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Evangelos Karapanos

Publications and source records attributed to Evangelos Karapanos.

9 recordsLinked to original sources

Contrasting Perspectives on Engagement Across Three Digital Behavior Change Interventions

We contrast three perspectives on engagement from three projects on the design of Digital Behavior Change Interventions (DBCIs), all conducted as part of the PhD thesis of the second author. We provide a reflection on this work with respect to engagement, discussing the motivation, the assumed effects of engagement, the measures of engagements and key insights of each project, as the well as the strategies employed to increase engagement.

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Motivating Healthy Water Intake through Prompting, Historical Information, and Implicit Feedback

We describe Hydroprompt, a prototype for sensing and motivating healthy water intake in work environments. In a 3-week field deployment of Hydroprompt, we evaluate the effectiveness of three approaches to behavior change: historical information enabling users to compare their water intake lev- els across different times of day and days of week, implicit feedback providing subtle cues to users on the current hydration levels, and explicit prompting at- tempting to remind participants when hydration falls below acceptable levels or when substantial amount of time has elapsed since the last sip.

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Designing for Different Stages in Behavior Change

The behavior change process is a dynamic journey with different informational and motivational needs across its different stages; yet current technologies for behavior change are static. In our recent deployment of Habito, an activity tracking mobile app, we found individuals "readiness" to behavior change (or the stage of behavior change they were in) to be a strong predictor of adoption. Individuals in the contemplation and preparation stages had an adoption rate of 56%, whereas individuals in precontemplation, action or maintenance stages had an adoption rate of only 20%. In this position paper we argue for behavior change technologies that are tailored to the different stages of behavior change.

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Footprint Tracker: reviewing lifelogs and reconstructing daily experiences

With the increasing emphasis on how mobile technologies are experienced in everyday life, researchers are increasingly emphasizing the use of in-situ methods such as Experience Sampling and Day Reconstruction. In our line of research we explore the concept of Technology-Assisted Reconstruction, in which passively logged behavior data assist in the later reconstruction of daily experiences. In this paper we introduce Footprint tracker, a web application that supports participants in reviewing lifelogs and reconstructing their daily experiences. We focus on three kinds of data: visual (as captured through Microsoft's sensecam), location, and context (i.e., SMS and calls received and made). We describe how Footprint Tracker supports the user in reviewing these lifelogs and outline a field study that attempts to inquire into whether and how this data support reconstruction from memory.

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Sense me: Supporting awareness in parent-child relationships through mobile sensing

We introduce Senseμ (pronounced "sense me"), a mobile application that aims at supporting awareness in parent- child relationships through the sensing capabilities of mobile devices. We discuss the relevance of three types of awareness information: physical activity inferred from accelerometers, verbal activity during class hours inferred from microphones, and social activity inferred from Bluetooth pair-wise proximity sensing. We describe how we attempt to contextualize these sensing data with the goal of supporting parents' awareness of the educational performance and social wellbeing of their children, as well as motivating and sustaining a two-way communication between parents and teachers over the long term.

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Beyond Experience Sampling: Evaluating Personal Informatics with Technology-Assisted Reconstruction

Experience Sampling has been considered the golden standard of in-situ measurement, yet, at the expense of high burden to participants. In this paper we propose Technology-Assisted Reconstruction (TAR), a methodological approach that combines passive logging of users' behaviors with use of these data in assisting the reconstruction of behaviors and experiences. Through a number of recent and ongoing projects we will discuss how TAR may be employed for the evaluation of personal informatics systems, but also, conversely, how ideas from the field of personal informatics may contribute towards the development of new methodologies for in-situ evaluation.

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Reconstructing Experiences through Sketching

We present iScale, a survey tool for the retrospective elicitation of longitudinal user experience data. iScale employs sketching in imposing a process in the reconstruction of one's experiences with the aim to minimize retrospection bias. Two versions, the Constructive and the Value-Account iScale, were motivated by two distinct theories on how people reconstruct emotional experiences from memory. These two versions were tested in two separate studies. Study 1 aimed at providing qualitative insight into the use of iScale and compared its performance to that of free-hand sketching. Study 2 compared the two versions of iScale to free recall, a control condition that does not influence the reconstruction process. Significant differences between iScale and free recall were found. Overall, iScale resulted in an increase in the amount, the richness, and the test-retest reliability of recalled information. These results provide support for the viability of retrospective techniques as a cost-effective alternative to longitudinal studies.

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The quantitative side of the Repertory Grid Technique: some concerns

User experience (UX) evaluation is gaining increased interest lately, both from academia and industry. In this paper we argue that UX evaluation needs to fulfill two important requirements: scalability, i.e. the ability to provide useful feedback in different stages of the design, and diversity, i.e. the ability to reflect the di-versity of opinions that may exist in different users. We promote the use of the Repertory Grid Technique as a promising UX evaluation technique and discuss some of our concerns regarding the quantitative side of its use.

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