This paper explores the nature and potential of improvisation as a method for learning and teaching in CSCW and HCI. It starts by reviewing concepts of improvisational learning in classic and more recent work in educational theory, art and music, and HCI that emphasize the reconstructive, materially-driven, error-engaged, transgressive, and collaborative nature of human learning processes. It then describes three pedagogical interventions of our own in which improvisational techniques were deployed as methods of teaching and learning. From this integrated study, we report specific pedagogical conditions (socio-material evaluations, multi-sensory practices, and making safe spaces for error) that can support improvisational learning, and three common challenges of HCI pedagogy – relevance, assessment, and inclusion that improvisational methods can help to address.
This paper examines the role of technoscientific speculation in large-scale development projects in postcolonial spaces, building on recent work in STS, postcolonial studies in and beyond CSCW, and design research. We analyze two historical cases of technology-infused development projects in the Canadian province of Newfoundland and Labrador and in Jamaica. We find that speculation in these contexts remixes the constructive stance toward speculation typical for normative technoscience with the critical, contesting orientation of speculative design. Conflicts between these stances are resolved by leveraging fantasy for pragmatic ends, grounding audacious fictions in imported realities, unmooring from conventional understandings of linear technological progress, and using even conservative futures to trouble colonial conventions.
https://doi.org/10.1145/3449195
Causal knowledge is of interest in many areas, such as statistics and machine learning, as it allows people and algorithms to predict outcomes and make data-driven decisions. Researchers in CSCW have proposed tools and workflows to externalize causal knowledge or beliefs from a group of people; however, most of the generated causal diagrams lack a deeper understanding of the causal mechanisms or could not capture diverse beliefs. By integrating narratives with causal diagrams, we implemented an interactive system that allows users to 1) write narratives to rationalize their perceived causal relationships, 2) visualize their causal models using directed diagrams, and 3) review and utilize others' causal diagrams and narratives. We conducted a user study (N=20) to learn how participants leveraged this integrated approach to externalize their perceived causal models for a given application context. Our results showed that the approach implemented in our tool enabled the externalization of users' causal beliefs (e.g., how and why a causal relationship might occur), allowed blind spots of individuals' causal reasoning to be revealed (e.g., learning new ideas from peers), and inspired their causal reasoning (e.g., revising or adding new causal relationships). We also identified the individual differences in people's causal beliefs and observed the impacts of showing others' causal models when one is building their causal diagram and narratives. This work provides practical design implications for developing collaborative tools that facilitate capturing and sharing causal beliefs.
https://doi.org/10.1145/3479588
Building and maintaining common ground is vital for effective collaboration in CSCW. Moreover, subtle changes in a CSCW user interface can significantly impact grounding and collaborative processes. Yet, researchers and technology designers lack tools to understand how specific user interface designs may hinder or facilitate communication grounding. In this work, we leverage the well-established theory of communication grounding to develop a visual framework, called Joint Action Storyboards (JASs), to analyze and articulate how interaction minutiae of a CSCW environment impact the costs of communication grounding. JASs can depict an integrated view of mental actions of collaborators, their physical interactions with each other and the CSCW environment, and the corresponding grounding costs incurred. We present the development of JASs and discuss its various benefits for HCI and CSCW research. Through a series of case studies, we demonstrate how JASs provide an analysis tool for researchers and technology designers and serve as a tool to articulate the impact of interaction minutiae on communication grounding.
https://doi.org/10.1145/3449102
Designing future IoT ecosystems requires new approaches and perspectives to understand everyday practices. While researchers recognize the importance of understanding social aspects of everyday objects, limited studies have explored the possibilities of combining data-driven patterns with human interpretations to investigate emergent relationships among objects. This work presents Thing Constellation Visualizer (thingCV), a novel interactive tool for visualizing the social network of objects based on their co-occurrence as computed from a large collection of photos. ThingCV enables perspective-changing design explorations over the network of objects with scalable links. Two exploratory workshops were conducted to investigate how designers navigate and make sense of a network of objects through thingCV. The results of eight participants showed that designers were actively engaged in identifying interesting objects and their associated clusters of related objects. The designers projected social qualities onto the identified objects and their communities. Furthermore, the designers changed their perspectives to revisit familiar contexts and to generate new insights through the exploration process. This work contributes a novel approach to combining data-driven models with designerly interpretations of thing constellation towards More-Than Human-Centred Design of IoT ecosystems.
