LTM is divided into episodic and semantic memory, with semantic memory derived from episodic experiences over time. - Semantic memory uses networks and frames to organize knowledge into relationships and allow for inference. - Information is transferred from short-term to long-term memory through rehearsal and distributed practice. - While information can be forgotten through decay or interference, it can also be selectively remembered based on emotion.

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chapter 1 -the human Lesson 2 – Long Term Memory
Lesson Objective: At the end of the lesson the students can: • Explain Long Term • Explain the different long term memory process
Long-term memory (LTM) • Repository for all our knowledge – slow access ~ 1/10 second – slow decay, if any – huge or unlimited capacity • Two types – episodic – serial memory of events – semantic – structured memory of facts,concepts, skills semantic LTM derived from episodic LTM
Long-term memory (cont.) • Semantic memory structure – provides access to information – represents relationships between bits of information – supports inference • Model: semantic network – inheritance – child nodes inherit properties of parent nodes – relationships between bits of information explicit – supports inference through inheritance
The Long Term Memory Process
LTM - semantic network
Models of LTM - Frames • Information organized in data structures • Slots in structure instantiated with values for instance of data • Type–subtype relationships DOG Fixed legs: 4 Default diet: carniverous sound: bark Variable size: colour COLLIE Fixed breed of: DOG type: sheepdog Default size: 65 cm Variable colour
Models of LTM - Scripts Model of stereotypical information required to interpret situation Script has elements that can be instantiated with values for context Script for a visit to the vet Entry conditions: dog ill vet open owner has money Result: dog better owner poorer vet richer Props: examination table medicine instruments Roles: vet examines diagnoses treats owner brings dog in pays takes dog out Scenes: arriving at reception waiting in room examination paying Tracks: dog needs medicine dog needs operation
Models of LTM - Production rules Representation of procedural knowledge. Condition/action rules if condition is matched then use rule to determine action. IF dog is wagging tail THEN pat dog IF dog is growling THEN run away
LTM - Storage of information • rehearsal – information moves from STM to LTM • total time hypothesis – amount retained proportional to rehearsal time • distribution of practice effect – optimized by spreading learning over time • structure, meaning and familiarity – information easier to remember
LTM - Forgetting decay – information is lost gradually but very slowly interference – new information replaces old: retroactive interference – old may interfere with new: proactive inhibition so may not forget at all memory is selective … … affected by emotion – can subconsciously `choose' to forget
LTM - retrieval recall – information reproduced from memory can be assisted by cues, e.g. categories, imagery recognition – information gives knowledge that it has been seen before – less complex than recall - information is cue
Thinking Reasoning deduction, induction, abduction Problem solving
Deductive Reasoning • Deduction: – derive logically necessary conclusion from given premises. e.g. If it is Friday then she will go to work It is Friday Therefore she will go to work. • Logical conclusion not necessarily true: e.g. If it is raining then the ground is dry It is raining Therefore the ground is dry
Deduction (cont.) • When truth and logical validity clash … e.g. Some people are babies Some babies cry Inference - Some people cry Correct? • People bring world knowledge to bear
Inductive Reasoning • Induction: – generalize from cases seen to cases unseen e.g. all elephants we have seen have trunks therefore all elephants have trunks. • Unreliable: – can only prove false not true … but useful! • Humans not good at using negative evidence e.g. Wason's cards.
