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Evaluating Ubiquitous Computing Applications In Situ. Katherine Everitt (UW, IRS intern) Sunny Consolvo (IRS, UW) Ian Smith (IRS) James Landay (IRS, UW CSE) Intel Research Seattle University of Washington In-Use, In-Situ Workshop 28 October 2005. Talk Overview.
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Evaluating Ubiquitous Computing Applications In Situ Katherine Everitt (UW, IRS intern) Sunny Consolvo (IRS, UW) Ian Smith (IRS) James Landay (IRS, UW CSE) Intel Research Seattle University of Washington In-Use, In-Situ Workshop 28 October 2005
Talk Overview • 2 evaluation approaches • Wizard of Oz • Mobile Phones (Existing technologies) • Cross-cutting problem • prototype fidelity • Value of in situ evaluations
In Situ Evaluation Technique:Wizard of Oz • Two examples: • CareNet Display • Home Energy Tutor Configuration Tool Home Energy TutorConfiguration Tool CareNet Display
WoZ Example: CareNet Display • Interactive photo augmented with care-relevant updates • Goal: help local care network members provide day-to-day care
WoZ Example:CareNet DisplaySystem architecture for evaluation
WoZ Example:CareNet Key Results • Improved relationship among care network (qualitative feedback) • Including caregiver-caregiver relationships • Improved quality of conversations with elder • All elders said before deployment that they would share with locals • Distant relations were concerns at start • Bad predictors of who to share with
In Situ Wizard of Oz: Challenges • Data collection was labor intensive • Full-time intern for 3 months! • No exceptions! • Not including development, analysis! • Unreliable technology • GPRS • Difficult to use touch screen • Can’t rely on participants to alert you when the technology fails • no matter how much you beg!
In Situ Evaluation Technique:Mobile Phones (existing technologies) • Houston: Sharing fitness information within a social group • Focus on the social effects • Competition, peer pressure/support • Reno: Sharing location data within a family • Focus on privacy issues • Location system design guidance
Mobile Phone Example:Houston mobile computing + social influence = increased step count Key Decision: Step counts are a reasonable proxy for physical activity
Mobile Phone Example:Houston • 3-week, in situ study of Houston • 3 groups of women aged 28 – 42 (13 participants total) • Carry “extra” mobile phone daily • Too complex to “modify” their phone • One group with no “assisted” sharing • Two groups with enhanced sharing • Used first week to set baseline
Houston: Key Results • Wanted credit for all activities • Proper credit within activity • 7 of 13 participants increased daily step count (on average) • Qualitative data suggests that most participants changed their behavior • Sharing motivates some people • Support but not require social interaction
Mobile Phones: Challenges • Input/output of a mobile phone is limited • Exacerbated by development choices • 2nd mobile phone was unnatural • 2nd phone offered us “more control” • Nokia 6600 is considered “too big” by some • Data loss when out of range • Timing of SMS • Charging batteries – custom apps burn batteries faster than participants are used to • Nightly charging isn’t always done
Mobile Phones: Loss of expensive prototype technologies • Theft • Theft from participant • Theft from you by participant • Damage • Pedometers lost to toilet, washing machine, sea, etc. • Phones/PDAs dropped (resulting in cracked screen) • Lost (leave the phone somewhere)
Cross-cutting problem:Fidelity of evaluation prototypes iGlove iBracelet
Value of early-stage in situ evaluations: No pain, no gain. Where would this woman clip a pedometer or carry a large cell phone? The glow of the CareNetDisplay was often distractingfor participants who could see it while watching a movie or trying to sleep
Thank you! • Questions? Comments? • Contact us at: • everitt@cs.washington.edu • [sunny.consolvo, ian.e.smith, james.a.landay]@intel.com
