802.11n is the high throughput amendment to the 802.11 standard. This section describes all the aspects of the physical layer which increase the data rate. MIMO/SDM is a key feature of 802.11n, which is discussed in Chapters 3 and 4. The other significant increase in data rate is derived from the new 40 MHz channel width. This section also discusses short guard interval, Greenfield preamble, and other modifications to the 20 MHz waveform.

40 MHz channel

In the last several years, regulatory domains have made much more spectrum available for unlicensed operation in the 5.47–5.725 GHz band for wireless local area networking. The addition of the new spectrum has more than doubled the number of available 20 MHz channels in the USA and Europe. Table 5.9 and Table 5.10 in Appendix 5.1 describe the current allocation in the USA and Europe, and the corresponding 802.11 channel number. Even with doubling the channel width to create 40 MHz channels, there are still more channels available for frequency re-use than in the early days of 802.11a. Furthermore, products currently in the market with proprietary 40 MHz modes have demonstrated that the cost for 40 MHz products is roughly the same as for 20 MHz products. Therefore, with free spectrum and relatively no increase in hardware cost, doubling the channel bandwidth is the simplest and most cost effective way to increase data rate.

Overview

Although formal techniques are not widely used in the analysis of interactive systems there are reasons why an appropriate set of tools, suitably designed to be usable by system engineers, could be of value in the portfolio of techniques used to assess interactive systems. This chapter describes the role of formal techniques in modelling and analysing interactive systems, discusses unfulfilled opportunities and speculates about the removal of barriers to their use. It also presents the opportunities that a clear expression of the problem and systematic analysis techniques may afford.

Introduction

Formal approaches bring rigour and automation to usability engineering. Models capture key features of the interactive behaviour of the design and are then subjected to systematic analysis using verification techniques such as model checking (Clarke, Grumberg and Peled, 1999). The appropriate selection of models and verification techniques is critical to the value of the analysis. Otherwise models can bias the analysis and verification techniques can take the focus away from important safety or business-critical features of the designed interactive system.

Formal techniques have been used to analyse a variety of properties of interactive behaviours in a number of systems including menu structures in mobile phones, flight management systems and other control systems on aircraft, air traffic control systems, interaction techniques for virtual environments and many others. Two categories of (semi-)automated verification techniques can be identified.

Overview

With fast changing technologies and related human interaction issues, there is an increased need for timely evaluation of systems with distributed users in varying contexts (Pace, 2004). This has led to the increased use of questionnaires, in-depth interviews and focus groups in commercial usability and academic research contexts. Questionnaires are usually paper based or delivered online and consist of a set of questions which all participants are asked to complete. Once the questionnaire has been created, it can be delivered to a large number of participants with little effort. However, a large number of participants also means a large amount of data needing to be coded and analysed. Interviews, on the other hand, are usually conducted on a one-to-one basis. They require a large amount of the investigator's time during the interviews and also for transcribing and coding the data. Focus groups usually consist of one investigator and a number of participants in any one session. Although the views of any one participant cannot be probed to same degree as in an interview, the discussions that are facilitated within the groups often result in useful data in a shorter space of time than that required by one-to-one interviews.

All too often, however, researchers eager to identify usability problems quickly throw together a questionnaire, interview or focus group that, when analysed, produces very little of interest.

Overview

Controlled experiments, an approach that has been adopted from research methods in psychology, feature large in the arsenal of HCI research methods. Controlled experiments are a widely used approach to evaluating interfaces (e.g. McGuffin and Balakrishnan, 2005) and styles of interaction (e.g. Moyle and Cockburn, 2005), and to understanding cognition in the context of interactions with systems (e.g. Li et al., 2006). The question they most commonly answer can be framed as: does making a change to the value of variable X have a significant effect on the value of variable Y? For example, X might be an interface or interaction feature and Y might be time to complete task, number of errors or users' subjective satisfaction from working with the interface. Controlled experiments are more widely used in HCI research than in practice, where the costs of designing and running a rigorous experiment typically outweigh the benefits.

The purpose of this chapter is to outline matters that need to be considered when designing experiments to answer questions in HCI.

The method

We have structured this section about how to design and run a controlled experiment in the order that the information is usually reported within the method section of a paper or project report; that is, first we will consider how to go about choosing the participants who will take part in the experiment before moving on to consider designing the experiment itself, assembling the materials and apparatus required, and finally the procedure.

Overview

Given the complex and dynamic nature of HCI, it could be argued that the methods described here, whilst successful so far, may not be sufficient to address the challenges of HCI research in future. The purpose of this chapter is to show that even in the new area of user experience, these methods are still able to structure investigations and so provide insights and knowledge that we hope will be valuable to other researchers. Of course, this new area also shows up some of the limitations of the existing methods and this leads us to discuss the relationship between HCI as it might be in future and the research methods it has and may come to need.

