Book contents
- Frontmatter
- Contents
- List of experiments
- Acknowledgements
- Preface
- 1 Introduction
- 2 Defining the research
- 3 Experimental procedure
- 4 Data collection and qualitative analysis
- 5 Statistics
- 6 Reporting
- 7 Problems and pitfalls
- 8 Six principles for conducting experiments
- Appendix A1 Independent measures examples
- Appendix A2 Statistical formulae
- Appendix A3 Factor analysis example
- Bibliography
- References
- Index
8 - Six principles for conducting experiments
Published online by Cambridge University Press: 05 August 2012
- Frontmatter
- Contents
- List of experiments
- Acknowledgements
- Preface
- 1 Introduction
- 2 Defining the research
- 3 Experimental procedure
- 4 Data collection and qualitative analysis
- 5 Statistics
- 6 Reporting
- 7 Problems and pitfalls
- 8 Six principles for conducting experiments
- Appendix A1 Independent measures examples
- Appendix A2 Statistical formulae
- Appendix A3 Factor analysis example
- Bibliography
- References
- Index
Summary
To conclude, this chapter summarises the contents of this book by presenting a model and six key principles for designing and conducting experiments.
A model of the experimental process
The model, presented in Figure 8.1, shows the main stages of the experimental process and the important considerations that need to be addressed at each stage.
Six key principles for conducting experiments
This book presents specific advice to guide the researcher through the experimental process, and, subsequently, six key general principles emerge. These are listed as follows:
Principle 1: Define a clear research question and answer it. Doing so will provide a useful focus throughout the process and will ensure that a good “story” can be told at the end. Many decisions need to be made, and making them within the context of a clearly phrased research question will make them easier to decide on and justify.
Principle 2: Plan, prepare, and pilot. Participant time is a scarce resource: insufficient preparation will simply result in wasting the participants’ time. You cannot do too much preparation!
Principle 3: Only collect, analyse, and present data that are meaningful to the research question. Experimenter time is also a scarce resource. Like Principle 1, this principle ensures that your efforts are focussed, that you are not sidetracked into addressing interesting (but irrelevant) issues, and that your own time is not wasted.
Principle 4: Apply the planned analysis method on fabricated data before running the experiment. Collecting data that are not sufficient for answering your research question wastes your time and the participants’ time. Identify the form of data required for answering the research question before you start the experiment.
Principle 5: Collect and use both quantitative and qualitative data. The temptation is to focus on the numbers, whereas “softer” data are often much more revealing. Qualitative data are also useful when the numbers do not tell you what you wanted to hear.
Principle 6: Acknowledge the limitations of the experiment. Doing so is not only honest, but ensures that you do not overstate the conclusions. It also helps preempt the criticisms of reviewers.
- Type
- Chapter
- Information
- Experimental Human-Computer InteractionA Practical Guide with Visual Examples, pp. 199 - 202Publisher: Cambridge University PressPrint publication year: 2012