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Mental Models: Design of User Interaction and Interfaces for Domestic Energy Systems [Hardback]

(University of Southhampton, United Kingdom), (University of Southampton, United Kingdom)
  • Formāts: Hardback, 312 pages, height x width: 234x156 mm, weight: 589 g, 24 Tables, black and white; 49 Line drawings, black and white; 34 Halftones, black and white
  • Izdošanas datums: 21-Apr-2017
  • Izdevniecība: CRC Press Inc
  • ISBN-10: 1498762174
  • ISBN-13: 9781498762175
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Mental Models: Design of User Interaction and Interfaces for Domestic Energy SystemsPalielināt
  • Formāts: Hardback, 312 pages, height x width: 234x156 mm, weight: 589 g, 24 Tables, black and white; 49 Line drawings, black and white; 34 Halftones, black and white
  • Izdošanas datums: 21-Apr-2017
  • Izdevniecība: CRC Press Inc
  • ISBN-10: 1498762174
  • ISBN-13: 9781498762175
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9781498762175.html
Keywords:

There is a resurgence of interest in mental models due to advances in our understanding of how they can be used to help design and due to the development of practical methods to elicit them. This book brings both areas together with a focus on reducing domestic energy consumption. The book focuses on how mental models can be applied in design to bring out behaviour change resulting in increased achievement of home heating goals (reduced waste and improved comfort). This book also offers a method to extract and apply mental models to interface design. The approach enables mental models to be applied across domains when behaviour change was sought, and is validated as a useful design method.

Recenzijas

"This is a valuable piece of work for most, if not all, interface designers practicing user-centered design in the industry. The mental models methodology and approach discussed in the book benefits not only on reduction of energy consumption in domestic energy systems, but also helps readers in understanding the behavior and behavioral changes of consumers in other design domains. I would believe a wide range of researchers and practitioners would be interested in the practical examples, insights and guidance provided by the two experienced authors in this book." Alan HS Chan, City University of Hong Kong





"When Stanton and colleagues address a topic, its important to pay attention to what they have to say. I recently heard a famous inventor talk about the difference between unintended, unanticipated, and perverse consequences of innovation. This book on mental models for home energy systems gives me a great working example of this complex aspect of sociotechnical impacts of technology innovation." Barrett Caldwell, Purdue University, Indiana, USA

