Evaluating user experience under location quality variations: A framework for in-the-wild studies

Champika Ranasinghe; Sven Heitmann; Max Pfeiffer; Christian Kray

doi:10.1145/3338286.3344392

Evaluating user experience under location quality variations: A framework for in-the-wild studies

Champika Ranasinghe, Sven Heitmann, Max Pfeiffer, Christian Kray

Datamanagement & Biometrics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

4 Citations (Scopus)

1 Downloads (Pure)

Abstract

While lab-based approaches to evaluation of location-based services (LBSs) allow faster, cost-effective and less complicated evaluation of many aspects, they are limited in evaluating certain aspects, especially the ones related to usability and user experience (UX). Variations in the location information quality can negatively affect location-based UX. Lab-based evaluations are limited in factoring users' actual context, which includes location quality variations into the evaluation process. Therefore, to evaluate actual location-based UX, we need to evaluate LBSs in-the-wild with users under variations in the quality of location information. Currently, there is a lack of standard tools, methods, and frameworks for this purpose. Motivated by this factor, in this paper, we describe the Location Uncertainty Injection Framework (LUIF) for evaluating mobile LBSs in-the-wild with users under location quality variations. We also present the results of a study conducted to gain initial feedback on the potential use cases of the framework.

Original language	English
Title of host publication	MobileHCI '19
Subtitle of host publication	Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services
Place of Publication	New York, NY
Publisher	Association for Computing Machinery
ISBN (Electronic)	978-1-4503-6825-4
DOIs	https://doi.org/10.1145/3338286.3344392
Publication status	Published - 1 Oct 2019
Event	21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019 - Taipei, Taiwan Duration: 1 Oct 2019 → 4 Oct 2019 Conference number: 21

Conference

Conference	21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019
Abbreviated title	MobileHCI
Country/Territory	Taiwan
City	Taipei
Period	1/10/19 → 4/10/19

Keywords

Design of mobile location based services
Location information quality
Mobile location based services
User behavior
User experience
n/a OA procedure

Access to Document

10.1145/3338286.3344392

Cite this

Ranasinghe, C., Heitmann, S., Pfeiffer, M., & Kray, C. (2019). Evaluating user experience under location quality variations: A framework for in-the-wild studies. In MobileHCI '19: Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services Article 45 Association for Computing Machinery. https://doi.org/10.1145/3338286.3344392

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title = "Evaluating user experience under location quality variations: A framework for in-the-wild studies",

abstract = "While lab-based approaches to evaluation of location-based services (LBSs) allow faster, cost-effective and less complicated evaluation of many aspects, they are limited in evaluating certain aspects, especially the ones related to usability and user experience (UX). Variations in the location information quality can negatively affect location-based UX. Lab-based evaluations are limited in factoring users' actual context, which includes location quality variations into the evaluation process. Therefore, to evaluate actual location-based UX, we need to evaluate LBSs in-the-wild with users under variations in the quality of location information. Currently, there is a lack of standard tools, methods, and frameworks for this purpose. Motivated by this factor, in this paper, we describe the Location Uncertainty Injection Framework (LUIF) for evaluating mobile LBSs in-the-wild with users under location quality variations. We also present the results of a study conducted to gain initial feedback on the potential use cases of the framework.",

keywords = "Design of mobile location based services, Location information quality, Mobile location based services, User behavior, User experience, n/a OA procedure",

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Ranasinghe, C, Heitmann, S, Pfeiffer, M & Kray, C 2019, Evaluating user experience under location quality variations: A framework for in-the-wild studies. in MobileHCI '19: Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services., 45, Association for Computing Machinery, New York, NY, 21st International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2019, Taipei, Taiwan, 1/10/19. https://doi.org/10.1145/3338286.3344392

Evaluating user experience under location quality variations: A framework for in-the-wild studies. / Ranasinghe, Champika; Heitmann, Sven; Pfeiffer, Max et al.
MobileHCI '19: Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services. New York, NY: Association for Computing Machinery, 2019. 45.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Evaluating user experience under location quality variations

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AU - Ranasinghe, Champika

AU - Heitmann, Sven

AU - Pfeiffer, Max

AU - Kray, Christian

N1 - Conference code: 21

PY - 2019/10/1

Y1 - 2019/10/1

N2 - While lab-based approaches to evaluation of location-based services (LBSs) allow faster, cost-effective and less complicated evaluation of many aspects, they are limited in evaluating certain aspects, especially the ones related to usability and user experience (UX). Variations in the location information quality can negatively affect location-based UX. Lab-based evaluations are limited in factoring users' actual context, which includes location quality variations into the evaluation process. Therefore, to evaluate actual location-based UX, we need to evaluate LBSs in-the-wild with users under variations in the quality of location information. Currently, there is a lack of standard tools, methods, and frameworks for this purpose. Motivated by this factor, in this paper, we describe the Location Uncertainty Injection Framework (LUIF) for evaluating mobile LBSs in-the-wild with users under location quality variations. We also present the results of a study conducted to gain initial feedback on the potential use cases of the framework.

AB - While lab-based approaches to evaluation of location-based services (LBSs) allow faster, cost-effective and less complicated evaluation of many aspects, they are limited in evaluating certain aspects, especially the ones related to usability and user experience (UX). Variations in the location information quality can negatively affect location-based UX. Lab-based evaluations are limited in factoring users' actual context, which includes location quality variations into the evaluation process. Therefore, to evaluate actual location-based UX, we need to evaluate LBSs in-the-wild with users under variations in the quality of location information. Currently, there is a lack of standard tools, methods, and frameworks for this purpose. Motivated by this factor, in this paper, we describe the Location Uncertainty Injection Framework (LUIF) for evaluating mobile LBSs in-the-wild with users under location quality variations. We also present the results of a study conducted to gain initial feedback on the potential use cases of the framework.

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KW - User behavior

KW - User experience

KW - n/a OA procedure

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BT - MobileHCI '19

PB - Association for Computing Machinery

CY - New York, NY

Y2 - 1 October 2019 through 4 October 2019

ER -

Evaluating user experience under location quality variations: A framework for in-the-wild studies

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