Human centered design and engineering

Permanent URI for this collectionhttps://digital.lib.washington.edu/handle/1773/19656

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Designing for Entangled Speculation: A Research Through Design Approach for Exploring Wicked Problems
(2026-02-05) Beach, Michael W.; Fox, Tyler
This dissertation explores entanglement as a structuring logic for speculative engagement, aiming to unsettle dominant ontologies and epistemologies to and expand design practice toward the ethical demands of an entangled world. This approach matters because the wicked problems we face in the 21st century, such as climate crisis, social inequity, global health crises, and extractive infrastructures, resist tidy solutions and expose the limits of conventional design frameworks that rely on separability, linear causality, or predictable outcomes. Grasping the magnitude, scale, and complexity of these challenges remains to be understood and will require new methods, approaches, and practices that can hold contradiction, that can embrace the unknown, that can imagine pathways of transformation. Many fields, disciplines, and communities develop their own knowledge practices for creating and maintaining contributions of meaning and understanding of how our world is entangled, from social and ecological entanglements found in HCI, social science, anthropology, animal studies, multispecies justice, critical geographies, law, art, and design, to the scale of entangled particles in quantum physics. By integrating insights of quantum mechanics with design speculation, this research acknowledges the world as it actually is: interconnected, uncertain, and deeply entangled. This dissertation presents Designing for Entangled Speculation (DES), a framework that integrates conceptual resources from quantum entanglement—superposition, observer effect, interconnectedness, and nonlocality & nonlinearity—to expand the theoretical and methodological capacity of design speculation. Using a modified Research through Design (RtD) approach, I conducted three investigations representing varied configurations of abstraction, situatedness, and stakeholder expertise. Post(-)human Hazmat explored speculative narrative as a means of interrogating multispecies relationality. Speculative F/Actors: Climate Futures operationalized collaborative material speculation to model climate-related system interactions. Entangled Justice convened practitioners and researchers with diverse expertise from domains including circular economy, marine energy, and climate migration to generate shared knowledge and ignorance maps through structured collaborative inquiry. A diffractive, cross-case analysis demonstrates how quantum entanglement concepts shape the dynamics of speculative engagement, influence participants’ reasoning about complex systems, and foreground ethical and epistemic considerations within design processes. Together, these contributions position DES as an ethically attuned framework for opening design to more speculative and accountable engagements with the complexities of an entangled world.
Hermeneutic Engineering: Material and Conceptual Tools for Open Systems
(2026-02-05) Benabdallah, Gabrielle; Rosner, Daniela K.; Peek, Nadya
In this dissertation, I argue that technological participation requires the parallel development of open technical systems and of interpretative practices that enable people to materially engage with, question, and reconfigure computational systems. Drawing from literary theory, textual studies, and the history of writing technologies, I present three case studies examining different modes of writing-with-machines. Imprimer, a computational notebook system for CNC milling, demonstrates how digital fabrication becomes interpretative when the system provides the space for engaging with complexity rather than abstracting it away. The Data Epics project transforms domestic IoT data into fiction, revealing how narrative modes of data representation made personal data simultaneously more and less legible. The Automated Writing Exercise inquires into text generation with large language models, exploring how automatic writing and algorithmic continuation create recursive spaces for material and interpretative engagement. Through an analysis and discussion of these three case studies, this dissertation suggests that participation in technical spaces does not come only from increased technical expertise but from interpretative openness, which can be enacted through 1) systems that scaffold complexity rather than hiding it, 2) modes of representation that materialize or visceralize computational artifacts, and 3) approaches that leverage the biases and glitches of systems as entry points into computational spaces. By positioning interpretation as a material practice, and engineering as always containing latent spaces for interpretative work, I propose hermeneutic engineering as an orientation that questions the fixity and opaqueness of computational systems, accessible only to experts. Hermeneutic engineering thus encourages a change of attitude towards computational systems, from fixed and definite entities to sites of ongoing inquiry, reconfiguration, and material exploration.
From Research to UX Practice: Evaluation Approaches and Tools for Realizing Human-Centered AI Goals
(2026-02-05) Muralikumar, Meena Devii; McDonald, David W.