https://doi.org/10.1145/3479866
The field of Computer-Supported Cooperative Work (CSCW) has long recognized a socio-technical gap complicating the design of technologies that can sustainably meet social needs. In response, a growing body of research advocates for assets-based design, an approach that seeks to build upon what the individuals and community already have. The emphasis on positioning assets rather than needs at the center of the process can complicate designers’ decisions on what activities to foster, how to conduct them, and what outcomes to expect. In this paper, we reflect on two different assets-based design endeavors with vulnerable populations. Our reflections present assets-based design as an ongoing process that prioritizes the formation and evolution of a collective of assets-based thinkers who continually learn about their assets and how to use them to attain desirable change. From that reflection, we contribute three methodological commitments for assets-based design to the growing CSCW scholarship on supporting vulnerable communities to attain emancipatory transformations: (1) embedding trust-building elements throughout the journey;(2) facilitating the formation of an interdependent collective; and (3) making moves towards incremental transformations. Further, we contribute a discussion on the change of perspective that entails for researchers and designers interested in undertaking assets-based design. In particular, we underscore the need to recognize the value of work before the work, to see technology as an intermediary rather than an inevitable end, and embrace impact in the shape of slow incremental transformation.
https://doi.org/10.1145/3479545
Surveys are a common instrument to gauge self-reported opinions from the crowd for scholars in the CSCW community, the social sciences, and many other research areas. Researchers often use surveys to prioritize a subset of given options when there are resource constraints. Over the past century, researchers have developed a wide range of surveying techniques, including one of the most popular instruments, the Likert ordinal scale, to elicit individual preferences. However, the challenge to elicit accurate and rich self-reported responses with surveys in a resource-constrained context still persists today. In this study, we examine Quadratic Voting (QV), a voting mechanism powered by the affordances of a modern computer and straddles ratings and rankings approaches, as an alternative online survey technique. We argue that QV could elicit more accurate self-reported responses compared to the Likert scale when the goal is to understand relative preferences under resource constraints. We conducted two randomized controlled experiments on Amazon Mechanical Turk, one in the context of public opinion polling and the other in a human-computer interaction user study. Based on our Bayesian analysis results, a QV survey with a sufficient amount of voice credits, aligned significantly closer to participants' incentive-compatible behaviors than a Likert scale survey, with a medium to high effect size. In addition, we extended QV's application scenario from typical public policy and education research to a problem setting familiar to the CSCW community: a prototypical HCI user study. Our experiment results, QV survey design, and QV interface serve as a stepping stone for CSCW researchers to further explore this surveying methodology in their studies and encourage decision-makers from other communities to consider QV as a promising alternative.
https://doi.org/10.1145/3449281
Crowdsourcing is being increasingly adopted as a platform to run studies with human subjects. Running a crowdsourcing experiment involves several choices and strategies to successfully port an experimental design into an otherwise uncontrolled research environment, e.g., sampling crowd workers, mapping experimental conditions to micro-tasks, or ensure quality contributions. While several guidelines inform researchers in these choices, guidance of how and what to report from crowdsourcing experiments has been largely overlooked. If under-reported, implementation choices constitute variability sources that can affect the experiment's reproducibility and prevent a fair assessment of research outcomes. In this paper, we examine the current state of reporting of crowdsourcing experiments and offer guidance to address associated reporting issues. We start by identifying sensible implementation choices, relying on existing literature and interviews with experts, to then extensively analyze the reporting of 171 crowdsourcing experiments. Informed by this process, we propose a checklist for reporting crowdsourcing experiments.
https://doi.org/10.1145/3479531