abstract

Wake-Up Task: Understanding Users in Task-based Mobile Alarm App

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Minsam KoAuthors Info & Claims

CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

Paper No.: LBW0253, Pages 1 - 6

https://doi.org/10.1145/3290607.3312765

Published: 02 May 2019 Publication History

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Abstract

Popular alarm apps are offering task-based alarms that do not allow the user to dismiss an alarm unless they complete a specific task (e.g., solving math problems). Because such wake-up tasks cause discomforts, their usefulness and necessity could vary among individuals and their context. In this work, we aimed to understand the characteristics of Alarmy (task-based alarm app) users who (dis) likes wake-up task in terms of alarm set usage. We grouped 8,500 US users into three according to the proportion of the task selection and investigated group-wise usage differences. We found significant usage differences among the groups in terms of (1) set frequency, (2) set time, and (3) set consistency, possibly caused by consistent needs and task difficulty. The results suggest promising directions for inconvenient interaction and behavior change research.

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Cited By

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Oh KKo JJin NHan SYoon CShin JKo M(2024)Understanding Morning Emotions by Analyzing Daily Wake-Up Alarm Usage: Longitudinal Observational StudyJMIR Human Factors10.2196/5083511(e50835)Online publication date: 29-Nov-2024
https://doi.org/10.2196/50835
Oh KKo JShin JKo M(2022)Utilizing Wake-Up Tasks for Morning Behavior Change: Development and Usability Study (Preprint)JMIR Formative Research10.2196/39497Online publication date: 25-May-2022
https://doi.org/10.2196/39497
Xun WZhang PLiu ZMeng YZheng YZou RRen X(2022)SleepHill: Designing an Incrementally Bouncing Pillow as a Comfortable Wake-Up ApproachEntertainment Computing – ICEC 202210.1007/978-3-031-20212-4_27(333-341)Online publication date: 24-Oct-2022
https://doi.org/10.1007/978-3-031-20212-4_27

Index Terms

Wake-Up Task: Understanding Users in Task-based Mobile Alarm App
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies

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Published In

CHI EA '19: Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems

May 2019

3673 pages

ISBN:9781450359719

DOI:10.1145/3290607

General Chairs:
Stephen Brewster
University of Glasgow, Scotland, UK
,
Geraldine Fitzpatrick
TU Wien, Austria
,
Program Chairs:
Anna Cox
University College London, UK
,
Vassilis Kostakos
University of Melbourne, Australia

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

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Published: 02 May 2019

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National Research Foundation of Korea (NRF)

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CHI '19

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SIGCHI

CHI '19: CHI Conference on Human Factors in Computing Systems

May 4 - 9, 2019

Glasgow, Scotland Uk

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Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

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Oh KKo JJin NHan SYoon CShin JKo M(2024)Understanding Morning Emotions by Analyzing Daily Wake-Up Alarm Usage: Longitudinal Observational StudyJMIR Human Factors10.2196/5083511(e50835)Online publication date: 29-Nov-2024
https://doi.org/10.2196/50835
Oh KKo JShin JKo M(2022)Utilizing Wake-Up Tasks for Morning Behavior Change: Development and Usability Study (Preprint)JMIR Formative Research10.2196/39497Online publication date: 25-May-2022
https://doi.org/10.2196/39497
Xun WZhang PLiu ZMeng YZheng YZou RRen X(2022)SleepHill: Designing an Incrementally Bouncing Pillow as a Comfortable Wake-Up ApproachEntertainment Computing – ICEC 202210.1007/978-3-031-20212-4_27(333-341)Online publication date: 24-Oct-2022
https://doi.org/10.1007/978-3-031-20212-4_27

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Identifying diverse usage behaviors of smartphone apps

Predicting task difficulty for different task types

Reducing Energy Consumption of Alarm-induced Wake-ups on Android Smartphones

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