The integration of AI models in various products and services poses unique challenges for design and UX practice. Unlike other technologies, AI poses distinct challenges due to its probabilistic nature, technical complexity, and lack of precedent. While collaboration with AI practitioners can help alleviate these challenges, there are significant communication, process, and knowledge barriers to overcome. In this dissertation, I present formative, design, and evaluative research to better support UX practice of AI and UX-AI collaborations, which in turn can support human-centered design of AI products. First, I conduct a qualitative study to understand key challenges that UX practitioners face in model comprehension and reinforcing a human-centered lens on model evaluation. Based on these findings, I design and test visualization-based methods that enable UX practitioners to infer insights about human-AI alignment. I also examine how practitioner tools are currently designed to support interdisciplinary collaborations, such as UX-AI collaborations, through a design space analysis. Based on these three studies, I derive implications for designing evaluation tools for AI/LLM applications that can better support UX practitioners’ needs and improve HCI/UX and AI collaborations.
Research Software Systems: Exploration and Infrastructure in Observational Cosmology
(2025-10-02) Sutherland-Keller, William; Lee, Charlotte; Ribes, David
In the last 20 years software has become an increasingly problematic object in the sciences. While it has become integral to research in many fields, scientific communities have struggled with problems of reproducibility, reuse, and the validity of findings produced by complex software systems. This has been attributed in part to the unplannable and unpredictable nature of scientific work itself, which makes it difficult to test research software or to define its requirements ahead of time. In this dissertation I draw on ethnographic work with a research group in the field of reionization cosmology in order to develop an understanding of how researchers develop novel software instrumentation in these contexts of uncertainty. I elaborate the notion of exploratory programming as a central process in scientific work that is distinct from software production, and I further develop the concept of the research software system as a system of heterogeneous software processes that is organized to reconcile the need for rigidity and flexibility in research infrastructures. This contribution reconceptualizes how software is used in scientific work as well as the process by which software engineering methods might be integrated into that work, and it provides new conceptual handles with which to support both activities.
Developing Feedback Systems For Live Stream Communities Using Large Language Models
(2025-10-02) Mallari, Keri; Zachry, Mark
Live streaming has become a key mode of community engagement, enabling real-time interaction between creators and audience. Platforms like Twitch have transformed content creation into a participatory, performative practice that blends entertainment, emotional labor, and community building. Despite its cultural and economic significance, little research has examined how streamers interpret and act on audience feedback in ways that support sustained growth, well-being, and meaningful interaction. This dissertation explores how large language models (LLMs) can power intelligent feedback systems that help streamers manage content production and community engagement. Through three studies, it examines feedback from multiple angles: streamers' existing information practices, proactive strategies for soliciting input, and reactive techniques for interpreting audience response post-stream. This research demonstrates how LLMs can synthesize audience input into insights that are actionable, emotionally supportive, and strategically meaningful. The work contributes both deployable systems and design principles for building feedback tools attuned to the demands of live stream communities.
