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Analyzing and Presenting
Performance metrics
Analyzing and Presenting
Time-on-Task Data
Common way
• TIME-ON-TASK is usually to measure
– Efficiency
• Look at the average amount of time spent on
– A particular set of tasks.
• Solution
– Create ranges or discrete time intervals
• To find patterns among participants
– report the
» frequency of participants per time interval
» Find out who took long to finish and if they share common
characteristics
Other solution
• Thresholds
– Set a time for completion
• What matter is whether users can complete certain tasks in
that time
– calculate the percentage of users above or below the
threshold
• e.g. show the percentage of participants who completed
each task in less than one minute.
• Aims is to minimize the number of users who
– need an excessive amount of time to complete a task.
Issue to know
• Look at all tasks or just the successful tasks?
– Successful tasks
• provide cleaner measure of efficiency;
• but no information on Unsuccessful performance
– Without that you can (Unsuccessful performance)
• Measure can be less accurate
• It can be harder to reflection of the overall user experience
– Solution
• Use only the times for the successful tasks
• And errors for unsuccessful task
• Shall we use a think-aloud protocol?
– This helps you contextualize your data and not to misinterpret the data
• But should not influence the time-to-task measurement
– Solution
• you can ask participants to hold most of comment to the between tasks period
• Shall we tell participants that time is being measured?
– Not directly
Analyzing and Presenting
Number of mistakes
Errors
• Or mistakes
– Help to understand possible usability issues
– how a specific action or set of actions
• result in task failure
• Errors vs usability issues
– A usability issue is the underlying cause of a
problem; and
– a error is the outcome
Errors can tell
• How usable something really is.
– Number of mistakes made,
• How they were made,
– Type and frequency of errors and it correlation with
• Product design
– Loss in efficiency
• e.g. filling in a form and a error results in lost of time to
complete the task
• e.g. influence cost effectiveness or influence task failure
Common way
• Organize by task
– Define the correct set of actions to do the task
• Define the correct and incorrect possible number of actions
• Then…
– Collect number or errors
• By user and by task
• How to collect
– Observe the participant
• During a lab study
• During a video record
Error analysis
• Look at the frequency of the error for each task
– calculate the average number of errors made by each
participant for each task.
– frequency of errors for each task.
• This helps you to
– find out which task is associated with the most errors
– Tell in which (task) participants made more error
• From that results you get an idea what were the
most significant usability issues.
Other approach
• If your concern is not with how participants
perform a specific task
– but about how participants performed overall
• Then…
– Find out the overall error rate for the study.
• By averaging the error rates for each task into a single
error rate
Issues to know
• Don’t double-count the errors
– Double-counting happens when you assign more
than one error to the same event
• Test the error counting before start the procedure and
• Define a clearly what errors you need to count
• If you need to know not just error rate but
– Also why this errors occurs then…
• You need to add a code name to each possible error
Analyzing and Presenting
Number of steps taken
Number of steps taken
• TASK-SETPS also measure
– Efficiency
• Efficiency metrics should be concerned not
only
– With the time-to-task, but also
– With the amount of cognitive and physical effort
involved
How to measure - Common Way
• Identify the action(s) to be measured
– More actions taken VS more effort is involved
• Type of efforts
– Cognitive
» involves finding the right place to perform an action
– Physical
» Involves the physical activity required to take action
How to identify- Common Way
• Identify the action(s) to be measured
– Define the start and end of an action
• Count the actions
– Easier way is to count while participants are doing the task
– If not possible use video recordings
• Actions should be meaningful
– represent an increase in cognitive and/or physical effort
» More action more effort
• Look only at successful tasks
Analysis
• Calculate an average for each task (by
participant)
– to see how many actions are taken
– This will help you to identify which task
• Requires the most amount of effort
• Another way is to use a method called
Lostness
Combine of metrics
• Task success and time-on-task to measure
– Efficiency
• How
– Ratio of the task completion to the task time in minutes
To read
• Measuring the User Experience.pdf
– Dropbox folder
• Workshops/W1
• Have a look at
– CHAPTER 4
• Pages 63-92

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Workshop 1 (analysis and Presenting)

  • 3. Common way • TIME-ON-TASK is usually to measure – Efficiency • Look at the average amount of time spent on – A particular set of tasks. • Solution – Create ranges or discrete time intervals • To find patterns among participants – report the » frequency of participants per time interval » Find out who took long to finish and if they share common characteristics
  • 4. Other solution • Thresholds – Set a time for completion • What matter is whether users can complete certain tasks in that time – calculate the percentage of users above or below the threshold • e.g. show the percentage of participants who completed each task in less than one minute. • Aims is to minimize the number of users who – need an excessive amount of time to complete a task.
