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![“First were mainframes, each shared by
lots of people. Now we are in the
personal computing era, person and
machine staring uneasily at each other
across the desktop. Next comes
ubiquitous computing [...] when
technology recedes into the background
of our lives.”
- Weiser](https://image.slidesharecdn.com/slides-140310115657-phpapp01/85/Using-Smartphones-to-Research-Daily-Life-2-320.jpg)
Uploaded byNeal Lathia
Using Smartphones to Research Daily Life
This document discusses using smartphones to research daily life through experience sampling methods. It describes the Emotion Sense app, which collects survey responses and sensor data from users to study mood, activities, and context. Key challenges included keeping users engaged in surveys over time. The author also introduces Easy M, a generalized version of Emotion Sense that allows other researchers to easily conduct sensor-enhanced experience sampling studies on their own topics.
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Using Smartphones to Research Daily Life
- 1. Using Smartphones toResearch Daily Life Dr. Neal Lathia Computer Laboratory, University of Cambridge neal.lathia@cl.cam.ac.uk
- 2. “First were mainframes,each shared by lots of people. Now we are in the personal computing era, person and machine staring uneasily at each other across the desktop. Next comes ubiquitous computing [...] when technology recedes into the background of our lives.” - Weiser
- 3. Android: 1.5 million dailyactivations
- 4. Phone Calls Text Messages SocialMedia E-mail Camera Calendars Maps Transport Games News Videos
- 5. Phone Calls Text Messages SocialMedia E-mail Camera Calendars Maps Transport Games News Music Videos Communication Patterns; Social Networks and Sharing; Information Diffusion; Points of Interest; Mobility; App Usage ...
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- 9. How can wesense, identify, and capture high-level behaviours (e.g., walking, running) from low-level sensors (e.g., accelerometer)? “Classic” Research Question (1): For ever higher level behaviours Given energy, computation constraints
- 10. How can weverify or understand qualitative aspects of behaviour that can be sensed (i.e., the why)? “Classic” Research Question (2): Choices, feelings, reasons, semantics (e.g., home vs. lat/lon).
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- 13. Researching Daily Life: Reflectingon the 'scientific' method
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- 16. Hypothesis Measure Test ESM Design Ready forthe public... Sensor-Sampling Design User Experience Design Build App Test App Deploy App Market App Debug App Update App Re-design UX User Support De-noise data
- 18. Emotion Sense Basics: (a)Complete a “long” survey about how you feel & your current context (b) Receive notifications that ask you to complete a “short” survey (c) View how your survey responses compare to the sensor data your phone has collected.
- 19. Emotion Sense Surveys (momentary) Positive/NegativeAffect Day “Goodness” Current Location Texting/Calling Habits Current Activity Device Interaction Recent Speech Personality Sociability Connectedness Engagement (non-momentary) Demographics Satisfaction with Life Personality Gratitude Health Sociability Job Satisfaction Life Aspirations Connectedness
- 21. Emotion Sense Sensors Location TextingLogs Call Logs Accelerometer Microphone Screen On/Off Samples Wi-Fi Battery Levels
- 22. ● How canwe keep users engaged in a seemingly repetitive task? ● Surveys are “too long” … “too obtrusive” .. “too repetitive” ● ESM experiments “don't beneft me” … “too boring” Design Challenges
- 23. A “Non”-Game designedlike a game
- 24. How many questionsto ask...? When the user is “volunteering” a response (10) vs. When the user is responding to a notification (3)
- 25. Limited feedback –avoiding judging
- 26. How are peopleinteracting? – 12,000 interacting users; – 650,000+ survey responses – ~6% answer only 1 survey – ~800 daily user responses – Average of 60+ days responding to surveys per user – ~15% users > 3 months – App demographics ~ published Android user demographics
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- 31. Emotion Sense: OngoingWork – Making sense of noisy sensor data: various devices, time zones, participation lengths – Analysing quality, content of survey responses – Investigating the future of these tools: generalising (for researchers) vs. specialising (for a particular context).
- 32. Easy M: Can Irun a study like Emotion Sense? (Without going back to the drawing board) Generalised sensor- enhanced experience sampling tool.
- 33. Easy M Basics: (a)Enter a “participant code” to join an experiment; app reconfigures itself (with timeout) (b) Receive notifications that ask you to complete your researchers' survey (c) Volunteer additional responses
- 34. Easy M Basics: Allowsfor both “momentary” and “volunteered” survey types. Questions include all the same types as Emotion Sense. User feedback is limited to response time and compliance.
- 35. Where could EasyM be used?
- 36. Using Smartphones toResearch Daily Life Dr. Neal Lathia Computer Laboratory, University of Cambridge neal.lathia@cl.cam.ac.uk http://emotionsense.org/ http://www.cl.cam.ac.uk/~nkl25/easym/