Principles for Designing Context-Aware Applications for Physical Activity Promotion

Mobile devices with embedded sensors have become commonplace, carried by billions of people worldwide. Their potential to influence positive health behaviors such as physical activity in people is just starting to be realized. Two critical ingredients, an accurate understanding of human behavior and use of that knowledge for building computational models, underpin all emerging behavior change applications. Early research prototypes suggest that such applications would facilitate people to make difficult decisions to manage their complex behaviors. However, the progress towards building real-world systems that support behavior change has been much slower than expected. The extreme diversity in real-world contextual conditions and user characteristics has prevented the conception of systems that scale and support end-users’ goals. We believe that solutions to the many challenges of designing context-aware systems for behavior change exist in three areas: building behavior models amenable to computational reasoning, designing better tools to improve our understanding of human behavior, and developing new applications that scale existing ways of achieving behavior change. With physical activity as its focus, this thesis addresses some crucial challenges that can move the field forward. Specifically, this thesis provides the notion of sweet spots, a phenomenological account of how people make and execute their physical activity plans. The key contribution of this concept is in its potential to improve the predictability of computational models supporting physical activity planning. To further improve our understanding of the dynamic nature of human behavior, we designed and built Heed, a low-cost, distributed and situated self-reporting device. Heed’s single-purpose and situated nature proved its use as the preferred device for self-reporting in many contexts. We finally present a crowdsourcing system that leverages expert knowledge to write personalized behavior change messages for large-scale context-aware applications.PHDInformationUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144089/1/gparuthi_1.pd

Smartphones as steady companions: device use in everyday life and the economics of attention

This thesis investigates smartphone use in naturally occurring contexts with a dataset comprising 200 hours of audio-visual first-person recordings from wearable cameras, and self-confrontation interview video footage (N = 41 users). The situated context in which smartphone use takes place has often been overlooked because of the technical difficulty of capturing context of use, actual action of users, and their subjective experience simultaneously. This research project contributes to filling this gap, with a detailed, mixed-methods analysis of over a thousand individual phone engagement behaviours (EB). We observe that (a) the smartphone is a key structuring element in the flow of daily activities. Participants report complex strategies on how they manage engaging with or avoiding their devices. (b) Unexpectedly, we find that the majority of EB (89%) are initiated by users, not devices; users engage with the phone roughly every five minutes regardless of the context they are in. (c) A large portion of EB seems to stem from contextual cues and an unconscious urge to pick up the device, even when there is no clear reason to do so. d) Participants are surprised about, and often unhappy with how frequently they mindlessly reach for the phone. Our in-depth analysis unveils several overlapping layers of motivations and triggers driving EB. Monitoring incoming notifications, managing time use, responding to social pressures, actually completing a task with the phone, design factors, unconscious urges, as well as the accessibility of the device, and most importantly its affordance for distraction all contribute to picking up the phone. This user drive for EB is used by providers to feed the attention economy. So far, keeping the smartphone outside of the visual field and immediate reach has appeared as the only efficient strategy to prevent overuse

Exploring thermal discomfort amongst lower-limb prosthesis wearers

Amongst lower-limb prosthesis wearers, thermal discomfort is a common problem with an estimated prevalence of more than 50%. Overheating does not just create discomfort to the user, but it has been linked to excessive sweating, skin damage caused by a moist environment and friction. Due to impermeable prosthetic components and a warm moist environment, minor skin damage can result in skin infections that can lead to prosthesis cessation, increased social anxiety, isolation and depression. Despite the seriousness of thermal discomfort, few studies explore the issue, with research predominantly constrained to controlled laboratory scenarios, with only one out of laboratory study. In this thesis, studies investigate how thermal discomfort arises and what are the consequences of thermal discomfort for lower-limb prosthesis wearers. Research studies are designed around the principles of presenting lived experiences of the phenomenon and conducting research in the context of participants' real-life activities. A design exploration chapter investigates modifying liner materials and design to create a passive solution to thermal discomfort. However, this approach was found to be ineffective and unfeasible. Study 1 presents a qualitative study which investigates the user experience of a prosthesis, thermal discomfort and related consequences. Study 2 explores limb temperature of male amputees inside and outside the laboratory, with the latter also collecting perceived thermal comfort (PTC) data. Finally, Study 3 investigates thermal discomfort in the real-world and tracks limb temperature, ambient conditions, activities, and experience sampling of PTC. While there were no apparent relationships presented in sensor data, qualitative data revealed that in situations where prosthesis wearers perceived a lack of control, thermal discomfort seemed to be worse. When combined, the studies create two knowledge contributions. Firstly, the research provides a methodological contribution showing how to conduct mixed-methods research to obtain rich insights into complex prosthesis phenomena. Secondly, the research highlights the need to appreciate psychological and contextual factors when researching prosthesis wearer thermal comfort. The research contributions are also converted into an implication for prosthesis design. The concept of 'regaining control' to psychologically mitigate thermal discomfort could be incorporated into technologies by using 'on-demand' thermal discomfort relief, rather than 'always-on' solutions, as have been created in the past

