Guidelines for user testing with thinking aloud
Practical study design
- Reflect on the participants' backgrounds and how they might affect the
study
- Be aware of problems that arise when experimenters know the users
personally
- Prepare for the study carefully (avoid last minute panic)
- Select the tasks carefully to be representative and to fit the allotted
time
- In general, start with an easier (but not frivolous) task
- Write down features of the system that are not being tested as
well as those that are!
- Define the start-up state for the study precisely
- Define precise rules for when and how users can be helped during the study
- Plan the timing and cut-off procedure (if subject gets stuck) for each
part of the study
- Include reasonable provisions for data collection (e.g., tape or video
recorder, keystroke capture where appropriate)
- Plan data analysis techniques in advance
- Carry out a pilot study (important but often overlooked)
Written materials
- Participant release form
- Questionnaire covering prior experience etc. (if relevant)
- Introduction to the study for users, including scenario of use
- Checklist for experimenters
- Evaluation survey (if relevant)
Carrying out the study
- Let users know that complete anonymity will be preserved
- Let them know that they may quit at any time
- Stress that the system is being tested, not the participant
- Indicate that you are only interested in their thoughts relevant to the
system
- Demonstrate the thinking-aloud method by acting it out for a simple
task, such as figuring out how to load a stapler, and a computer-related
task
- Hand out instructions for each part of the study individually, not all
at once
- Maintain a relaxed environment free of interruptions
- Occasionally encourage users to talk if they grow silent
- If users ask questions, try to get them to talk (e.g., "What do
you think is going on?" and follow predefined rules on when to help
or interrupt to help.
- Debrief each user after the experiment
Improving the study
- The pilot study should "debug" the study. This minimize
changes during the study, allowing quantitative data analysis. But
improvements may be warranted.
- Experimenters' role can be improved
- Tasks given to participant can be improved
- Written materials can be improved