Review: Quantifying the user experience by J. Sauro and J. Lewis

Egon van den Broek

Research output: Contribution to journalBook/Film/Article reviewAcademic

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Abstract

Before I started to read this book, I searched for the authors’ definition of user experience (UX). To my surprise, I did not find one. Of course, I may have missed it; however, if it is really missing then this is definitely a weak aspect of the book. The reason I started with this search is because many people have issues with UX, usability, and related concepts. These terms are often used without scoping or defining them, which diminishes the value of work conducted in this field. For the purposes of this review, I will adopt the International Organization for Standardization (ISO) 9241-210 definition of UX: “A person’s perceptions and responses that result from the use or anticipated use of a product, system, or service‿ (http://www.iso.org/iso/catalogue_detail.htm?csnumber=52075). This comes quite close to the book’s definition of user research: “the systematic study of the goals, needs, and capabilities of users so as to specify design, construction, or improvement of tools to benefit how users work and live‿ (p. 9). However, although related, these definitions do differ. The definition of user research includes the definition of UX. This makes for an odd start to the book. Fortunately, some resources available online provide more information on the ins and outs of UX [1,2,3]. These sources can help readers get a solid footing for reading this book. Many books have already been published on UX, some even by the same publisher [4,5,6]. Where Buxton’s book [4] emphasizes the qualitative aspects of UX, Tullis and Albert [5] and Goodman et al. [6] focus on quantitative aspects of UX, as this book does. However, they focus on data acquisition and not on data analysis, which is the prime focus here. This is what makes this book valuable for both students and practitioners. Both these categories of readers can also benefit from a complementary book by the same authors [7]. This book provides more hands-on computing practice, examples, and exercises to give readers a jump-start on quantifying UX. The book takes a pragmatic and realistic--hence, the best possible--approach. In chapter 1, the authors provide four decision trees that help the practitioner or student choose the right chapter to start with (and skip the others). As such, it provides even pointers up to section level for the methods denoted in the decision trees. So, there are no more excuses for making a mistake when choosing your design of quantitative analysis. Having said this, it should be noted that the book provides an overview of rather basic statistical analysis and does not touch advanced statistical analysis (for example, mixed models and structural equation models). As such, the book provides room for follow-up books to continue where it leaves off. Without going into too much depth, I can say that the authors provide the basic mathematics underlying their analysis. For those that lack the fundamentals of statistics, the authors provide an appendix with a nutshell overview. Reading this book requires high-school-level mathematics, nothing more, which makes the book accessible to a very wide audience. On the other hand, those already in the field can use it as a refresher. Moreover, each chapter takes a historical stance, providing sufficient explanations and a decent list of references. I will admit that I had a false start with this book. I noticed its weak spot--perhaps its only one--from the beginning. However, taken as a whole, it provides a pragmatic approach to quantifying UX, without oversimplifying or claiming too much. It delivers what it promises. As such, this book is valuable for both practitioners and students, in virtually any discipline. It can help psychologists transfer their statistical knowledge to UX practice, it can help practitioners quickly assess their envisioned design and analysis, it can help engineers demystify UX, and it can help students appreciate UX’s merits. 1) Hassenzahl, M.; Tractinsky, N. User experience -- a research agenda. Behaviour and Information Technology 25, 2(2006), 91–97. 2) Law, E. L.-C.; Roto, V.; Hassenzahl, M.; Vermeeren, A. P. O. S.; Kort, J. Understanding, scoping and defining user experience: a survey approach. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, ), ACM, 2009, 719–728. 3) Hassenzahl, M. User experience and experience design. In The encyclopedia of human-computer interaction (2nd ed.). Interaction Design Foundation, 2013. 4) Buxton, B. Sketching user experiences: getting the design right and the right design. Morgan Kaufmann, San Francisco, CA, 2007. 5) Tullis, T.; Albert, B. Measuring the user experience: collecting, analyzing, and presenting usability metrics. Morgan Kaufmann, Burlington, MA, 2008. 6) Goodman, E.; Kuniavsky, M.; Moed, M. Observing the user experience: a practitioner’s guide to user research (2nd ed.). Morgan Kaufmann, Waltham, MA, 2012. 7) Lewis, J. R.; Sauro, J. Excel and R companion to: Quantifying the user experience: practical statistics for user research: rapid answers to over 100 examples and exercises. Create Space, Denver, CO, 2012.
Original languageUndefined
Pages (from-to)CR141037
JournalComputing reviews
Publication statusPublished - 19 Mar 2013

Keywords

  • EWI-23234
  • HMI-HF: Human Factors
  • Design
  • Methods
  • IR-86100
  • User eXperience (UX)
  • Statistics
  • METIS-297611
  • Review