Truth-Seeking as Collaborative Work: Expert-Journalist Infrastructure in High-Stakes News Moments
(2025-08-01) Haughey, Melinda McClure; Starbird, Kate
The modern, networked information environment enables public attention to converge and intensify quickly during high-stakes news moments. Sometimes, this attention is expected, as in elections; other times, it emerges suddenly, sparked by violence, leaks, protests, or when local developments escalate into national stories. In periods of heightened uncertainty, both directly affected individuals and ambient observers strive to make sense of unfolding developments while searching for plausible explanations. In this interpretive scramble, rumors and misleading frames can emerge and solidify within hours or days, sometimes in the absence of timely, credible information. Journalists have long assisted the public in interpreting complex, contested realities in their role as explainers and annotators—a role increasingly vital as people face an overwhelming volume and speed of information. To fulfill this role, journalists must "truth-seek", or make sense of events themselves. Yet, as this dissertation shows, access to experts—an efficient and valuable information source—and the systems supporting that access are patchwork, unevenly distributed, and break down with the demands of real-time reporting. These constraints widen the gap between public demand for information and journalists’ ability to provide timely interpretation to the public, especially for journalists with limited resources and amid industry strain. Drawing on qualitative methods—including ethnography, interviews, and participant observation—I present three studies that examine the sociotechnical and professional dynamics of journalist–expert collaboration during high-stakes news moments in the United States, including two contested presidential elections and other high-attention events such as public health crises, social justice protests, and moments of platform accountability and political violence. \begin{itemize} \item The first study investigates how journalists reporting on digital misinformation, often during or about these events, navigate knowledge gaps under deadline pressure, surfacing tensions around sourcing, tools, and ethics, and revealing a growing desire for more timely access to academic expertise. \item The second study analyzes thirty cases of journalist–researcher collaboration during high-tempo news events surrounding the 2020 U.S. election and certification period, identifying a typology of journalists’ needs and uncovering recurring ethical, logistical, and structural tensions. \item The third study examines a structured many-to-many online helpdesk deployed during the 2024 U.S. presidential election, demonstrating how intentional design of expert support spaces can mitigate previously identified challenges, while also requiring ongoing coordination and care. \end{itemize} Finally, I offer a conceptual contribution by articulating journalist–expert networks as part of the broader public sensemaking process and as a form of infrastructure: critical yet fragmented networks, tools, and routines that become visible in moments of strain—strain that emerges where high-stakes news events intersect with the demands of today’s networked information environment. This reframing offers both a conceptual shift and a normative claim: if journalists serve the the public by providing interpretation at speed, then improving access to expert knowledge during high-stakes news moment deserves attention, support, resourcing, and design—early provocations for which are offered as both a framework and a call to action in the final chapter of this dissertation.
Human-Centered Sound Recognition Tools for Deaf and Hard of Hearing People
(2025-01-23) Goodman, Steven; Findlater, Leah
Sound carries rich information about our surroundings; however, this information can be inaccessible to people who are Deaf, deaf, or hard of hearing (DHH). Automatic sound recognition features are now available on smartphones and other devices, but current implementations offer limited personalization options, hindering their ability to accommodate DHH users' diverse interests and varied contexts of use. In this dissertation, I present a series of iterative studies that explore the design of human-centered sound recognition tools to enable DHH users to tailor sound information to their individual needs. I examine user experiences across different stages of a machine learning workflow for personalization, including: problem framing for contextual sound feedback, capturing and curating personal audio data, and interactive training and evaluation of custom sound recognition models. Together, this work provides a comprehensive, empirical investigation into the challenges and opportunities with developing human-centered sound recognition tools for DHH users. I close with recommendations for interface design and opportunities for future research in this space.
Tools for Digital/Physical Creativity
(2025-01-23) Twigg-Smith, Hannah; Peek, Nadya
Digital fabrication machines extend human creativity by enabling us to precisely manipulate the material world according to complex designs. Digital/physical creativity involves navigating relationships between digital design representations, physical processes, and emergent material behavior. Our interaction with this dynamic system is largely mediated by software tools, leading me to ask: How can software tools support digital/physical creativity? This dissertation presents a series of four projects which I use to answer this question. To ground my work in current practice, I begin by studying an community of artist practitioners on #PlotterTwitter. I find that these artists rely on small, flexible tools that enable them to quickly iterate between digital designs and material outcomes. This insight informs development of three systems with which I contribute demonstrations of different strategies software tools can use to support digital/physical iteration. First, I build Dynamic Toolchains, a live dataflow environment which demonstrates how extensible infrastructure can support end-user construction of feedback loops integrating diverse data representations, machines, and materials. Next, I build two versions of KnitScape, a design and simulation tool for knitting. The first shows how lightweight simulation can support development of intuition about emergent material behavior by enabling rapid exploration of unintuitive digital/physical relationships. The second shows how composable primitive elements enable this intuition to be applied to the creation of more complex designs. Together, these three systems serve as examples of three kinds of digital/physical creativity support: exploration of workflows, materials, and designs. More generally, each of these systems supports an approach to making I identify as swatching, a ubiquitous creative strategy in which small artifacts are made to reason about creative processes. I propose the term "swatchiness" to capture how well software tools facilitate small artifact iteration. I argue that swatchiness is a highly desirable quality in software tools which support digital/physical creativity, and I use insights gained from my empirical and systems work to synthesize and contribute four "Principles of Swatchiness" which developers can use to consider swatchiness in future tools: rapid insight, tinkerability, targeted support, and multimodal exploration. I argue that it is critical to build highly swatchy tools for digital/physical creativity because they will not only help us make more things today, but also help us imagine what we could make tomorrow.
