About

Paul C Parsons, PhD, is an Associate Professor in the Department of Computer Graphics Technology at Purdue University. He received his Bachelor degree in computing and cognitive science from Queen's University in Kingston, Ontario, and earned his Ph.D. in Computer Science from the University of Western Ontario in 2013, specializing in human-centered design, interactive visual interfaces, and cognitive technologies. His research focuses on the human-centered design of interactive technology, with particular attention to human cognition, visualization interfaces, and interaction design. Parsons has professional experience as a Research Scientist with IBM Canada and has held a Postdoctoral Fellowship at Western University, working in visual analytics and human-centered design. His academic and research interests include cognitive systems, human-computer interaction, design practice, data visualization, and cognition.

Research topics

• Computer Science
• Artificial Intelligence
• World Wide Web
• Multimedia
• Human–computer interaction

Selected publications

• Slide.Bingo: From Passive Attendance to Active Listening Through AI-Generated Bingo

  2026-04-13

  articleOpen access

  Conference attendance is predominantly passive: audiences sit, listen, and hope to absorb information. Yet, active learning research demonstrates that participation outperforms passive reception. We present Slide.Bingo, an interactive system that uses generative AI to transform presentation content into personalised bingo cards, aiming to give each attendee a task to perform and specific targets to attend to during sessions. The bingo format provides sustained engagement, directed attention, and social presence through real-time awareness of other players. Designed for conference-scale deployment, the system supports two card policies: an Individual Card Policy for paper/panel sessions and a Shared Card Policy for demo/poster sessions. Presenters can customize their content and add custom statements for key takeaways. At CHI 2026, attendees can use Slide.Bingo as their conference schedule app, experiencing Slide.Bingo across the programme. Visitors to our interactivity booth will be able to interact with a demo presentation or customize Slide.Bingo content for their own papers.

  PublisherDOI

• Visualization Was Here: Reorienting Research When Visualizations Fade into the Background

  ArXiv.org · 2025-09-30

  preprintOpen access1st authorCorresponding

  Visualization research often centers on how visual representations generate insight, guide interpretation, or support decision-making. But in many real-world domains, visualizations do not stand out--they recede into the background, stabilized and trusted as part of the everyday infrastructure of work. This paper explores what it means to take such quiet roles seriously. Drawing on theoretical traditions from joint cognitive systems, naturalistic decision making, and infrastructure studies, I examine how visualization can become embedded in the rhythms of expert practice--less a site of intervention than a scaffold for attention, coordination, and judgment. I illustrate this reorientation with examples from mission control operations at NASA, where visualizations are deeply integrated but rarely interrogated. Rather than treat invisibility as a failure of design or innovation, I argue that visualization's infrastructural presence demands new concepts, methods, and critical sensibilities. The goal is not to diminish visualization's importance, but to broaden the field's theoretical repertoire--to recognize and support visualization-in-use even when it fades from view.

  PublisherOA PDFDOI

• Judgment as Coordination: A Joint Systems View of Visualization Design Practice

  ArXiv.org · 2025-07-01

  preprintOpen access1st authorCorresponding

  Professional visualization design has become an increasingly important area of inquiry, yet much of the field's discourse remains anchored in researcher-centered contexts. Studies of design practice often focus on individual designers' decisions and reflections, offering limited insight into the collaborative and systemic dimensions of professional work. In this paper, we propose a systems-level reframing of design judgment grounded in the coordination and adaptation that sustain progress amid uncertainty, constraint, and misalignment. Drawing on sustained engagement across multiple empirical studies--including ethnographic observation of design teams and qualitative studies of individual practitioners--we identify recurring episodes in which coherence was preserved not by selecting an optimal option, but by repairing alignment, adjusting plans, and reframing goals. We interpret these dynamics through the lens of Joint Cognitive Systems, which provide tools for analyzing how judgment emerges as a distributed capacity within sociotechnical activity. This perspective surfaces often-invisible work in visualization design and offers researchers a new conceptual vocabulary for studying how design activity is sustained in practice.