Cite this

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title = "Review: Quantifying the user experience by J. Sauro and J. Lewis",
abstract = "Before I started to read this book, I searched for the authors’ definition of user experience (UX). To my surprise, I did not find one. Of course, I may have missed it; however, if it is really missing then this is definitely a weak aspect of the book. The reason I started with this search is because many people have issues with UX, usability, and related concepts. These terms are often used without scoping or defining them, which diminishes the value of work conducted in this field. For the purposes of this review, I will adopt the International Organization for Standardization (ISO) 9241-210 definition of UX: “A person’s perceptions and responses that result from the use or anticipated use of a product, system, or service‿ (http://www.iso.org/iso/catalogue_detail.htm?csnumber=52075). This comes quite close to the book’s definition of user research: “the systematic study of the goals, needs, and capabilities of users so as to specify design, construction, or improvement of tools to benefit how users work and live‿ (p. 9). However, although related, these definitions do differ. The definition of user research includes the definition of UX. This makes for an odd start to the book. Fortunately, some resources available online provide more information on the ins and outs of UX [1,2,3]. These sources can help readers get a solid footing for reading this book. Many books have already been published on UX, some even by the same publisher [4,5,6]. Where Buxton’s book [4] emphasizes the qualitative aspects of UX, Tullis and Albert [5] and Goodman et al. [6] focus on quantitative aspects of UX, as this book does. However, they focus on data acquisition and not on data analysis, which is the prime focus here. This is what makes this book valuable for both students and practitioners. Both these categories of readers can also benefit from a complementary book by the same authors [7]. This book provides more hands-on computing practice, examples, and exercises to give readers a jump-start on quantifying UX. The book takes a pragmatic and realistic--hence, the best possible--approach. In chapter 1, the authors provide four decision trees that help the practitioner or student choose the right chapter to start with (and skip the others). As such, it provides even pointers up to section level for the methods denoted in the decision trees. So, there are no more excuses for making a mistake when choosing your design of quantitative analysis. Having said this, it should be noted that the book provides an overview of rather basic statistical analysis and does not touch advanced statistical analysis (for example, mixed models and structural equation models). As such, the book provides room for follow-up books to continue where it leaves off. Without going into too much depth, I can say that the authors provide the basic mathematics underlying their analysis. For those that lack the fundamentals of statistics, the authors provide an appendix with a nutshell overview. Reading this book requires high-school-level mathematics, nothing more, which makes the book accessible to a very wide audience. On the other hand, those already in the field can use it as a refresher. Moreover, each chapter takes a historical stance, providing sufficient explanations and a decent list of references. I will admit that I had a false start with this book. I noticed its weak spot--perhaps its only one--from the beginning. However, taken as a whole, it provides a pragmatic approach to quantifying UX, without oversimplifying or claiming too much. It delivers what it promises. As such, this book is valuable for both practitioners and students, in virtually any discipline. It can help psychologists transfer their statistical knowledge to UX practice, it can help practitioners quickly assess their envisioned design and analysis, it can help engineers demystify UX, and it can help students appreciate UX’s merits. 1) Hassenzahl, M.; Tractinsky, N. User experience -- a research agenda. Behaviour and Information Technology 25, 2(2006), 91–97. 2) Law, E. L.-C.; Roto, V.; Hassenzahl, M.; Vermeeren, A. P. O. S.; Kort, J. Understanding, scoping and defining user experience: a survey approach. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, ), ACM, 2009, 719–728. 3) Hassenzahl, M. User experience and experience design. In The encyclopedia of human-computer interaction (2nd ed.). Interaction Design Foundation, 2013. 4) Buxton, B. Sketching user experiences: getting the design right and the right design. Morgan Kaufmann, San Francisco, CA, 2007. 5) Tullis, T.; Albert, B. Measuring the user experience: collecting, analyzing, and presenting usability metrics. Morgan Kaufmann, Burlington, MA, 2008. 6) Goodman, E.; Kuniavsky, M.; Moed, M. Observing the user experience: a practitioner’s guide to user research (2nd ed.). Morgan Kaufmann, Waltham, MA, 2012. 7) Lewis, J. R.; Sauro, J. Excel and R companion to: Quantifying the user experience: practical statistics for user research: rapid answers to over 100 examples and exercises. Create Space, Denver, CO, 2012.",
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note = "Book title: Quantifying the user experience: practical statistics for user research",
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journal = "Computing reviews",
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Review: Quantifying the user experience by J. Sauro and J. Lewis. / van den Broek, Egon.