Trans Science: Research, Medicine, and the Politics of Proof
(2025-01-23) Keyes, Os; Ribes, David
With ongoing conflict and debate over the legitimacy of gender-affirming medical treatments, there have been a multitude of calls for science. Specifically, for studies testing the efficacy and consequences of gender-affirming care. Although such studies and the treatments they assess are often portrayed as relatively novel, neither is the case. Both are close to a century old, with a complex and potent history to them that has resonance with current debates. This dissertation sets out and discusses that history–specifically the history of "trans science", by which I mean the way that access to gender-affirming care for transgender people has often been interwoven with, and conditioned on, involvement in scientific studies. Specifically, it looks at the history of studies to establish the consequences of medical interventions. Focusing on the 1960s–1980s, which constituted the heyday of such research in North America, this dissertation looks at the role scientific work played in institutionalising trans healthcare, the consequences that such desires had for patients (and research) given broader cultural anxieties around treatment, and the way that studies were interpreted and taken up inside and outside medicine. Based on over 170 interviews and material from some 30 archival repositories, I argue that the interweaving of medical treatment and scientific research–particularly under conditions of cultural opprobrium–produced difficulties that undermined both patients' aims and the aims of clinical researchers. The interpretation and deployment of these studies in policymaking was shaped by those same cultural pressures to such a degree that the results themselves played a minimal role in decisionmaking. I argue that the debate, at its core, was not over scientific purity or the sufficiency of evidence, but instead over the underlying values that actors hewed to, and whether trans lives could be conceived as good ones to live. These findings have substantial implications for how we evaluate proposals for further study, and how we understand the legitimacy, or responses to, claims of disputed science within the current conflict surrounding gender-affirming care.
Applying Critical Reflection to Reimagine Global Health
(2025-01-23) Dunbar, Elizabeth L; Kolko, Beth
Global health structures are steeped in power asymmetries, where much of the funding, leadership, and evidence-based interventions originate in the global north. Despite increasing calls for adopting reflexivity to critique existing approaches, few interventions exist to help global health practitioners engage in critical reflection. This dissertation leverages scholarship from the fields of Human-Computer Interaction (HCI), Feminist Theory, and Critical Technology Studies to inform the design of an interactive technology called the (re)imaginator that guides global health practitioners in reflective practices. HCI’s emphasis on critical reflection and its extensive research on designing for reflection offers global health important evidence, and it can guide global health in building mechanisms to interrogate the current practices, explore alternatives, and reimagine interventions. This research investigates how critical reflection can be leveraged to reimagine global health by answering three questions. First, it examines how design for reflection literature from Human-Computer Interaction (HCI) can inform the development of an intervention for global health practitioners (RQ1) and then utilizes this evidence to build a prototype reflection tool called (re)imaginator. Second, it explores how practitioners engage with and perceive this tool (RQ2), and, third, gauges the extent to which (re)imaginator provokes global health practitioners to rethink and reimagine their work (RQ3). One key contribution of this dissertation is weaving Feminist Theory, particularly Patricia Hill Collins’ Matrix of Domination framework, into the design of the intervention. These theories ground this tool so that it can be used by a diverse set of global health practitioners—from health project designers to implementers to evaluators to funders—to provoke critiques across this interdisciplinary field. This dissertation demonstrates that critical reflection interventions like (re)imaginator support global health practitioners to think about their work in new ways and commit to take more equitable actions. It also demonstrates that these interventions help participants see that their colleagues question their beliefs, suggesting that reflection interventions can support practitioners in recognizing the shared appetite for changing thinking and practices across their organizations. Insights from this study can also inform the design of future reflection tools to more effectively encourage sustained critical thinking and behavior change. Critical reflection tools offer new pathways for practitioners to unpack their own contributions, recognize ways their work reinforces the field’s inequities, and begin to identify changes to their practice that can help shift the course of global health.
