Challenges of Quantified-Self: Encouraging Self-Reported Data Logging During Recurrent Smartphone Usage (bibtex)
by Visuri, Aku, van Berkel, Niels, Luo, Chu, Goncalves, Jorge, Ferreira, Denzil and Kostakos, Vassilis
Abstract:
We argue that improved data entry can motivate Quantified-Self (QS) users to better engage with QS applications. To improve data entry, we investigate the notion of transforming active smartphone usage into data logging contributions through alert dialogs. We evaluate this assertion in a 4-week long deployment with 48 participants. We collect 17,906 data entries, where 68.3% of the entries are reported using the alert dialogs. We demonstrate that QS applications can benefit from alert dialogs: to increase data precision, frequency, and reduce the probability of forgetfulness in data logging. We investigate the impact of usage session type (e.g., sessions with different goals or durations) and the assigned reminder delay on frequency of data contributions. We conclude with insights gathered from our investigation, and the implications they have on future designs.
Reference:
A. Visuri, N. van Berkel, C. Luo, J. Goncalves, D. Ferreira, V. Kostakos, "Challenges of Quantified-Self: Encouraging Self-Reported Data Logging During Recurrent Smartphone Usage", in Proceedings of the British Human Computer Interaction Conference (British HCI'17), 2017.
Bibtex Entry:
@inproceedings{Visuri2017QSSmartphone,
	Abstract = {We argue that improved data entry can motivate Quantified-Self (QS) users to better engage with QS applications. To improve data entry, we investigate the notion of transforming active smartphone usage into data logging contributions through alert dialogs. We evaluate this assertion in a 4-week long deployment with 48 participants. We collect 17,906 data entries, where 68.3% of the entries are reported using the alert dialogs. We demonstrate that QS applications can benefit from alert dialogs: to increase data precision, frequency, and reduce the probability of forgetfulness in data logging. We investigate the impact of usage session type (e.g., sessions with different goals or durations) and the assigned reminder delay on frequency of data contributions. We conclude with insights gathered from our investigation, and the implications they have on future designs.},
	Author = {Visuri, Aku and van Berkel, Niels and Luo, Chu and Goncalves, Jorge and Ferreira, Denzil and Kostakos, Vassilis},
	Booktitle = {Proceedings of the British Human Computer Interaction Conference},
	Location = {British HCI'17},
	Title = {Challenges of Quantified-Self: Encouraging Self-Reported Data Logging During Recurrent Smartphone Usage},
	Type = {Conference Paper},
	Url = {https://www.nielsvanberkel.com/files/publications/bhci2017b.pdf},
	Year = {2017}}
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