In: Computing reviews, 19.03.2013, p. CR141037.

Research output: Contribution to journalBook/Film/Article reviewAcademic

TY - JOUR

T1 - Review: Quantifying the user experience by J. Sauro and J. Lewis

AU - van den Broek, Egon

N1 - Book title: Quantifying the user experience: practical statistics for user research

PY - 2013/3/19

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N2 - Before I started to read this book, I searched for the authors’ definition of user experience (UX). To my surprise, I did not find one. Of course, I may have missed it; however, if it is really missing then this is definitely a weak aspect of the book. The reason I started with this search is because many people have issues with UX, usability, and related concepts. These terms are often used without scoping or defining them, which diminishes the value of work conducted in this field. For the purposes of this review, I will adopt the International Organization for Standardization (ISO) 9241-210 definition of UX: “A person’s perceptions and responses that result from the use or anticipated use of a product, system, or service‿ (http://www.iso.org/iso/catalogue_detail.htm?csnumber=52075). This comes quite close to the book’s definition of user research: “the systematic study of the goals, needs, and capabilities of users so as to specify design, construction, or improvement of tools to benefit how users work and live‿ (p. 9). However, although related, these definitions do differ. The definition of user research includes the definition of UX. This makes for an odd start to the book. Fortunately, some resources available online provide more information on the ins and outs of UX [1,2,3]. These sources can help readers get a solid footing for reading this book. Many books have already been published on UX, some even by the same publisher [4,5,6]. Where Buxton’s book [4] emphasizes the qualitative aspects of UX, Tullis and Albert [5] and Goodman et al. [6] focus on quantitative aspects of UX, as this book does. However, they focus on data acquisition and not on data analysis, which is the prime focus here. This is what makes this book valuable for both students and practitioners. Both these categories of readers can also benefit from a complementary book by the same authors [7]. This book provides more hands-on computing practice, examples, and exercises to give readers a jump-start on quantifying UX. The book takes a pragmatic and realistic--hence, the best possible--approach. In chapter 1, the authors provide four decision trees that help the practitioner or student choose the right chapter to start with (and skip the others). As such, it provides even pointers up to section level for the methods denoted in the decision trees. So, there are no more excuses for making a mistake when choosing your design of quantitative analysis. Having said this, it should be noted that the book provides an overview of rather basic statistical analysis and does not touch advanced statistical analysis (for example, mixed models and structural equation models). As such, the book provides room for follow-up books to continue where it leaves off. Without going into too much depth, I can say that the authors provide the basic mathematics underlying their analysis. For those that lack the fundamentals of statistics, the authors provide an appendix with a nutshell overview. Reading this book requires high-school-level mathematics, nothing more, which makes the book accessible to a very wide audience. On the other hand, those already in the field can use it as a refresher. Moreover, each chapter takes a historical stance, providing sufficient explanations and a decent list of references. I will admit that I had a false start with this book. I noticed its weak spot--perhaps its only one--from the beginning. However, taken as a whole, it provides a pragmatic approach to quantifying UX, without oversimplifying or claiming too much. It delivers what it promises. As such, this book is valuable for both practitioners and students, in virtually any discipline. It can help psychologists transfer their statistical knowledge to UX practice, it can help practitioners quickly assess their envisioned design and analysis, it can help engineers demystify UX, and it can help students appreciate UX’s merits. 1) Hassenzahl, M.; Tractinsky, N. User experience -- a research agenda. Behaviour and Information Technology 25, 2(2006), 91–97. 2) Law, E. L.-C.; Roto, V.; Hassenzahl, M.; Vermeeren, A. P. O. S.; Kort, J. Understanding, scoping and defining user experience: a survey approach. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, ), ACM, 2009, 719–728. 3) Hassenzahl, M. User experience and experience design. In The encyclopedia of human-computer interaction (2nd ed.). Interaction Design Foundation, 2013. 4) Buxton, B. Sketching user experiences: getting the design right and the right design. Morgan Kaufmann, San Francisco, CA, 2007. 5) Tullis, T.; Albert, B. Measuring the user experience: collecting, analyzing, and presenting usability metrics. Morgan Kaufmann, Burlington, MA, 2008. 6) Goodman, E.; Kuniavsky, M.; Moed, M. Observing the user experience: a practitioner’s guide to user research (2nd ed.). Morgan Kaufmann, Waltham, MA, 2012. 7) Lewis, J. R.; Sauro, J. Excel and R companion to: Quantifying the user experience: practical statistics for user research: rapid answers to over 100 examples and exercises. Create Space, Denver, CO, 2012.

