Tracking Distraction and testing vibration alert response
I did this series of a prototype, I decided to test my assumption: if we find a way to bring a student’s attention back to their reading task, we can help them finish. Monitoring is a practice that teachers often do in the classroom. And this special true for ADD students, that need to be constant reminders what to do and turn back their attention to a task.
In this second of user testing, I would like to bold my research of defining distracting behaviors, predicting distractions in body signals, and experimenting with different types of alerts.
My goals with this second round of user observation:
- Identify and defining distraction patterns. For example, thinking, checking smartphones, vocabulary, and complimentary videos.
- Predicting potential distractions from behavior
- Define a time period to consider that a person is distracted
- Test vibration as distraction alerts
- Test vibration on the body — back, core, and arm, and on the tablet.
User test group and criteria
- Graduate students who need to read complementary material for their thesis and feel overwhelmed
- ADD students also in reading tasks
- Observing through a digital camera for 20 minutes, at least. I want to get the opportunity to observe their body manifesting tiredness. And camera because most of them do not feel observed.
- Reading in digital format and article from their choice
*I tested on a graduate student because they’re also under pressure and feeling overwhelmed with the work overload and many complaints that reading is a difficult skill for them. Also, they are learning new subjects and learning from reading on their own, for example, one drop off the reading because they felt bored. Their reading was difficult. Although it was important, they drop off it.
Evaluating vibration alert responses
- Distraction alerts (vibration or sound) are good They keep distracted readers on track, they do not get irritated after being alerted more than 5 times, as far as I could test, and they said that they would use it again;
- Alerts help them recognize their distraction patterns and change behaviors; They got aware of their impulsiveness response to an external and internal stimulus.
- Reading but not learning;
I could not recognize when they were struggling in understanding a text or they are bored, they just suddenly stopped.
- In general, After 25 minutes they reduce their reading productivity, and they were easily willing to change activity.
- Internal thoughts are distractions and triggers to abandon the reading.
- Distractions alerts are effective for attention;
- Part of being concentrated is being engaged;
- Distractions alerts must be customized; Some users prefer to sound and others, vibration;
- Distraction alerts must come from the device that they are reading;
- Timing and interval keep the focus and brain energy;
- 15 second is a time limit to alert.
Learning for predictions
- After 25 minutes, in general readers reduce their pace and their posture is more curved;
- They skim more;
- They got stuck in a paragraph or move forward and back in the same page, they are likely to get distracted or drop off the reading.
Next Steps and Questions
- Define engagement in reading tasks
- How might I create more engagement in reading?
- Should the app check if they are not engaged?
- How does the app control internal impulse to do another activity? For examples, participant A remembered to write an email while reading.
- Is taking notes or highlighting information a good metric to track concentration?
- Is taking notes a way to measure engagement in reading?