Understanding, Designing, and Theorizing Collective Access Approaches to Captioning-Mediated Communication
(2024-10-16) McDonnell, Emma Jean; Findlater, Leah
For the many people who cannot access audio content, perhaps because they are d/Deaf or hard of hearing, captions are a crucial accessibility tool. While a significant body of work has developed and studied captioning technologies, researchers have traditionally only considered d/Deaf and hard of hearing (DHH) people as captioning users. Yet, communication is inherently interactive, and Deaf and disabled scholars and activists increasingly emphasize that accessibility ought to be a group-level, not individual, concern. Treating DHH people as the sole users of captioning places all of the work of ensuring communication access on the group that faces access barriers. Further, when captioning tools are not designed to also engage conversation partners, a number of avenues to make conversation more accessible cannot be considered. In my dissertation I identify the impact of conversation partners on captioning use and design collective communication access approaches, reimagining how we conceptualize communication access. My dissertation research uses a range of qualitative, theoretical, and design methods to understand the context that shapes caption use and to envision collective access technologies. I begin by outlining a theoretical framework for collective communication access, drawing from disability studies, Deaf studies, disability justice, and communication studies. I then identify factors that shape DHH people's experiences of real-time captioning in small groups and identify the potential for and interest in group captioning tools. Via a codesign study with mixed hearing ability groups, I identify promising practical directions for the design of collective access captioning tools. I then explore the role of contextual factors and collective access in a different form of captioning -- user-generated captions on TikTok. Finally. I review the past decade of captioning literature through a collective communication access lens, identifying that designing for the group, grounded in communication context, is a novel but promising approach to creating captioning technologies. My dissertation makes empirical, theoretical, and design contributions, envisioning and grappling with the complexities of designing communication access technologies anchored in Deaf and disability scholarship and activism. I propose a future of accessibility practice that uses technology to guide nondisabled people toward more accessible norms and builds tools that can better match the ways they are used in practice.
Methods of Designing Justice-oriented Interactive AI Systems
(2024-10-16) Cunningham, Jay L.; Kientz, Julie A; Rosner, Daniela K
The rise of artificial intelligence (AI) technologies has introduced concerns about the perpetuation and exacerbation of existing racial inequities. Although AI promises innovative advances, its design and implementation often reflect and amplify societal biases, disproportionately impacting marginalized groups, particularly Black individuals and groups of people. My dissertation explores this critical issue through examining how racial inequity manifests in two prominent interactive AI systems: banking applications and AI-enabled language tools. Existing research reveals shortcomings in current technology design practices, particularly in fostering accountability and inclusivity for underrepresented minority communities. While human-centered AI methods offer valuable tools, they may fall short in addressing the complex socio-cultural contexts of marginalized user groups. To bridge this gap, my dissertation contributes a provisional Techno-Realist Innovation Framework, a human-centered approach that integrates social justice principles into AI research and design. Through three distinct investigations, I explore the experiences of African American users with interactive AI systems, highlighting their unique challenges, benefits, and cultural assets. This research culminates in a reflective analysis and a methodological proposal for accountable community-based collaboration, emphasizing the importance of diverse community knowledge and participation in shaping technological innovation. By centering the voices and perspectives of marginalized groups, my dissertation seeks to pave the way for more just, equitable, and socially responsible AI systems.
