Applying quantified self approaches to support reflective learning

Rivera-Pelayo, Verónica; Zacharias, Valentin; Müller, Lars; Braun, Simone

doi:10.1145/2330601.2330631

Cited by 63 publications

(33 citation statements)

References 4 publications

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“…has been designed for students empowerment in open learning environments [15][16] [17] in the "quantified self" perspective [18]. It collects tracking data from group blogs and twitter (post, comments, tweet).…”

Section: A Visualizing Progresses and Performaces In E-learning Envimentioning

confidence: 99%

Visualizing student engagement in e-learning environment

Pesare

Roselli

Rossano

2016

International Conferences on Distributed Multimedia Systems

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Abstract-The learning assessment in e-learning contexts is one of the latest challenges for educational technology researchers. One of the main issues to be addressed is the definition of dimensions that should be used to measure the learning effectiveness. In this perspective, the research work aims at defining the engagement indicators useful to assess the active participation of students in social learning environments. Moreover, the paper presents the design and implementation of Learning Dashboards aimed at visualizing the student engagement in online communities where the engagement and involvement of students are the key factors for successful learning.

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Section: A Visualizing Progresses and Performaces In E-learning Envimentioning

confidence: 99%

Visualizing student engagement in e-learning environment

Pesare

Roselli

Rossano

2016

International Conferences on Distributed Multimedia Systems

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“…Self-tracking and Quantified Self technologies (e.g., Fitbit, Jawbone Up, Nike Fuel, WakeMate, Withings Scale) belong to these types of systems that focus on data collection and quantification of a variety of everyday activities (e.g., work, leisure, and self-care) such as diet, exercise, sleeping patterns, weight, blood pressure, hearing function, work productivity, social behaviour, alcohol and tobacco consumption, and so on (Lupton 2013b;Swan 2012;Wiederhold 2012;Yau and Schneider 2009). The Quantified Self movement is rather experimental by nature, and the movement's followers measure, test, and reflect on their bio-values over time (Rivera-Pelayo et al 2012). Hence, Quantified Self is empirical, rather than built on proven research models (Rivera-Pelayo et al 2012).…”

Section: Preventive Self-monitoring Technology Quantified Self and mentioning

confidence: 99%

“…The Quantified Self movement is rather experimental by nature, and the movement's followers measure, test, and reflect on their bio-values over time (Rivera-Pelayo et al 2012). Hence, Quantified Self is empirical, rather than built on proven research models (Rivera-Pelayo et al 2012). …”

Section: Preventive Self-monitoring Technology Quantified Self and mentioning

confidence: 99%

On preventive blood pressure self-monitoring at home

Verdezoto

Grönvall

2015

Cogn Tech Work

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Self-monitoring activities are increasingly parts of people's everyday lives. Some of these measurements are performed voluntary rather than being referred by a physician, and conducted because of either a preventive health interest, or to better understand the body and its functions (so-called 'Quantified Self'). In this article, we explore socio-technical complexities that may occur when introducing preventive health-measurement technologies into older adults' daily routines and everyday lives. In particular, the original study investigated blood pressure (BP) measurement in nonclinical settings, to understand existing challenges, and uncover opportunities for self-monitoring technologies to support preventive healthcare activities among older adults. From our study, several aspects emerged that are important to consider when designing preventive self-monitoring technology, such as the complexity of guidelines for selfmeasuring, the importance of interpretation, understanding and health awareness, sharing self-monitoring information for prevention, various motivational factors, the role of the doctor in prevention, the home as a distributed information space, and so on. An awareness of these aspects may help designers to develop better support tools for people's preventive self-monitoring needs, compared to existing solutions. Supporting the active and informed individual may improve their self-care, awareness, and implementation of preventive care. Based on our study, we reflect on the findings to illustrate how these aspects may also inform both people engaged in Quantified Self activities and designers alike, and the tools and approaches that have sprung from the so-called 'Quantified Self' movement.

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“…In the literature, a growing number of scholars have emphasized that QS devices are powerful tools for engaging people in self-reflection and increasing their awareness (Li, Dey & Forlizzi, 2011;Rivera-Pelayo et al, 2012). Recently, wearable smart objects that automatically collect data have received interest among educators, as well as researchers in the field of teaching and learning.…”

Section: Introductionmentioning

confidence: 99%

Reflection in Learning through a Self-monitoring Device: Design Research on EEG Self-Monitoring during a Study Session

Durall¹,

Leinonen²,

Salvat³

et al. 2017

Designs for Learning

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The increasing availability of self-monitoring technologies has created opportunities for gaining awareness about one's own behavior and reflecting on it. In teaching and learning, there is interest in using self-monitoring technologies, but very few studies have explored the possibilities. In this paper, we present a design study that investigates a technology (called Feeler) that guides students to follow a specific learning script, monitors changes in their electroencephalogram (EEG) while studying, and later provides visualization of the EEG data. The results are two-fold: (1) the hardware/software prototype and (2) the conclusions from the proof-of-concept research conducted with the prototype and six participants. In the research, we collected qualitative data from interviews to identify whether the prototype supported students to develop their reflective skills. The thematic analysis of the interviews showed that the Feeler's learning script and visualization of the EEG data supported greater levels of reflection by fostering students' curiosity, puzzlement, and personal inquiry. The proof-of-concept research also provided insights into several factors, such as the value of personal experience, the challenge of assumptions, and the contextualization of the data that trigger reflective thinking. The results validate the design concept and the role of the prototype in supporting awareness of and reflection about students' mental states when they perform academic tasks.

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Applying quantified self approaches to support reflective learning

Cited by 63 publications

References 4 publications

Visualizing student engagement in e-learning environment

Visualizing student engagement in e-learning environment

On preventive blood pressure self-monitoring at home

Reflection in Learning through a Self-monitoring Device: Design Research on EEG Self-Monitoring during a Study Session

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