From Offshore Operation to Onshore Simulator: Using Visualized Ethnographic Outcomes to Work with Systems Developers

This paper focuses on the process of translating insights from a Computer Supported Cooperative Work (CSCW)-based study, conducted on a vessel at sea, into a model that can assist systems developers working with simulators, which are used by vessel operators for training purposes on land. That is, the empirical study at sea brought about rich insights into cooperation, which is important for systems developers to know about and consider in their designs. In the paper, we establish a model that primarily consists of a ‘computational artifact’. The model is designed to support researchers working with systems developers. Drawing on marine examples, we focus on the translation process and investigate how the model serves to visualize work activities; how it addresses relations between technical and computational artifacts, as well as between functions in technical systems and functionalities in cooperative systems. In turn, we link design back to fieldwork studies

Ambiguity for Social Self-tracking Practices: Exploring an emerging design space

Ambiguity is gaining attention in self-tracking research as a means to go beyond the mere quantification of body signals. Recent research has suggested that ambiguity can be used even to enable social connection mediated by personal data. To explore this design space more widely, we organized two design workshops with a total of 67 participants. In this paper, we present three design concepts, as outcomes of the workshops, which use ambiguity to enable social self-tracking practices. We then discuss how these concepts demonstrate the potential of ambiguity to encourage collective sense-making, directly impact the user’s social relationships, and offer multifaceted perspectives on reality

Working Together in a PhamilySpace: Facilitating Collaboration on Healthy Behaviors Over Distance

Studies have shown that interpersonal relationships such as families and friends are an important source of support and encouragement to those who seek to engage in healthier habits. However, challenges related to geographic distance may hinder those relationships from fully collaborating and engaging in healthy living together. To explore this domain, we developed and deployed a lightweight photo-based application called PhamilySpace with a week-long intervention. Our goal is to examine family members\u27 and friends\u27 engagement and awareness on healthy behaviors while living apart. Our analysis of the semi-structured interviews, pre/post-intervention instruments, and application logs suggests three main benefits of interventions for health promotion in this context: (1) increased awareness on acts of health; (2) reciprocal sharing of health information supports social accountability over distance; and (3) positive dialogue around health enhances support on healthy living. By providing insights into distributed family/friends interactions and experiences with the application, we identify benefits, challenges, and opportunities for future design interventions that promote healthy behaviors

Leveraging Learners for Teaching Programming and Hardware Design at Scale

In a massive open online course (MOOC), a single pro-gramming or digital hardware design exercise may yield thousands of student solutions that vary in many ways, some superï¬ cial and some fundamental. Understanding large-scale variation in student solutions is a hard but important problem. For teachers, this variation can be a source of pedagogically valuable examples and expose corner cases not yet covered by autograding. For students, the variation in a large class means that other students may have struggled along a similar solution path, hit the same bugs, and can offer hints based on that earned expertise. We developed three systems to take advantage of the solu-tion variation in large classes, using program analysis and learnersourcing. All three systems have been evaluated using data or live deployments in on-campus or edX courses with thousands of students

Data work: how energy advisors and clients make IoT data accountable

We present fieldwork findings from the deployment of an interactive sensing system that supports the work of energy advisors who give face-to-face advice to low-income households in the UK. We focus on how the system and the data it produced are articulated in the interactions between professional energy advisors and their clients, and how they collaboratively anticipate, rehearse, and perform data work. In addition to documenting how the system was appropriated in advisory work, we elaborate the ‘overhead cost’ of building collaborative action into connected devices and sensing systems, and the commensurate need to support discrete workflows and accountability systems to enable the methodical incorporation of the IoT into collaborative action. We contribute an elaboration of the social, collaborative methods of data work relevant to those who seek to design and study collaborative IoT systems

Conflict and Computation on Wikipedia: a Finite-State Machine Analysis of Editor Interactions

What is the boundary between a vigorous argument and a breakdown of relations? What drives a group of individuals across it? Taking Wikipedia as a test case, we use a hidden Markov model to approximate the computational structure and social grammar of more than a decade of cooperation and conflict among its editors. Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped, sometimes for months, in a computational subspace associated with significantly higher levels of conflict-tracking "revert" actions. Distinct patterns of behavior characterize the lower-conflict subspace, including tit-for-tat reversion. While a fraction of the transitions between these subspaces are associated with top-down actions taken by administrators, the effects are weak. Surprisingly, we find no statistical signal that transitions are associated with the appearance of particularly anti-social users, and only weak association with significant news events outside the system. These findings are consistent with transitions being driven by decentralized processes with no clear locus of control. Models of belief revision in the presence of a common resource for information-sharing predict the existence of two distinct phases: a disordered high-conflict phase, and a frozen phase with spontaneously-broken symmetry. The bistability we observe empirically may be a consequence of editor turn-over, which drives the system to a critical point between them.Comment: 23 pages, 3 figures. Matches published version. Code for HMM fitting available at http://bit.ly/sfihmm ; time series and derived finite state machines at bit.ly/wiki_hm

Webstrates: demonstrating the potential of Shareable Dynamic Media

International audienceShareable Dynamic Media is our vision for an interactive computing environment that blurs the distinction between documents and applications, characterized by three key properties: malleability, so that users can appropriate and repurpose media in idiosyncratic ways; shareability, so that users can collaborate on any type of content; and dis-tributability, so that users can access and manipulate media across diverse devices and platforms. Webstrates is a prototype web-based environment designed to explore this vision. It supports real-time sharing of any web content, as well as transclusion to flexibly combine and assemble multiple media together. The demonstration illustrates the power of Webstrates and Shared Dynamic Media through several scenarios, such as collaborative authoring, distributed slideshow presentation with audience participation, collabo-rative programming, and shareable window management