AB - Before I started to read this book, I searched for the authors’ definition of user experience (UX). To my surprise, I did not find one. Of course, I may have missed it; however, if it is really missing then this is definitely a weak aspect of the book. The reason I started with this search is because many people have issues with UX, usability, and related concepts. These terms are often used without scoping or defining them, which diminishes the value of work conducted in this field. For the purposes of this review, I will adopt the International Organization for Standardization (ISO) 9241-210 definition of UX: “A person’s perceptions and responses that result from the use or anticipated use of a product, system, or service‿ (http://www.iso.org/iso/catalogue_detail.htm?csnumber=52075). This comes quite close to the book’s definition of user research: “the systematic study of the goals, needs, and capabilities of users so as to specify design, construction, or improvement of tools to benefit how users work and live‿ (p. 9). However, although related, these definitions do differ. The definition of user research includes the definition of UX. This makes for an odd start to the book. Fortunately, some resources available online provide more information on the ins and outs of UX [1,2,3]. These sources can help readers get a solid footing for reading this book. Many books have already been published on UX, some even by the same publisher [4,5,6]. Where Buxton’s book [4] emphasizes the qualitative aspects of UX, Tullis and Albert [5] and Goodman et al. [6] focus on quantitative aspects of UX, as this book does. However, they focus on data acquisition and not on data analysis, which is the prime focus here. This is what makes this book valuable for both students and practitioners. Both these categories of readers can also benefit from a complementary book by the same authors [7]. This book provides more hands-on computing practice, examples, and exercises to give readers a jump-start on quantifying UX. The book takes a pragmatic and realistic--hence, the best possible--approach. In chapter 1, the authors provide four decision trees that help the practitioner or student choose the right chapter to start with (and skip the others). As such, it provides even pointers up to section level for the methods denoted in the decision trees. So, there are no more excuses for making a mistake when choosing your design of quantitative analysis. Having said this, it should be noted that the book provides an overview of rather basic statistical analysis and does not touch advanced statistical analysis (for example, mixed models and structural equation models). As such, the book provides room for follow-up books to continue where it leaves off. Without going into too much depth, I can say that the authors provide the basic mathematics underlying their analysis. For those that lack the fundamentals of statistics, the authors provide an appendix with a nutshell overview. Reading this book requires high-school-level mathematics, nothing more, which makes the book accessible to a very wide audience. On the other hand, those already in the field can use it as a refresher. Moreover, each chapter takes a historical stance, providing sufficient explanations and a decent list of references. I will admit that I had a false start with this book. I noticed its weak spot--perhaps its only one--from the beginning. However, taken as a whole, it provides a pragmatic approach to quantifying UX, without oversimplifying or claiming too much. It delivers what it promises. As such, this book is valuable for both practitioners and students, in virtually any discipline. It can help psychologists transfer their statistical knowledge to UX practice, it can help practitioners quickly assess their envisioned design and analysis, it can help engineers demystify UX, and it can help students appreciate UX’s merits. 1) Hassenzahl, M.; Tractinsky, N. User experience -- a research agenda. Behaviour and Information Technology 25, 2(2006), 91–97. 2) Law, E. L.-C.; Roto, V.; Hassenzahl, M.; Vermeeren, A. P. O. S.; Kort, J. Understanding, scoping and defining user experience: a survey approach. In Proc. of the SIGCHI Conference on Human Factors in Computing Systems (Boston, MA, ), ACM, 2009, 719–728. 3) Hassenzahl, M. User experience and experience design. In The encyclopedia of human-computer interaction (2nd ed.). Interaction Design Foundation, 2013. 4) Buxton, B. Sketching user experiences: getting the design right and the right design. Morgan Kaufmann, San Francisco, CA, 2007. 5) Tullis, T.; Albert, B. Measuring the user experience: collecting, analyzing, and presenting usability metrics. Morgan Kaufmann, Burlington, MA, 2008. 6) Goodman, E.; Kuniavsky, M.; Moed, M. Observing the user experience: a practitioner’s guide to user research (2nd ed.). Morgan Kaufmann, Waltham, MA, 2012. 7) Lewis, J. R.; Sauro, J. Excel and R companion to: Quantifying the user experience: practical statistics for user research: rapid answers to over 100 examples and exercises. Create Space, Denver, CO, 2012.

KW - EWI-23234

KW - HMI-HF: Human Factors

KW - Design

KW - Methods

KW - IR-86100

KW - User eXperience (UX)

KW - Statistics

KW - METIS-297611

KW - Review

M3 - Book/Film/Article review

SP - CR141037

JO - Computing reviews

JF - Computing reviews

SN - 0010-4884

ER -