  PublisherOA PDFDOI

• Beyond Problem Solving: Framing and Problem-Solution Co-Evolution in Data Visualization Design

  ArXiv.org · 2025-08-09 · 1 citations

  preprintOpen access1st authorCorresponding

  Visualization design is often described as the process of solving a well-defined problem by navigating a design space. While existing visualization design models have provided valuable structure and guidance, they tend to foreground technical problem-solving and underemphasize the interpretive, judgment-based aspects of design. In contrast, research in other design disciplines has emphasized the importance of framing--how designers define and redefine what the problem is--and the co-evolution of problem and solution spaces through reflective practice. These dimensions remain underexplored in visualization research, particularly from the perspective of expert practitioners. This paper investigates how visualization designers frame problems and navigate the dynamic interplay between problem understanding and solution development. We conducted a mixed-methods study with 11 expert practitioners using design challenges, diary entries, and semi-structured interviews. Through reflexive thematic analysis, we identified key strategies that participants used to frame problems, reframe them in response to evolving constraints or insights, and build bridges between problem and solution spaces. These included using metaphors, heuristics, sketching, primary generators, and reflective evaluation of failed or incomplete ideas. Our findings contribute an empirically grounded account of visualization design as a reflective, co-evolutionary practice, where framing is not a preliminary step but a continuous activity embedded in design. Participants often reshaped their understanding of the problem based on solution attempts, tool feedback, and ethical or narrative concerns. These insights extend current visualization design models and highlight the need for frameworks that better account for framing and interpretive judgment. (See paper for full abstract.)

  PublisherOA PDFDOI

• How Visualization Designers Perceive and Use Inspiration

  2025-04-24 · 4 citations

  articleOpen accessSenior author

  Inspiration plays an important role in design, yet its specific impact on data visualization design practice remains underexplored. This study investigates how professional visualization designers perceive and use inspiration in their practice. Through semi-structured interviews, we examine their sources of inspiration, the value they place on them, and how they navigate the balance between inspiration and imitation. Our findings reveal that designers draw from a diverse array of sources, including existing visualizations, real-world phenomena, and personal experiences. Participants describe a mix of active and passive inspiration practices, often iterating on sources to create original designs. This research offers insights into the role of inspiration in visualization practice, the need to expand visualization design theory, and the implications for the development of visualization tools that support inspiration and for training future visualization designers.

  PublisherDOI

• Coping with Uncertainty in UX Design Practice: Practitioner Strategies and Judgment

  2025-06-22 · 5 citations

  articleOpen accessSenior author

  The complexity of UX design practice extends beyond ill-structured design problems to include uncertainties shaped by shifting stakeholder priorities, team dynamics, limited resources, and implementation constraints.While prior research in related fields has addressed uncertainty in design more broadly, the specific character of uncertainty in UX practice remains underexplored.This study examines how UX practitioners experience and respond to uncertainty in real-world projects, drawing on a multi-week diary study and follow-up interviews with ten designers.We identify a range of practitioner strategies-including adaptive framing, negotiation, and judgment-that allow designers to move forward amid ambiguity.Our findings highlight the central role of design judgment in navigating uncertainty, including emergent forms such as temporal and sacrificial judgment, and extend prior understandings by showing how UX practitioners engage uncertainty as a persistent, situated feature of practice.

  PublisherOA PDFDOI

• Judgment as Coordination: A Joint Systems View of Visualization Design Practice

  2025-11-01 · 1 citations

  article1st authorCorresponding

  Professional visualization design has become an increasingly important area of inquiry, yet much of the field’s discourse remains anchored in researcher-centered contexts. Studies of design practice often focus on individual designers’ decisions and reflections, offering limited insight into the collaborative and systemic dimensions of professional work. In this paper, we propose a systems-level reframing of design judgment grounded in the coordination and adaptation that sustain progress amid uncertainty, constraint, and misalignment. Drawing on sustained engagement across multiple empirical studies—including ethnographic observation of design teams and qualitative studies of individual practitioners—we identify recurring episodes in which coherence was preserved not by selecting an optimal option, but by repairing alignment, adjusting plans, and reframing goals. We interpret these dynamics through the lens of Joint Cognitive Systems, which provide tools for analyzing how judgment emerges as a distributed capacity within sociotechnical activity. This perspective surfaces often-invisible work in visualization design and offers researchers a new conceptual vocabulary for studying how design activity is sustained in practice.