Before describing our research into user experience, it is worth discussing the move in HCI towards user experience and why it seems a natural trajectory for HCI to take.

From usability to user experience

Traditional usability, as embodied in standards such as ISO 9241, have focused on users being able to interact with a system in a given context in a way which is effective, efficient and satisfying.

Why write this book?

Human–Computer Interaction (HCI) is a clearly multidisciplinary subject. It has historically grown out of both computer science and psychology but in addressing the full complexity of how people use computers it has also grown to encompass social sciences, organisational theories, cognitive ergonomics and even philosophy. These areas all have their own traditions for how to make a useful contribution to knowledge. This means that researchers coming into HCI, be they MSc students, PhD students or even established academics from another area, are rarely aware of the full range of methods that can be used to provide a useful contribution to HCI knowledge. Moreover, it is through awareness of the range of research methods that good researchers realise that a narrow approach to HCI may not be most appropriate in providing a substantial contribution to the area.

The purpose of this book is to describe and demonstrate research methods used in HCI so that new researchers in this area are aware of the possible sorts of research that can be done. In addition, through demonstrating how such research has been done, the book will provide a starting reference for a researcher who is intending to use a particular method. This book will not therefore tell you everything you need to know about a particular method, but it will tell you where you can find out more.

Overview

Over the last 30 years or so, computers have evolved rapidly into powerful and complex systems that underlie virtually every aspect of modern life and, if current trends continue, it is likely that they will be even more pervasive in the future. With the increased embeddedness of computer technology into our society, the characteristics of users have diversified rapidly from a situation where the average user was often a white, middle-aged male with a particular educational and socio-economic background to one in which users of all ages, sexes, social and ethnic backgrounds, levels of education and computer knowledge are interacting with complex interfaces to computer systems. The range and complexity of people's interactions with computers have also grown rapidly over recent years, so that we now do many things via a computer (e.g., managing a bank account, paying household bills, shopping, organising a holiday) that would have been done in the high street just a few years ago.

These rapid developments present significant challenges to interface designers. As the range and sophistication of computer-based tasks have increased so have the interfaces that people are required to use, and so the issue of how people perceive and process complex displays of information when carrying out tasks becomes ever more important. In order to understand these processes more closely, analysts have utilised the theories and methods of cognitive psychology – the study of human perception and information processing – to construct cognitive models: specifications of the mental representations, operations and problem-solving strategies that occur during the execution of computer-based tasks.

Overview

One feature of HCI research is that a broad range of methods have been developed to support the design and evaluation of interactive systems. In this chapter, we focus on evaluation methods – not because they are more important than design methods, but because we have more experience of them. In particular we consider the excitements and challenges of research on developing and testing new methods for evaluating interactive systems.

Evaluation methods can be broadly classed on three dimensions:

• with or without the active involvement of users

• with or without a running system

• with or without a realistic context of use.

Most methods fit into one position in this three-dimensional space. For example, controlled experiments typically involve the active participation of users with a running system in a laboratory setting (a non-realistic context of use), while contextual inquiry (Beyer and Holtzblatt, 1998) involves users with a running system in a realistic context. Conversely, interviews involve users but typically not a running system (though they may sometimes take place within the intended context of use). Most of the techniques that involve the active participation of users have drawn on and adapted methods initially developed within the social sciences, and methodological development has been relatively minor and definitely incremental.

In this chapter we focus on the other set of methods – those which do not require the active involvement of users, being applied, rather, by HCI experts.

Overview

A chapter on theory as a research technique is strange as, in a way, what is academic research about if it is not about theory? Without theory we may be engaged in product development, or data gathering, but not research. This said, there is of course also a spiritus mundi against theory: in abstracting away from the particular, theory is seen as at best simplistic and at worst reductionist and dangerous. And of course in popular language a theory is an unsubstantiated guess, almost the opposite of the scientific understanding of theory!

A theoretical approach is also not so much a method or technique that is applied to research, but an attitude and a desire to make sense of and to understand, in some ordered way, the phenomena around us. This approach can influence design and research methodology; indeed those most avowedly atheoretical in their methods are often most theoretical in their methodology!

Theories, that is systematic and structured bodies of knowledge, are the raw material for both research and practical design, but are also the outcomes of research and often the results of more informal reflection on experience. As we shall discuss shortly, theory is the language of generalisation, the way we move from one particular to another with confidence.

And theories can be more basic still. A tiny baby watches her moving fingers, hits out at a ball and sees it move, gradually making sense of the relation between feelings and effects; the building, testing and use of theory are as essential a part of our lives as feeding and breathing.