The Measurement and Representation of Influencer Communities in United States Political Discourse on Social Media
(2024-09-09) Beers, Anna; Starbird, Kate; Spiro, Emma S
The United States (U.S.) is in the midst of a paradigm shift in who creates news. It is widely known that the internet has in the past few decades displaced television and print newspapers as the primary medium where news is consumed. However, the past two decades have also seen a shift in who is communicating the news. People consuming digital news, and especially young people, are now less likely than they were to get their news from journalists or television broadcasters, and more likely to receive it from a nebulous figure commonly referred to as the influencer. People are not only paying more attention to influencers, but there has seemingly been a remarkable growth in the type of and number of influencers in the last decade. This growth has been enabled both by the maturation of new, massively-networked social media platforms and the industrialization of influencing as a profession and an economic infrastructure. In this dissertation, I use quantitative and qualitative methods to analyze case studies of U.S. political discourse networks to better understand the structure, tactics, and consequences of our new era of influencer media. After conducting a literature review of previous work on influencers in political communication and media studies, I propose flexible ways to represent both influencers and what I call influencer communities in social media networks. Influencer communities are assemblages of influencers working cooperatively and antagonistically to earn the attention of networked audiences on large social media platforms. Via four case studies of Twitter discourse in the U.S., each of which presents a new method for understanding influencers' behaviors and organization, I seek to understand how to represent and visualize influencer communities; how to analyze the strategies that influencers pursue within these communities; and how to understand the effects these influencer communities have on political discourse in the United States. I conclude this dissertation with a collection of reflections, most of which concern how characteristics of influencer communities, such as their embeddedness in power relations and their relationship to the "mainstream," structure which strategies influencers within them take.
Designing with Polyamory
(2024-09-09) Kinnee, Brian Andrew; Rosner, Daniela K.; Desjardins, Audrey
Design is, and has long been, mononormative. It focuses on couples, dyads, and traditional relationship structures that are often taken for granted as the norm. In this dissertation, I contribute techniques for inquiring about lived experiences of queerness and queer relationships with data from sensorially rich first-person and participatory design perspectives. Using sonic and tactile media to probe about lived experiences of the important but under-studied relationship formation of polyamory, in this dissertation, I ask: how might we design with and within the contexts of polyamory and computing? The project uses a combination of autoethnographic design inquiry and participatory design to investigate personal data and its potential for exploring non-normative relationships and lived experiences of polyamory. Moving from individual to participatory design inquiries, this dissertation presents the development of autospeculation. I define autospeculation as a design research method that uses reflections on personal data to access and analyze lived experiences of technology design. I use autospeculation at both the individual and community registers. Using such practices, I argue for sensorially rich engagements with personal data as catalysts for personally meaningful reflection and speculation. Findings from this dissertation include: 1) autobiographical reflections with one’s own data can serve as a bridge between first-person research and participatory design research, 2) zines and craft-based design kits can successfully introduce participants to ways of engaging their data and of doing autospeculation, and 3) design researchers and practitioners can, as demonstrated by this dissertation, attend to more diverse relationship forms.
Centering Culture in Health: Developing Culturally Safe Technology for Early Childhood Health Promotion, A community-based approach to technology design for child development support
(2024-09-09) DeWitt, Akeiylah; Kientz, Julie A
My dissertation investigates the potential of health technologies to improve child health outcomes while emphasizing diversity and equity. I explore both how mobile health interventions can be beneficial for parents and caregivers, and the potential risks if these technologies are not designed to be equitable and inclusive, drawing on prior work across the design of technologies created for parenting, child development, and early childhood health promotion. I explore the application of cultural safety, an approach to health services delivery, to sensitize technologies to the experiential differences between diverse children and families. My research highlights how current design and research practices often overlook the diverse experiences and contexts of families from diverse cultural backgrounds by surveying existing technologies and connecting with parents. I then demonstrate how we can integrate cultural safety into our practices by developing a heuristic evaluation method and collaborating with local parent communities to create a technology prototype that integrates the cultural safety approach. Overall, my dissertation offers a new lens for improving early childhood health technologies. By practicing cultural safety, we can ensure more equitable health outcomes for marginalized children and families by respecting the diversity of human experiences.
