MyExperience: a system for in situ tracing and capturing of user feedback on mobile phones

This paper presents MyExperience, a system for capturing both objective and subjective in situ data on mobile computing activities. MyExperience combines the following two techniques: 1) passive logging of device usage, user context, and environmental sensor readings, and 2) active context-triggered user experience sampling to collect in situ, subjective user feedback. MyExperience currently runs on mobile phones and supports logging of more than 140 event types, including: 1) device usage such as communication, application usage, and media capture, 2) user context such as calendar appointments, and 3) environmental sensing such as Bluetooth and GPS. In addition, user experience sampling can be targeted to moments of interest by triggering off sensor readings. We present several case studies of field deployments on people's personal phones to demonstrate how MyExperience can be used effectively to understand how people use and experience mobile technology.

[1]  Daniel J. Barrett,et al.  An Introduction to Computerized Experience Sampling in Psychology , 2001 .

[2]  Andy Hopper,et al.  Deploying and evaluating a location-aware system , 2005, MobiSys '05.

[3]  Ingrid Mulder,et al.  What's Your Lab Doing in My Pocket? Supporting Mobile Field Studies with SocioXensor , 2006 .

[4]  Leysia Palen,et al.  Voice-mail diary studies for naturalistic data capture under mobile conditions , 2002, CSCW '02.

[5]  Alex Pentland,et al.  Social serendipity: mobilizing social software , 2005, IEEE Pervasive Computing.

[6]  Mike Y. Chen,et al.  Improved access point selection , 2006, MobiSys '06.

[7]  Connor Graham,et al.  A Review of Mobile HCI Research Methods , 2003, Mobile HCI.

[8]  Bill N. Schilit,et al.  Place Lab: Device Positioning Using Radio Beacons in the Wild , 2005, Pervasive.

[9]  Patrick Losquin,et al.  Gather customer's real usage on mobile phones , 2005, Mobile HCI.

[10]  David Kotz,et al.  Analysis of a Campus-Wide Wireless Network , 2002, MobiCom '02.

[11]  Sunny Consolvo,et al.  Using the Experience Sampling Method to Evaluate Ubicomp Applications , 2003, IEEE Pervasive Comput..

[12]  Mingyan Liu,et al.  Building realistic mobility models from coarse-grained traces , 2006, MobiSys '06.

[13]  Minna Isomursu,et al.  Experience clip: method for user participation and evaluation of mobile concepts , 2004, PDC 04.

[14]  Dan Frankowski,et al.  An experiment in discovering personally meaningful places from location data , 2005, CHI Extended Abstracts.

[15]  Brad A. Myers,et al.  Past, Present and Future of User Interface Software Tools , 2000, TCHI.

[16]  Ling Bao,et al.  A context-aware experience sampling tool , 2003, CHI Extended Abstracts.

[17]  Gregory D. Abowd,et al.  Farther Than You May Think: An Empirical Investigation of the Proximity of Users to Their Mobile Phones , 2006, UbiComp.

[18]  Mika Raento,et al.  ContextPhone: a prototyping platform for context-aware mobile applications , 2005, IEEE Pervasive Computing.

[19]  James A. Landay,et al.  Conducting In Situ Evaluations for and With Ubiquitous Computing Technologies , 2007 .

[20]  Jonna Häkkilä,et al.  'It's like if you opened someone else's letter': user perceived privacy and social practices with SMS communication , 2005, Mobile HCI.

[21]  Kori Inkpen Quinn,et al.  It's a jungle out there: practical considerations for evaluation in the city , 2005, CHI EA '05.

[22]  Mike Y. Chen,et al.  Practical Metropolitan-Scale Positioning for GSM Phones , 2006, UbiComp.

[23]  M. Csíkszentmihályi,et al.  Validity and Reliability of the Experience‐Sampling Method , 1987, The Journal of nervous and mental disease.

[24]  M. Csíkszentmihályi,et al.  Validity and Reliability of the Experience‐Sampling Method , 1987, The Journal of nervous and mental disease.

[25]  Gordon Bell,et al.  Passive capture and ensuing issues for a personal lifetime store , 2004, CARPE'04.

[26]  Jennifer Mankoff.  Crossing Qualitative and Quantitative Evaluation in the domain of Ubiquitous Computing , 2005 .

[27]  Louise Barkhuus.  Why everyone loves to text message: social management with SMS , 2005, GROUP '05.

[28]  Mike Y. Chen,et al.  Voting with your feet : An investigative study of the relationship between place visit behavior and preference , 2006 .

[29]  Gaetano Borriello,et al.  A Practical Approach to Recognizing Physical Activities , 2006, Pervasive.

[30]  Kerry Rodden,et al.  Mobile search with text messages: designing the user experience for google SMS , 2005, CHI EA '05.

[31]  Rebecca E. Grinter,et al.  Y Do Tngrs Luv 2 Txt Msg? , 2001, ECSCW.

[32]  Songwu Lu,et al.  A study of the short message service of a nationwide cellular network , 2006, IMC '06.

[33]  John Rieman,et al.  The diary study: a workplace-oriented research tool to guide laboratory efforts , 1993, INTERCHI.

[34]  Jeffrey Heer,et al.  Momento: support for situated ubicomp experimentation , 2007, CHI.

[35]  Mark D. Corner,et al.  LLAMA: An Adaptive Strategy for Performing Background Tasks on Mobile Devices , 2006, Seventh IEEE Workshop on Mobile Computing Systems & Applications (WMCSA'06 Supplement).

[36]  Yi-Min Wang,et al.  Flight Data Recorder: Always-on Tracing and Scalable Analysis of Persistent State Interactions to Improve Systems and Security Management , 2006 .