A stage-based model of personal informatics systems

By Ian Li, Anind K. Dey, J. Forlizzi. International Conference on Human Factors in Computing Systems, 2010

1,253 citations recorded by the source corpus.

Subfields: Demography, Information Systems and Management, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/66a95b2249fc239edb14e6dc180582652257de7e

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Citations in the corpus

Why we use and abandon smart devices (2015, background): “terms that have been used to refer to smart devices are personal informatics systems [16] and quantified self [5].”
Examining Menstrual Tracking to Inform the Design of Personal Informatics Tools (2017, background): “’s definition of personal informatics as tracking to obtain self-knowledge [25].”
Personal Visualization and Personal Visual Analytics (2015, background): “As PV&PVA research broadens the scope of visualization and visual analytics, it also subsumes many related fields, including casual InfoVis [69], InfoVis for the Masses [21], persuasive computing [30] and personal informatics [56], [59].”
Translating Learning into Numbers: A Generic Framework for Learning Analytics (2012, background): “, humancomputer interaction systems that support this process (Li et al., 2010).”
Exercise as Labour: Quantified Self and the Transformation of Exercise into Labour (2014, neutral): “been conducted particularly in the field of human computer interaction [2], which has explored the”
Learning Analytics Dashboard Applications (2013, methodology): “However, as illustrated in Figure 1, the process model adds greater detail between the reflection and action steps of Li et al.’s (2010) stage-based model and generalizes the action stage to impact.”
No longer wearing: investigating the abandonment of personal health-tracking technologies on craigslist (2015, background): “In addition to studying these technologies from the perspective of health and wellness [22, 28, 34], HCI researchers also study their potential for improving selfknowledge (personal informatics) [25, 26], augmenting memory [18], and reducing environmental impact [10].”
Use and Adoption Challenges of Wearable Activity Trackers (2015, methodology): “Li et al. (2010) pointed out that most research focuses primarily on the collection and the reflection phase (e.g., Sellen & Whittaker, 2010), and there exists an opportunity to improve the other stages.”
Measuring Large-Scale Social Networks with High Resolution (2014, background): “We are interested in studying how personal data can be used to provide feedback about individual behavior and promote self-awareness and positive behavior change, which is an active area of research in Personal Informatics [125].”
Personal tracking as lived informatics (2014, background): “’s staged model of personal informatics systems [9] is often cited as a key representation for this area.”
Self-tracking cultures: towards a sociology of personal informatics (2014, background): “This research has been valuable in identifying such factors as the personal benefits and rewards that people gain from engaging in self-tracking and the reasons why people take up, discard or continue these practices (Kamal et al., 2010; Li et al., 2010; Li et al., 2011; MacLeod et al., 2013; Rooksb”