List of Figures
xv
List of Tables
xxi
Preface xxiii
Acknowledgements xxv
Authors xxvii
List of Abbreviations
xxix
Chapter 1 Introduction
1(8)
1.1 Who Is This Book For?
1(1)
1.2 How Different Readers Should Approach Reading the Book?
1(1)
1.3 Background
1(1)
1.4 Aims and Objectives/Purpose
2(2)
1.4.1 Overall Hypotheses
2(1)
1.4.2 Sub-Hypotheses
3(1)
1.5 Contribution to Research
4(1)
1.6 Structure of the Book
4(5)
Chapter 2 Models of Models: Filtering and Bias Rings in Depiction of Knowledge Structures and Their Implications for Design
9(28)
2.1 Introduction
9(6)
2.1.1 The Concept of Mental Models as Inferred Knowledge in Cognitive Processing
10(1)
2.1.1.1 Johnson-Laird (1983)
11(1)
2.1.1.2 Bainbridge (1992)
12(1)
2.1.1.3 Moray (1990)
12(1)
2.1.1.4 Summary of Comparison of Theories of Cognitive Processing
13(2)
2.2 Importance of Accuracy in Mental Model Descriptions: The Development of an Adaptable Framework
15(16)
2.2.1 Bias and Inhering When Constructing or Accessing Mental Models
15(4)
2.2.2 Accuracy of Mental Model Content: A Case Study of Kempton (1986) Illustrating the Impact of Methodology
19(1)
2.2.2.1 Bias When Accessing Another Person's Mental Model
20(3)
2.2.3 Accuracy in Definition: The Perspective from Which Data Is Gathered
23(1)
2.2.3.1 Norman (1983)
24(2)
2.2.3.2 Wilson and Rutherford (1989)
26(4)
2.2.3.3 Summary of Comparison of Perspectives of Mental Models
30(1)
2.3 Application of Adaptable Framework: Charactering Mental Models by Perspective and Evaluating `Risk of Bias'
31(1)
2.4 Conclusions
32(5)
Chapter 3 The Quick Association Check (QuACk): A Resource-Light, `Bias Robust' Method for Exploring the Relationship between Mental Models and Behaviour Patterns with Home-Heating Systems
37(40)
3.1 Introduction
37(2)
3.2 Methods Used for the Development and Evaluation of QuACk
39(14)
3.2.1 Literature Review
40(1)
3.2.2 Assess Methods for Home-Heating Context
41(6)
3.2.2.1 Content Analysis of Previous Research
47(1)
3.2.3 Existing Categories of Mental Models and Behaviour
47(2)
3.2.4 Consider Bias in Mental Models Research
49(1)
3.2.5 Developing Data Collection Method
49(2)
3.2.5.1 Paper-Based Activities
51(1)
3.2.5.2 Verification of Outputs
51(1)
3.2.6 Developing Analysis Method
52(1)
3.3 Pilot Case Studies and Participant Observation for Data Collection
53(2)
3.4 Participant Observation -- Data Analysis
55(12)
3.4.1 Applying the Analysis Reference Table
55(1)
3.4.1.1 Behaviour Pattern
55(6)
3.4.1.2 Mental Model Description of Home-Heating Function
61(3)
3.4.2 Benefits of Output Formats
64(1)
3.4.2.1 Self-Report Diagram
64(1)
3.4.2.2 Mental Model Description
64(1)
3.4.2.3 Association between Mental Model of Device Function and Behaviour
64(1)
3.4.3 Evaluating the Utility of the Analysis Reference Table
65(1)
3.4.4 Improvements to the Analysis Reference Table
65(2)
3.5 Validation
67(4)
3.5.1 Measurement Validity of Self-Report Behaviour
67(2)
3.5.2 Reliability of Analysis Method
69(1)
3.5.2.1 Dynamics of Exercise
69(1)
3.5.2.2 Results of Inter-Analyst Reliability Exercise
69(2)
3.5.2.3 Improvements
71(1)
3.6 Discussion
71(4)
3.6.1 Method Evaluation
73(2)
3.7 Conclusions
75(2)
Chapter 4 Case Studies of Mental Models in Home Heat Control: Searching for Feedback, Valve, Timer and Switch Theories
77(34)
4.1 Introduction
77(3)
4.2 Method
80(9)
4.2.1 Participants and Setting
80(1)
4.2.2 Data Collection
81(1)
4.2.3 Dynamics of the Interview
82(5)
4.2.4 Analysis of Outputs
87(2)
4.3 Case Studies
89(16)
4.3.1 Participant A: A Feedback Mental Model of Thermostat with Elements of Valve Behaviour
89(6)
4.3.2 Participant B: Feedback Behaviour without a Feedback Mental Model
95(4)
4.3.3 Participant C: Timer Model for Alternate Control Devices
99(6)
4.4 Discussion
105(4)
4.5 Conclusions
109(2)
Chapter 5 When Energy-Saving Advice Leads to More, Rather Than Less, Consumption
111(24)
5.1 Introduction
111(4)
5.2 Method
115(2)
5.2.1 Participants
115(1)
5.2.2 Setting
116(1)
5.2.3 Data Collection
116(1)
5.2.4 From Central Heating System
116(1)
5.2.5 From the User
117(1)
5.3 Results and Discussion
117(16)
5.4 Summary and Conclusions
133(2)
Chapter 6 Mind the Gap: A Case Study of the Gulf of Evaluation and Execution of Home-Heating Systems
135(48)
6.1 Introduction
135(5)
6.1.1 Norman's (1986) Gulf of Evaluation and Execution
137(2)
6.1.2 Conceptual and Mental Models of Home-Heating Systems
139(1)
6.2 The Design Model
140(10)
6.2.1 The Design Model Expressed as an Expert `User Mental Model'
142(3)
6.2.2 What Does `Appropriate' Home-Heating Control Look Like?
145(1)
6.2.3 Stages of `Appropriate' Activity with a Home-Heating System
145(5)
6.3 System Image of Home Heating
150(4)
6.3.1 Home Heating at the `System' Level
150(2)
6.3.2 Home Heating at the Device Level
152(2)
6.4 The User's Mental Model of Home Heating -- Case Study Results and Discussion
154(15)
6.4.1 How Compatible Were the Case Study User Mental Models of Home Heating?
155(1)
6.4.2 How Appropriate Were Case Study Self-Reported Behaviour of Home-Heating Operation?
155(7)
6.4.3 A Discussion of the Seven Stages of Activity When Users Operate Their Home-Heating System
162(1)
6.4.3.1 The Gulf of Execution
162(5)
6.4.3.2 The Gulf of Evaluation
