Tracking mobile workers' daily activities with the contextual activity sampling system

Hanni Muukkonen; Kai Hakkarainen; Shupin Li; Matti Vartiainen

doi:10.1007/978-3-319-07626-3_27

Tracking mobile workers' daily activities with the contextual activity sampling system

Hanni Muukkonen, Kai Hakkarainen, Shupin Li, Matti Vartiainen

Department of Industrial Engineering and Management

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

3 Citations (Scopus)

Abstract

The present study used smart phones to collect contextualized data on professionals' daily working activities; our purpose was to trace professionals' work engagement and socio-emotional activities. We used two tools, the Contextual Activity Sampling System (CASS-Q) and ContextLogger for collecting, in parallel, complementary self-report and location-sensor data. This allowed us to compare the types of data and their richness of information. The methods and instruments developed enabled one to trace various aspects of the mobile multi-locational workers' positive and negative self-reported affects in work contexts, as well as their activities and experiences of challenge and competence. The secondary working contexts (e.g., seminars, meetings, customer's office), especially, included interactions with others leading to both high positive and negative affects. The results also indicate that the participants' self-reported locations corresponded closely with the actual location documented by ContextLogger. Our results suggest possibilities for developing an algorithm that uses location information to automatically recognize certain activity contexts.

Original language	English
Title of host publication	Design, User Experience, and Usability
Subtitle of host publication	User Experience Design for Diverse Interaction Platforms and Environments - Third International Conference, DUXU 2014, Held as Part of HCI Int. 2014, Proc.
Publisher	Springer
Pages	289-300
Number of pages	12
Edition	PART 2
ISBN (Print)	9783319076256
DOIs	https://doi.org/10.1007/978-3-319-07626-3_27
Publication status	Published - 1 Jan 2014
MoE publication type	A4 Conference publication
Event	International Conference on Design, User Experience, and Usability - Heraklion, Greece Duration: 22 Jun 2014 → 27 Jun 2014 Conference number: 3

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	8518 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Design, User Experience, and Usability
Abbreviated title	DUXU
Country/Territory	Greece
City	Heraklion
Period	22/06/2014 → 27/06/2014

Keywords

event sampling
location data
mobile data collection
mobile work
self-report

Access to Document

10.1007/978-3-319-07626-3_27

Cite this

Muukkonen, H., Hakkarainen, K., Li, S., & Vartiainen, M. (2014). Tracking mobile workers' daily activities with the contextual activity sampling system. In Design, User Experience, and Usability: User Experience Design for Diverse Interaction Platforms and Environments - Third International Conference, DUXU 2014, Held as Part of HCI Int. 2014, Proc. (PART 2 ed., pp. 289-300). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8518 LNCS, No. PART 2). Springer. https://doi.org/10.1007/978-3-319-07626-3_27

Muukkonen, Hanni ; Hakkarainen, Kai ; Li, Shupin et al. / Tracking mobile workers' daily activities with the contextual activity sampling system. Design, User Experience, and Usability: User Experience Design for Diverse Interaction Platforms and Environments - Third International Conference, DUXU 2014, Held as Part of HCI Int. 2014, Proc.. PART 2. ed. Springer, 2014. pp. 289-300 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2).

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abstract = "The present study used smart phones to collect contextualized data on professionals' daily working activities; our purpose was to trace professionals' work engagement and socio-emotional activities. We used two tools, the Contextual Activity Sampling System (CASS-Q) and ContextLogger for collecting, in parallel, complementary self-report and location-sensor data. This allowed us to compare the types of data and their richness of information. The methods and instruments developed enabled one to trace various aspects of the mobile multi-locational workers' positive and negative self-reported affects in work contexts, as well as their activities and experiences of challenge and competence. The secondary working contexts (e.g., seminars, meetings, customer's office), especially, included interactions with others leading to both high positive and negative affects. The results also indicate that the participants' self-reported locations corresponded closely with the actual location documented by ContextLogger. Our results suggest possibilities for developing an algorithm that uses location information to automatically recognize certain activity contexts.",

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Muukkonen, H, Hakkarainen, K, Li, S & Vartiainen, M 2014, Tracking mobile workers' daily activities with the contextual activity sampling system. in Design, User Experience, and Usability: User Experience Design for Diverse Interaction Platforms and Environments - Third International Conference, DUXU 2014, Held as Part of HCI Int. 2014, Proc.. PART 2 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 8518 LNCS, Springer, pp. 289-300, International Conference on Design, User Experience, and Usability, Heraklion, Greece, 22/06/2014. https://doi.org/10.1007/978-3-319-07626-3_27

Tracking mobile workers' daily activities with the contextual activity sampling system. / Muukkonen, Hanni; Hakkarainen, Kai; Li, Shupin et al.
Design, User Experience, and Usability: User Experience Design for Diverse Interaction Platforms and Environments - Third International Conference, DUXU 2014, Held as Part of HCI Int. 2014, Proc.. PART 2. ed. Springer, 2014. p. 289-300 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8518 LNCS, No. PART 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

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AB - The present study used smart phones to collect contextualized data on professionals' daily working activities; our purpose was to trace professionals' work engagement and socio-emotional activities. We used two tools, the Contextual Activity Sampling System (CASS-Q) and ContextLogger for collecting, in parallel, complementary self-report and location-sensor data. This allowed us to compare the types of data and their richness of information. The methods and instruments developed enabled one to trace various aspects of the mobile multi-locational workers' positive and negative self-reported affects in work contexts, as well as their activities and experiences of challenge and competence. The secondary working contexts (e.g., seminars, meetings, customer's office), especially, included interactions with others leading to both high positive and negative affects. The results also indicate that the participants' self-reported locations corresponded closely with the actual location documented by ContextLogger. Our results suggest possibilities for developing an algorithm that uses location information to automatically recognize certain activity contexts.

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Muukkonen H, Hakkarainen K, Li S, Vartiainen M. Tracking mobile workers' daily activities with the contextual activity sampling system. In Design, User Experience, and Usability: User Experience Design for Diverse Interaction Platforms and Environments - Third International Conference, DUXU 2014, Held as Part of HCI Int. 2014, Proc.. PART 2 ed. Springer. 2014. p. 289-300. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-319-07626-3_27

Tracking mobile workers' daily activities with the contextual activity sampling system

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