Title

If Numbers Could Speak: Bringing "Quantified Self" to an Alternative Demographic

Authors

Mary Briggs

Document Type

Article

Journal/Book Title/Conference

USU Student Showcase

Publication Date

4-2014

Faculty Mentor

Victor Lee

Abstract

Quantified Self is a recent movement using technology to track, and attach a number to various aspects of a person's life. Much of this is enabled by wearable devices that track physical activity data. A person can easily track steps taken, sleep, calories burned, etc. in ways that have never been considered before technology made the data readily available. One interesting development is the voluntary sustained engagement and analysis of data among self quantifiers. Previous analysis suggests that the population most often identified in the Quantified Self (QS) movement include white, middle-age, affluent, educated males, from metropolitan areas. Because of the resources available to these individuals, the engagement with data might be a simple extension of other activities and resources they already have. My project included an effort to give those of a different demographic a chance to engage in QS activities. I gathered 5 Latina high school students who resided in a non-metropolitan area, and through video recorded focus groups I observed their experience with self quantification technologies. I observed definite preferences for aesthetic appeal and observed obstacles in finding researchable and personally relevant questions on what to quantify. Yet once the students used their devices, they shared why they were interested in tracking certain aspects of their lives, and how their families reacted to the technology. In this poster, I discuss how they interacted and understood their own data, and their interest levels in this activity. The project helps to inform what drives or inhibits people from engaging in Quantified Self activities, and examines what an atypical population can learn from these activities.

This document is currently not available here.

Share

COinS