  • 5. Issue to know • Look at all tasks or just the successful tasks? – Successful tasks • provide cleaner measure of efficiency; • but no information on Unsuccessful performance – Without that you can (Unsuccessful performance) • Measure can be less accurate • It can be harder to reflection of the overall user experience – Solution • Use only the times for the successful tasks • And errors for unsuccessful task • Shall we use a think-aloud protocol? – This helps you contextualize your data and not to misinterpret the data • But should not influence the time-to-task measurement – Solution • you can ask participants to hold most of comment to the between tasks period • Shall we tell participants that time is being measured? – Not directly
  • 7. Errors • Or mistakes – Help to understand possible usability issues – how a specific action or set of actions • result in task failure • Errors vs usability issues – A usability issue is the underlying cause of a problem; and – a error is the outcome
  • 8. Errors can tell • How usable something really is. – Number of mistakes made, • How they were made, – Type and frequency of errors and it correlation with • Product design – Loss in efficiency • e.g. filling in a form and a error results in lost of time to complete the task • e.g. influence cost effectiveness or influence task failure
  • 9. Common way • Organize by task – Define the correct set of actions to do the task • Define the correct and incorrect possible number of actions • Then… – Collect number or errors • By user and by task • How to collect – Observe the participant • During a lab study • During a video record
  • 10. Error analysis • Look at the frequency of the error for each task – calculate the average number of errors made by each participant for each task. – frequency of errors for each task. • This helps you to – find out which task is associated with the most errors – Tell in which (task) participants made more error • From that results you get an idea what were the most significant usability issues.
  • 11. Other approach • If your concern is not with how participants perform a specific task – but about how participants performed overall • Then… – Find out the overall error rate for the study. • By averaging the error rates for each task into a single error rate
  • 12. Issues to know • Don’t double-count the errors – Double-counting happens when you assign more than one error to the same event • Test the error counting before start the procedure and • Define a clearly what errors you need to count • If you need to know not just error rate but – Also why this errors occurs then… • You need to add a code name to each possible error
  • 14. Number of steps taken • TASK-SETPS also measure – Efficiency • Efficiency metrics should be concerned not only – With the time-to-task, but also – With the amount of cognitive and physical effort involved
  • 15. How to measure - Common Way • Identify the action(s) to be measured – More actions taken VS more effort is involved • Type of efforts – Cognitive » involves finding the right place to perform an action – Physical » Involves the physical activity required to take action
  • 16. How to identify- Common Way • Identify the action(s) to be measured – Define the start and end of an action • Count the actions – Easier way is to count while participants are doing the task – If not possible use video recordings • Actions should be meaningful – represent an increase in cognitive and/or physical effort » More action more effort • Look only at successful tasks
  • 17. Analysis • Calculate an average for each task (by participant) – to see how many actions are taken – This will help you to identify which task • Requires the most amount of effort • Another way is to use a method called Lostness
  • 18. Combine of metrics • Task success and time-on-task to measure – Efficiency • How – Ratio of the task completion to the task time in minutes
  • 19. To read • Measuring the User Experience.pdf – Dropbox folder • Workshops/W1 • Have a look at – CHAPTER 4 • Pages 63-92