  PublisherDOI

• Identifying Framing Practices in Visualization Design Through Practitioner Reflections

  ArXiv.org · 2025-08-28

  preprintOpen accessSenior author

  Framing -- how designers define and reinterpret problems, shape narratives, and guide audience understanding -- is central to design practice. Yet in visualization research, framing has been examined mostly through its rhetorical and perceptual effects on audiences, leaving its role in the design process underexplored. This study addresses that gap by analyzing publicly available podcasts and book chapters in which over 80 professional visualization designers reflect on their work. We find that framing is a pervasive, iterative activity, evident in scoping problems, interpreting data, aligning with stakeholder goals, and shaping narrative direction. Our analysis identifies the conditions that trigger reframing and the strategies practitioners use to navigate uncertainty and guide design. These findings position framing as a core dimension of visualization practice and underscore the need for research and education to support the interpretive and strategic judgment that practitioners exercise throughout the design process.

  PublisherOA PDFDOI

• Rethinking Citation of AI Sources in Student-AI Collaboration within HCI Design Education

  2025-07-14 · 2 citations

  preprintOpen accessSenior author

  The growing integration of AI tools in student design projects presents an unresolved challenge in HCI education: how should AI-generated content be cited and documented? Traditional citation frameworks -- grounded in credibility, retrievability, and authorship -- struggle to accommodate the dynamic and ephemeral nature of AI outputs. In this paper, we examine how undergraduate students in a UX design course approached AI usage and citation when given the freedom to integrate generative tools into their design process. Through qualitative analysis of 35 team projects and reflections from 175 students, we identify varied citation practices ranging from formal attribution to indirect or absent acknowledgment. These inconsistencies reveal gaps in existing frameworks and raise questions about authorship, assessment, and pedagogical transparency. We argue for rethinking AI citation as a reflective and pedagogical practice; one that supports metacognitive engagement by prompting students to critically evaluate how and why they used AI throughout the design process. We propose alternative strategies -- such as AI contribution statements and process-aware citation models that better align with the iterative and reflective nature of design education. This work invites educators to reconsider how citation practices can support meaningful student--AI collaboration.

  PublisherDOI

• Beyond Problem Solving: Framing and Problem-Solution Co-Evolution in Data Visualization Design

  IEEE Transactions on Visualization and Computer Graphics · 2025-11-21 · 3 citations

  article1st authorCorresponding

  Visualization design is often described as a process of solving a well-defined problem by navigating a design space. While existing visualization design models have provided valuable structure and guidance, they tend to foreground technical problem-solving and underemphasize the interpretive, judgment-based aspects of design. In contrast, research in other design disciplines has emphasized the importance of framing-how designers define and redefine what the problem is-and the co-evolution of problem and solution spaces through reflective practice. These dimensions remain underexplored in visualization research, particularly from the perspective of expert practitioners. This paper investigates how visualization designers frame problems and navigate the interplay between problem understanding and solution development. We conducted a mixed-methods study with 11 expert design practitioners using design challenges, diary entries, and semi-structured interviews. Through reflexive thematic analysis, we identified key strategies that participants used to frame design problems, reframe them in response to evolving constraints or insights, and construct bridges between problem and solution spaces. These included the use of metaphors, heuristics, sketching, primary generators, and reflective evaluation of failed or incomplete ideas. Our findings contribute an empirically grounded account of visualization design as a reflective, co-evolutionary practice. We show that framing is not a preliminary step, but a continuous activity embedded in the act of designing. Participants frequently shifted their understanding of the problem based on solution attempts, feedback from tools, and ethical or narrative concerns. These insights extend current visualization design models and highlight the need for frameworks that better account for framing and interpretive judgment. We conclude with implications for visualization research, education, and practice. In particular, we discuss how design education can better support framing and co-evolutionary thinking, and how visualization research can benefit from greater attention to the cognitive strategies and reflective processes that underpin expert design.

  PublisherDOI

Recent grants

• CRII: CHS: Understanding cognitive potentials of interactive visualizations

  NSF · $195k · 2018–2021

Frequent coauthors

• Zhutian Chen

  Twin Cities Orthopedics

  36 shared

• Nils Gehlenborg

  Harvard University

  36 shared

• Christina Stoiber

  36 shared

• Simon Warchol

  36 shared

• Johanna Beyer

  36 shared

• Chenyang Zhang

  Tibet University

  36 shared

• Jonathan P. Leidig

  Grand Valley State University

  36 shared

• Kamran Sedig

  Western University

  35 shared

Education

• Ph.D., Computer Science

  Western University

  2013

• B. Computing Specialization Cognitive Science, Computing

  Queen's University

  2007

Awards & honors

• Polytechnic research awards - May 2025
• Polytechnic research awards - December 2024
• Full list of Teaching Excellence award winners among Polytec…
• Polytechnic research awards - June 2024