167(2)
6.5 Conclusions
169(14)
Chapter 7 Using Interface Design to Promote a Compatible User Mental Model of Home Heating and Pilot of Experiment to Test the Resulting Design
183(18)
7.1 Introduction
183(3)
7.2 Concept Development
186(11)
7.2.1 Design of Key Devices
186(1)
7.2.1.1 Thermostat
186(2)
7.2.1.2 Programmer
188(2)
7.2.1.3 Boost
190(1)
7.2.1.4 TRV
191(1)
7.2.2 Design of System View
192(3)
7.2.3 Creating a Simulation
195(2)
7.2.4 Pilot
197(1)
7.3 Discussion
197(3)
7.4 Conclusion
200(1)
Chapter 8 Mental Model Interface Design: Putting Users in Control of Their Home-Heating Systems
201(26)
8.1 Introduction
201(3)
8.2 Method
204(5)
8.2.1 Experimental Design
205(2)
8.2.2 Participants
207(1)
8.2.3 Apparatus and Materials
207(1)
8.2.4 Procedure
208(1)
8.3 Results
209(12)
8.3.1 User Mental Models of Home-Heating Simulation
209(6)
8.3.2 User Behaviour with Home-Heating Simulation
215(1)
8.3.2.1 Underlying Assumption for Study
215(6)
8.4 Discussion
221(5)
8.4.1 Improved Discoverability of Home-Heating Controls
221(1)
8.4.2 More Appropriate Mental Models
222(1)
8.4.3 Increased Use of Frost Protection and Holiday Buttons
223(1)
8.4.4 More Appropriate Behaviour with TRV Controls
223(1)
8.4.5 Greater Control of Boiler Activation
224(1)
8.4.6 Increased Goal Achievement
225(1)
8.4.6.1 Limitations of Study
225(1)
8.5 Conclusions
226(1)
Chapter 9 Conclusion
227(10)
9.1 Introduction
227(1)
9.2 Summary of Findings
227(3)
9.2.1 Bias Must Be Considered in Mental Models Research
228(1)
9.2.2 Outputs from QuACk Help Explain Energy-Consuming Behaviour
228(1)
9.2.3 We Need to Think beyond the Thermostat -- Home-Heating Behaviour Should Be Understood at a System Level
229(1)
9.2.4 Broader System Variables Need to Be Understood for Optimal Consumption, but Are Not Promoted by Existing Technology
229(1)
9.2.5 Mental-Model-Driven Design Helps Users Achieve More Heating Goals
230(1)
9.3 Core Issues Relating Particularly to the Home-Heating Case Study
230(2)
9.3.1 Optimal Home Heat Control Is a Complex Task
230(1)
9.3.2 Existing Technology Does Not Support a `Systems UMM' of Home Heating
231(1)
9.3.3 We Cannot Control All the Variables That Affect Optimal Home Heating Control
232(1)
9.4 Recommendations
232(2)
9.4.1 Recognize the Complexity of the Task for Householders, When Embarking on Strategies to Reduce Home-Heating Consumption
232(1)
9.4.2 Use System-Level Strategies for Encouraging Appropriate Home-Heating Consumption
233(1)
9.4.3 Use a Mental Models Approach When Seeking to Encourage Appropriate Behaviour in Complex Systems
233(1)
9.4.4 Design Future Heating Systems with Optimal Consumption as the Primary Goal
233(1)
9.5 Areas of Future Research
234(1)
9.5.1 Extension of the `Tree-Ring' Method for Considering Bias
234(1)
9.5.2 Extension of the QuACk Method for Exploring Association with Mental Models and Behaviour
234(1)
9.5.3 Tailored Guidance for Optimal Home-Heating Behaviour in Different Circumstances
234(1)
9.5.4 Enhancement to Home-Heating Control Panel and Testing in Domestic Setting
234(1)
9.6 Concluding Remarks
235(2)
Appendix A The Quick Association Check
237(10)
A.1 QuACk Instructions for Interviewer
237(2)
A.1.1 Background
237(1)
A.1.2 Preparation
238(1)
A.1.2.1 Provide Participant Information Sheet
238(1)
A.1.2.2 Verbal Positioning
238(1)
A.1.3 What to Expect and How to Deal with It
238(1)
A.1.4 Interview Outputs
239(1)
A.2 QuACk Participant Information Sheet
239(1)
A.3 QuACk Interview Template for Home-Heating Domain
240(7)
A.3.1 Background Experience in Home Heating
240(1)
A.3.2 Behaviour
241(1)
A.3.2.1 Self-Report on Usage
242(1)
A.3.2.2 Response to Scenarios
243(1)
A.3.3 Mental Model of Device Function
244(3)
Appendix B
247(20)
References 267(10)
Bibliography 277(2)
Index 279
Kirsten M A Revell, PhD, graduated from Exeter University in 1995 with a BSc (Hons) in Psychology BSc at Exeter University. Her dissertation focused on the use of affordances in product design, and she has been fascinated with user centred design ever since. After graduating, Kirsten worked in Microsoft Ltd., implementing and managing the EMEA Services Academy, which prepared graduates for technical and consulting roles within Microsoft, across Europe, Middle East and Africa. In 2005 Kirsten undertook a second degree in Industrial Design, at Brunel University that included an industrial placement with the Ergonomics Research Group. During this time, Kirsten joined a major field trial for the Human Factors Integration Defence Technology Centre (HFI DTC) focused on the usability of digital mission planning and battle-space management systems. After graduating from Brunel University in 2009, Kirsten joined the Transportation Research Group, University of Southampton. Working again for the HFI DTC, her research investigated methods for metaphorical design of digital systems for mission planning. In 2010, Kirsten embarked on a EPSRC sponsored PhD in Human Factors at the University of Southampton, investigating a mental models approach to behavior change with domestic energy systems. This brought together both psychology and design disciplines to further her expertise in user-centred design.



