Week 5 - HCI Concepts II_.pdf

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RichTourmaline9881

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Yakın Doğu Üniversitesi Dişhekimliği Fakültesi

2024

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human-computer interaction hci cognitive psychology

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Chp 2-4: HCI Concepts: Human, Computer, Interaction SE234: Human Computer Interaction Priscilla olawale Spring 2024 LTM - Storage of information rehearsal ◦ information moves from STM to LTM total time hypothesis ◦ amount retained proportional to rehearsal time distri...

Chp 2-4: HCI Concepts: Human, Computer, Interaction SE234: Human Computer Interaction Priscilla olawale Spring 2024 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 ©PRISCILLA OLAWALE (MSC) 2 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 ©PRISCILLA OLAWALE (MSC) 3 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 4 ©PRISCILLA OLAWALE (MSC) THINKING  Reasoning  deduction, induction, abduction  Problem solving 5 ©PRISCILLA OLAWALE (MSC) 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 6 ©PRISCILLA OLAWALE (MSC) 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 7 ©PRISCILLA OLAWALE (MSC) 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. 8 ©PRISCILLA OLAWALE (MSC) Wason's cards 7 E 4 K If a card has a vowel on one side it has an even number on the other Is this true? How many cards do you need to turn over to find out? …. and which cards? 9 ©PRISCILLA OLAWALE (MSC) 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 10 ©PRISCILLA OLAWALE (MSC) 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 11 ©PRISCILLA OLAWALE (MSC) 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 12 ©PRISCILLA OLAWALE (MSC) 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 13 ©PRISCILLA OLAWALE (MSC) 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 14 ©PRISCILLA OLAWALE (MSC) 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 15 ©PRISCILLA OLAWALE (MSC) 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) 16 ©PRISCILLA OLAWALE (MSC) 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 17 ©PRISCILLA OLAWALE (MSC) 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? 18 ©PRISCILLA OLAWALE (MSC) 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, the correct application generally requires an understanding of the context in psychology, and an understanding of particular experimental conditions A lot of knowledge has been distilled in ◦ guidelines ◦ cognitive models ◦ experimental and analytic evaluation techniques 19 ©PRISCILLA OLAWALE (MSC)

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