Investigating Information Provenance as a Cue to Look through the Opacity of (Mis)Information
(2024-09-09) Zade, Himanshu; Turns, Jennifer
Everyday users access information through different online media platforms as it propagates through the collective actions of users and algorithms. A diverse and huge audience with easy online access to such socio-technically curated information finds it challenging to make sense of this often evolving and sometimes contrasting information. Though researchers and some users know how to interpret this opacity of information, very few everyday users have the understanding and/or tools needed to look into online platforms’ machinations and witness how and why (mis)information spreads. How can we (re)design online media platforms to allow users to look through the opacity of propagating information — in often limited attention span of user interaction on these platforms — and assess the credibility of that information? This dissertation adopts information provenance — a record of information as it moves across users and platforms due to socio-technical actions — as a construct to ground thinking related to the overarching research question. Provenance facilitates a way to imagine what users could know about information and subsequently assess the credibility of the information. The first study on the Google Search platform suggested the importance of information provenance. Findings suggest that making this provenance salient to users can convey the context behind information search and assist users in identifying how information surfacing through different provenances could vary in credibility. The second study on the Twitter platform utilized a design intervention that offered users a direct window into parts of the provenance of information they were engaging with. Findings suggest that easy access to provenance can assist users in inferring specific judgments useful for credibility assessment. The third study on the TikTok platform revealed how users employ nuanced strategies unique to platform features to afford the socio-technical context of information. Findings suggest that when assessing credibility, users implicitly referenced the concept of provenance even without any direct provocation. My dissertation presents numerous contributions across data, empirical research, artifacts, theory, and methodology based on studies conducted at three distinct research sites. Two of these contributions are particularly noteworthy. Firstly, I introduce a framework that proposes how design features of various platforms can facilitate credibility assessment. This framework considers dimensions such as inauthenticity, unfavorable online associations, contentious behavior, lack of trust, and the potential negative consequences of sharing information. Secondly, my dissertation establishes information provenance as a platform-agnostic cue for signaling information credibility. I discuss the findings in light of modern-day media literacy principles to advocate that information provenance could serve as a platform-agnostic construct valuable for conveying the opacity of information to users, who, in turn, can employ that realization to assess information credibility.
Exploring How the Exercise of Power Contributes to Creating More Inclusive Spaces in Engineering Education
(2024-02-12) Mejia, Kenya Z; Turns, Jennifer
Engineering Education in the United States has been trying to address its problem with underrepresentation of minoritized student groups for decades. In recent years, the engineering community has shifted its focus from solely diversity efforts to Diversity, Equity, and Inclusion (DEI) efforts that focus on structural barriers to representation. The work of this dissertation looks to examine efforts to create more inclusive spaces, starting with exploring the educators' perspective followed by collaborative research methods including both faculty and student perspectives. The aim of these co-design efforts is to explore the space of power as it contributes to exclusion. Through co-design workshops, students and faculty discuss experiences of exclusion, reflect on their privileged and marginalized identities, and finally discuss opportunities to create change. Findings from this work re-iterate that doing work to create inclusive spaces is hard, both for students and faculty. Doing this work has both individual components, such as learning about the history and culture of engineering and reflecting on one’s identities, and also community-centered work as people learn from each other’s experiences, acknowledging that intersectionality creates a multitude of ways one moment in time can be experienced based on the different identities one holds. Using Patricia Hill Collins’ Domains of Power, this work dissects how different moments of inclusion are made up of interpersonal, structural, cultural, and disciplinary domains of power. This dissertation concludes by offering two steps the engineering education community can continue to take as we work to-wards creating inclusive spaces. The first is to accept and appreciate the hard work of doing this work. Hard means it is a slow process. It means one must take time to learn and process the learn-ing. Hard means having to reflect on the learning and how one’s identities privilege us at times and marginalize us at other times, based on the context and who is in the room. But hard also means taking action to “move the needle” forward. Second, one should not do all of it alone. Have conversations with others. Use conversations to process what one is learning. To seek advice. To learn from others’ experiences. And to apologize when one has made a mistake. Engineering has a long history, and with that history comes many entrenched norms that are not always beneficial. But as a discipline, engineering prides itself in solving problems and impacting the world for the better. Let’s move forward focusing on our aspirations to make the world a better place for everyone.