Wason's cards Is this true? How many cards do you need to turn over to find out? …. and which cards? If a card has a vowel on one side it has an even number on the other 7 E 4 K
Abductive reasoning • reasoning from event to cause e.g. Sam drives fast when drunk. If I see Sam driving fast, assume drunk. • Unreliable: – can lead to false explanations
Problem solving • Process of finding solution to unfamiliar task using knowledge. • Several theories. • Gestalt – problem solving both productive and reproductive – productive draws on insight and restructuring of problem – attractive but not enough evidence to explain `insight' etc. – move away from behaviourism and led towards information processing theories
Problem solving (cont.) Problem space theory – problem space comprises problem states – problem solving involves generating states using legal operators – heuristics may be employed to select operators e.g. means-ends analysis – operates within human information processing system e.g. STM limits etc. – largely applied to problem solving in well-defined areas e.g. puzzles rather than knowledge intensive areas
Problem solving (cont.) • Analogy – analogical mapping: • novel problems in new domain? • use knowledge of similar problem from similar domain – analogical mapping difficult if domains are semantically different • Skill acquisition – skilled activity characterized by chunking • lot of information is chunked to optimize STM – conceptual rather than superficial grouping of problems – information is structured more effectively
Errors and mental models Types of error • slips – right intention, but failed to do it right – causes: poor physical skill,inattention etc. – change to aspect of skilled behaviour can cause slip • mistakes – wrong intention – cause: incorrect understanding humans create mental models to explain behaviour. if wrong (different from actual system) errors can occur
Emotion • Various theories of how emotion works – James-Lange: emotion is our interpretation of a physiological response to a stimuli – Cannon: emotion is a psychological response to a stimuli – Schacter-Singer: emotion is the result of our evaluation of our physiological responses, in the light of the whole situation we are in • Emotion clearly involves both cognitive and physical responses to stimuli
Emotion (cont.) • The biological response to physical stimuli is called affect • Affect influences how we respond to situations – positive  creative problem solving – negative  narrow thinking “Negative affect can make it harder to do even easy tasks; positive affect can make it easier to do difficult tasks” (Donald Norman)
Emotion (cont.) • Implications for interface design – stress will increase the difficulty of problem solving – relaxed users will be more forgiving of shortcomings in design – aesthetically pleasing and rewarding interfaces will increase positive affect
Individual differences • long term – sex, physical and intellectual abilities • short term – effect of stress or fatigue • changing – age Ask yourself: will design decision exclude section of user population?
Psychology and the Design of Interactive System • Some direct applications – e.g. blue acuity is poor  blue should not be used for important detail • However, correct application generally requires understanding of context in psychology, and an understanding of particular experimental conditions • A lot of knowledge has been distilled in – guidelines (chap 7) – cognitive models (chap 12) – experimental and analytic evaluation techniques (chap 9)

More Related Content

Lesson 2

  • 1. chapter 1 -the human Lesson 2 – Long Term Memory
  • 2. Lesson Objective: At the end of the lesson the students can: • Explain Long Term • Explain the different long term memory process
  • 3. Long-term memory (LTM) • Repository for all our knowledge – slow access ~ 1/10 second – slow decay, if any – huge or unlimited capacity • Two types – episodic – serial memory of events – semantic – structured memory of facts,concepts, skills semantic LTM derived from episodic LTM
  • 4. Long-term memory (cont.) • Semantic memory structure – provides access to information – represents relationships between bits of information – supports inference • Model: semantic network – inheritance – child nodes inherit properties of parent nodes – relationships between bits of information explicit – supports inference through inheritance
  • 5. The Long Term Memory Process
  • 6. LTM - semantic network
  • 7. Models of LTM - Frames • Information organized in data structures • Slots in structure instantiated with values for instance of data • Type–subtype relationships DOG Fixed legs: 4 Default diet: carniverous sound: bark Variable size: colour COLLIE Fixed breed of: DOG type: sheepdog Default size: 65 cm Variable colour
  • 8. Models of LTM - Scripts Model of stereotypical information required to interpret situation Script has elements that can be instantiated with values for context Script for a visit to the vet Entry conditions: dog ill vet open owner has money Result: dog better owner poorer vet richer Props: examination table medicine instruments Roles: vet examines diagnoses treats owner brings dog in pays takes dog out Scenes: arriving at reception waiting in room examination paying Tracks: dog needs medicine dog needs operation
  • 9. Models of LTM - Production rules Representation of procedural knowledge. Condition/action rules if condition is matched then use rule to determine action. IF dog is wagging tail THEN pat dog IF dog is growling THEN run away
  • 10. LTM - Storage of information • rehearsal – information moves from STM to LTM • total time hypothesis – amount retained proportional to rehearsal time • distribution of practice effect – optimized by spreading learning over time • structure, meaning and familiarity – information easier to remember
  • 11. LTM - Forgetting decay – information is lost gradually but very slowly interference – new information replaces old: retroactive interference – old may interfere with new: proactive inhibition so may not forget at all memory is selective … … affected by emotion – can subconsciously `choose' to forget
  • 12. LTM - retrieval recall – information reproduced from memory can be assisted by cues, e.g. categories, imagery recognition – information gives knowledge that it has been seen before – less complex than recall - information is cue
  • 14. Deductive Reasoning • Deduction: – derive logically necessary conclusion from given premises. e.g. If it is Friday then she will go to work It is Friday Therefore she will go to work. • Logical conclusion not necessarily true: e.g. If it is raining then the ground is dry It is raining Therefore the ground is dry
  • 15. Deduction (cont.) • When truth and logical validity clash … e.g. Some people are babies Some babies cry Inference - Some people cry Correct? • People bring world knowledge to bear
  • 16. Inductive Reasoning • Induction: – generalize from cases seen to cases unseen e.g. all elephants we have seen have trunks therefore all elephants have trunks. • Unreliable: – can only prove false not true … but useful! • Humans not good at using negative evidence e.g. Wason's cards.