Computational and Causal Approaches on Social Media and Multimodal Sensing Data: Examining Wellbeing in Situated Contexts

A core aspect of our lives is often embedded in the communities we are situated in. The interconnectedness of our interactions and experiences intertwines our situated context with our wellbeing. A better understanding of wellbeing will help us devise proactive and tailored support strategies. However, existing methodologies to assess wellbeing suffer from limitations of scale and timeliness. These limitations are surmountable by social and ubiquitous technologies. Given its ubiquity and wide use, social media can be considered a “passive sensor” that can act as a complementary source of unobtrusive, real-time, and naturalistic data to infer wellbeing. This dissertation leverages social media in concert with multimodal sensing data, which facilitate analyzing dense and longitudinal behavior at scale. This work adopts machine learning, natural language, and causal inference analysis to infer wellbeing of individuals and collectives, particularly in situated communities, such as college campuses and workplaces. Before incorporating sensing modalities in practice, we need to account for confounds. One such confound that might impact behavior change is the phenomenon of “observer effect” --- that individuals may deviate from their typical or otherwise normal behavior because of the awareness of being “monitored”. I study this problem by leveraging the potential of longitudinal and historical behavioral data through social media. Focused on a multimodal sensing study, I conduct a causal study to measure observer effect in social media behavior, and explain the observations through existing theory in psychology and social science. The findings provide recommendations to correcting biases due to observer effect in social media sensing for human behavior and wellbeing. The novelties and contributions of this dissertation are four-fold. First, I use social media data that uniquely captures the behavior of situated communities. Second, I adopt theory-driven computational and causal methods to make conclusive research claims on wellbeing dynamics. Third, I address major challenges with methods to combine social media with multimodal sensing data for a comprehensive understanding of human behavior. Fourth, I draw interpretations and explanations of online-data-driven offline inferences. This dissertation situates the findings in an interdisciplinary context, including psychology and social science, and bears implications from theoretical, practical, design, methodological, and ethical perspectives catering to various stakeholders, including researchers, practitioners, and policymakers.Ph.D

Designing personalised, authentic and collaborative learning with mobile devices: Confronting the challenges of remote teaching during a pandemic.

This article offers teachers a digital pedagogical framework, research-inspired and underpinned by socio-cultural theory, to guide the design of personalised, authentic and collaborative learning scenarios for students using mobile devices in remote learning settings during this pandemic. It provides a series of freely available online resources underpinned by our framework, including a mobile learning toolkit, a professional learning app, and robust, validated surveys for evaluating tasks. Finally, it presents a set of evidence-based principles for effective innovative teaching with mobile devices

Research-Informed Teaching in a Global Pandemic: "Opening up" Schools to Research

The teacher-research agenda has become a significant consideration for policy and professional development in a number of countries. Encouraging research-based teacher education programmes remains an important goal, where teachers are able to effectively utilize educational research as part of their work in school settings and to reflect on and enhance their professional development. In the last decade, teacher research has grown in importance across the three i’s of the teacher learning continuum: initial, induction and in-service teacher education. This has been brought into even starker relief with the global spread of COVID-19, and the enforced and emergency, wholesale move to digital education. Now, perhaps more than ever, teachers need the perspective and support of research-led practice, particularly in how to effectively use Internet technologies to mediate and enhance learning, teaching and assessment online, and new blended modalities for education that must be physically distant. The aim of this paper is to present a number of professional development open educational systems which exist or are currently being developed to support teachers internationally, to engage with, use and do research. Exemplification of the opening up of research to schools and teachers is provided in the chapter through reference to the European Union-funded Erasmus + project, BRIST: Building Research Infrastructures for School Teachers. BRIST is developing technology to coordinate and support teacher-research at a European level