Data Literacies in Informal Settings
(2024-02-12) Cheng, Ruijia; Hill, Benjamin Mako; Turns, Jennifer A
As data becomes an integral part of our daily lives, the general public increasingly needs to actively engage with it to understand everyday lives, support personal goals, and engage with social issues. Formal data science training, however, remains out of reach for most people and does not cater to the diverse needs associated with data. Emerging informal settings, such as online social spaces and community workshops, offer accessible platforms for diverse and meaningful data interactions. However, current research on data literacy does not fully capture the diverse ways the public interacts with data in these informal environments. The dissertation presents four studies exploring the ways people interact with data in informal settings, examining the challenges and needs emerging from these engagements. These findings can guide future research and shape the design of tools to foster data engagement in diverse informal environments. Study A illustrates a mixed method analysis of 400 Scratch forum discussion threads and more than 240,000 user-made projects that involve data, unpacking the benefits and drawbacks of interest-driven participation in a large online community. Study B presents a semi-structured interview study with 14 Kaggle users on their collaborative and communicative practices in working with large datasets, highlighting the needs and challenges in conveying procedures to a varied audience and fostering collaboration among users of different experience levels. Study C contains a theory-driven quantitative analysis of a large collection of Twitter messages that involve discussions about COVID-19 vaccine data, identifying features that differentiate critical engagement with data from conspiracy discourses. Study D presents a constructionist system that scaffolds novices to programmatically analyze and visualize data, as well as the insights from the user study workshops that showcase the diverse range of concepts, perspectives, and practices that the system can support. Together, these studies reveal a pluralism in people's competencies and epistemological pathways concerning data engagement—what I refer to as "data literacies"—that should be accounted for in the design of technologies and research for data literacies. This dissertation contributes rich empirical knowledge on the public's engagement with data in a range of informal settings, various design recommendations for informal environments to support data literacies, a call for acknowledging of the pluralism in data literacies in the design of tools and interventions, and a sociotechnical framework for conceptualizing and designing to support data literacies in informal settings.
Designing for ‘Seeing Across Projects’ Based Learning
(2024-02-12) Shroyer, Kathryn Elizabeth; Turns, Jennifer; Atman, Cynthia
Design thinking is an important skill in engineering practice, but it is difficult to teach and learn. The primary means of teaching design is by engaging students in project-based design experiences. In addition to supporting students in having design experiences, there is a need to help students get more out of the design experience they are already having. This gap presents a design research opportunity for which there are many directions to explore. The variation theory of learning posits that people learn through exposure to certain patterns of variance and invariance across instances of a concept. However, there are few systematic curricular efforts to help students learn by seeing across collections of personal or community design experiences. This work explores the design research problem and opportunity of “how might we design environments that support learning from seeing across individual design experiences?” A three-phase design research approach was used. First, the iterative design of several learning environments and activities over four years was framed as a series of research through design (RtD) inquiries that all addressed the same broad design research question. This resulted in over fifty learning activities (RtD artifacts) named ‘seeing across projects (SAP)’ activities. Second, these artifacts were synthesized using the annotated portfolio methodology. Two Annotated portfolios were created, the first focused on breadth, and the second focused on depth. Variation theory was used as an analytical lens to provide insights on what was made possible to learn in the enacted learning environment annotations. These two portfolios resulted in a model that describes the five key elements of the analyzed SAP activities. This also resulted in the identification of three key properties of SAP activities (content, source, and selection), their values, and some potential implications they have for learning and the feasibility of implementation. Finally, the model resulting from the annotated portfolio was aligned with the key principles of the variation theory of learning to create a framework for designing SAP activities grounded in a learning theory. Overall, the results of this work are the proposal and initial investigation of a new, but complementary, pedagogical direction for engineering design education called ‘seeing across projects’ based learning.
Technology Support for Online Science Communication
(2024-02-12) Williams, Spencer Russell; Hsieh, Gary; Reinecke, Katharina
As researchers, we have an obligation to share our scholarship and act as advocates for scientific knowledge. Participatory platforms like social media have become an important way for researchers to connect with the public, but the shifting affordances, audiences, and roles on these platforms make such public engagement difficult. In my dissertation work, I make three primary contributions. First, I contribute the results of qualitative and quantitative studies to understand how the structure of social media platforms affects the flow of scientific information. Second, empirical knowledge showing that an analytics tool to help researchers understand their audiences better can motivate them to improve the framing of their work, and to make more informed decisions about how (and whether) to use Twitter. Third, methods of communicating large-scale, metascientific information to skeptical audiences online, an issue of pressing concern highlighted by the COVID-19 pandemic. Finally, I discuss future directions for researchers, designers, and policymakers in this space. Ultimately, I show how understanding the dynamics of online platforms can lead to better technology support for various stakeholders in the science communication process.

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