  • 17. Wason's cards Is this true? How many cards do you need to turn over to find out? …. and which cards? If a card has a vowel on one side it has an even number on the other 7 E 4 K
  • 18. Abductive reasoning • reasoning from event to cause e.g. Sam drives fast when drunk. If I see Sam driving fast, assume drunk. • Unreliable: – can lead to false explanations
  • 19. Problem solving • Process of finding solution to unfamiliar task using knowledge. • Several theories. • Gestalt – problem solving both productive and reproductive – productive draws on insight and restructuring of problem – attractive but not enough evidence to explain `insight' etc. – move away from behaviourism and led towards information processing theories
  • 20. Problem solving (cont.) Problem space theory – problem space comprises problem states – problem solving involves generating states using legal operators – heuristics may be employed to select operators e.g. means-ends analysis – operates within human information processing system e.g. STM limits etc. – largely applied to problem solving in well-defined areas e.g. puzzles rather than knowledge intensive areas
  • 21. Problem solving (cont.) • Analogy – analogical mapping: • novel problems in new domain? • use knowledge of similar problem from similar domain – analogical mapping difficult if domains are semantically different • Skill acquisition – skilled activity characterized by chunking • lot of information is chunked to optimize STM – conceptual rather than superficial grouping of problems – information is structured more effectively
  • 22. Errors and mental models Types of error • slips – right intention, but failed to do it right – causes: poor physical skill,inattention etc. – change to aspect of skilled behaviour can cause slip • mistakes – wrong intention – cause: incorrect understanding humans create mental models to explain behaviour. if wrong (different from actual system) errors can occur
  • 23. Emotion • Various theories of how emotion works – James-Lange: emotion is our interpretation of a physiological response to a stimuli – Cannon: emotion is a psychological response to a stimuli – Schacter-Singer: emotion is the result of our evaluation of our physiological responses, in the light of the whole situation we are in • Emotion clearly involves both cognitive and physical responses to stimuli
  • 24. Emotion (cont.) • The biological response to physical stimuli is called affect • Affect influences how we respond to situations – positive  creative problem solving – negative  narrow thinking “Negative affect can make it harder to do even easy tasks; positive affect can make it easier to do difficult tasks” (Donald Norman)
  • 25. Emotion (cont.) • Implications for interface design – stress will increase the difficulty of problem solving – relaxed users will be more forgiving of shortcomings in design – aesthetically pleasing and rewarding interfaces will increase positive affect
  • 26. Individual differences • long term – sex, physical and intellectual abilities • short term – effect of stress or fatigue • changing – age Ask yourself: will design decision exclude section of user population?
  • 27. Psychology and the Design of Interactive System • Some direct applications – e.g. blue acuity is poor  blue should not be used for important detail • However, correct application generally requires understanding of context in psychology, and an understanding of particular experimental conditions • A lot of knowledge has been distilled in – guidelines (chap 7) – cognitive models (chap 12) – experimental and analytic evaluation techniques (chap 9)