 



Professor Neville A Stanton, PhD, is both a Chartered Psychologist and a Chartered Engineer and holds the Chair in Human Factors in the Faculty of Engineering and the Environment at the University of Southampton. He has degrees in Psychology, Applied Psychology and Human Factors and has worked at the Universities of Aston, Brunel, Cornell and MIT. His research interests include modelling, predicting and analysing human performance in transport systems as well as designing the interfaces between humans and technology. Professor Stanton has worked on cockpit design in automobiles and aircraft over the past 25 years, working on a variety of automation projects. He has published 30 books and over 200 journal papers on Ergonomics and Human Factors, and is currently an editor of the peer-reviewed journal Ergonomics. In 1998 he was awarded the Institution of Electrical Engineers Divisional Premium Award for a co-authored paper on Engineering Psychology and System Safety. The Institution of Ergonomics and Human Factors awarded him The Otto Edholm Medal in 2001, The President¹s Medal in 2008 and The Sir Frederic Bartlett Medal in 2012 for his contribution to basic and applied ergonomics research. The Royal Aeronautical Society awarded him and his colleagues the Hodgson Prize and Bronze Medal in 2006 for research on design-induced flight-deck error published in The Aeronautical Journal. The University of Southampton have awarded him a DSc in 2014 for his sustained contribution to the development and validation of Human Factors methods.