Stop questioning me!: towards optimizing user involvement during data collection on mobile devices

Nicholas Micallef; Michael Just; Lynne Baillie; Hilmi Gunes Kayacik

doi:10.1145/2493190.2494426

Stop questioning me!: towards optimizing user involvement during data collection on mobile devices

Nicholas Micallef, Michael Just, Lynne Baillie, Hilmi Gunes Kayacik

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Current methods of behavioral data collection from mobile devices either require significant involvement from participants to verify the 'ground truth' of the data, or approximations that involve post-experiment comparisons to seed data. In this paper we argue that user involvement can be gracefully reduced by performing more intelligent seed comparisons. We aim to reduce the participant involvement to the 'most interesting' temporal slots, both during the experiment and in post-experiment verification. We carried out a 2 week study with 4 users, consisting of an initial opportunistic gathering of mobile sensor data. Our findings suggest that by using such a method we can significantly reduce user involvement.

Original language	English
Title of host publication	MobileHCI 2013
Subtitle of host publication	Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services
Publisher	ACM
Pages	588-593
Number of pages	6
ISBN (Print)	9781450322737
DOIs	https://doi.org/10.1145/2493190.2494426
Publication status	Published - 27 Aug 2013

Keywords

mobile devices
data collection methods
mobile sensor data
user involvement

Documents and Links

10.1145/2493190.2494426

Cite this

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title = "Stop questioning me!: towards optimizing user involvement during data collection on mobile devices",

abstract = "Current methods of behavioral data collection from mobile devices either require significant involvement from participants to verify the 'ground truth' of the data, or approximations that involve post-experiment comparisons to seed data. In this paper we argue that user involvement can be gracefully reduced by performing more intelligent seed comparisons. We aim to reduce the participant involvement to the 'most interesting' temporal slots, both during the experiment and in post-experiment verification. We carried out a 2 week study with 4 users, consisting of an initial opportunistic gathering of mobile sensor data. Our findings suggest that by using such a method we can significantly reduce user involvement.",

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author = "Nicholas Micallef and Michael Just and Lynne Baillie and Kayacik, {Hilmi Gunes}",

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month = aug,

day = "27",

doi = "10.1145/2493190.2494426",

language = "English",

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booktitle = "MobileHCI 2013",

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Stop questioning me!: towards optimizing user involvement during data collection on mobile devices. / Micallef, Nicholas; Just, Michael; Baillie, Lynne; Kayacik, Hilmi Gunes.

MobileHCI 2013: Proceedings of the 15th international conference on Human-computer interaction with mobile devices and services. ACM, 2013. p. 588-593.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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T1 - Stop questioning me!: towards optimizing user involvement during data collection on mobile devices

AU - Micallef, Nicholas

AU - Just, Michael

AU - Baillie, Lynne

AU - Kayacik, Hilmi Gunes

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Y1 - 2013/8/27

N2 - Current methods of behavioral data collection from mobile devices either require significant involvement from participants to verify the 'ground truth' of the data, or approximations that involve post-experiment comparisons to seed data. In this paper we argue that user involvement can be gracefully reduced by performing more intelligent seed comparisons. We aim to reduce the participant involvement to the 'most interesting' temporal slots, both during the experiment and in post-experiment verification. We carried out a 2 week study with 4 users, consisting of an initial opportunistic gathering of mobile sensor data. Our findings suggest that by using such a method we can significantly reduce user involvement.

AB - Current methods of behavioral data collection from mobile devices either require significant involvement from participants to verify the 'ground truth' of the data, or approximations that involve post-experiment comparisons to seed data. In this paper we argue that user involvement can be gracefully reduced by performing more intelligent seed comparisons. We aim to reduce the participant involvement to the 'most interesting' temporal slots, both during the experiment and in post-experiment verification. We carried out a 2 week study with 4 users, consisting of an initial opportunistic gathering of mobile sensor data. Our findings suggest that by using such a method we can significantly reduce user involvement.

KW - mobile devices

KW - data collection methods

KW - mobile sensor data

KW - user involvement

U2 - 10.1145/2493190.2494426

DO - 10.1145/2493190.2494426

M3 - Conference contribution

SN - 9781450322737

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EP - 593

BT - MobileHCI 2013

PB - ACM

ER -

Stop questioning me!: towards optimizing user involvement during data collection on mobile devices

Abstract

Keywords

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