ActiveInk

Romat, Hugo; Riche, Nathalie Henry; Hinckley, Ken; Lee, Bongshin; Appert, Caroline; Pietriga, Emmanuel; Collins, Christopher

doi:10.1145/3290605.3300272

Cited by 44 publications

(13 citation statements)

References 39 publications

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“…Studies in these fields are typically concerned with evaluating either visualizations (e.g., design decisions) or their underlying processes (e.g., user experience) (Lam et al, 2012). A common finding speaks to how specific features of a tool or visualization may affect or augment resulting interpretations (Larkin & Simon, 1987;Scaife & Rogers, 1996;Grammel, Tory, & Storey, 2010;Romat et al, 2019;Yi, Kang, Stasko, & Jacko, 2007). However, studies that delve into the nuanced practices that educators undertake when making sense of learning data are only beginning to emerge in the HCI and InfoVis fields.…”

Section: Expanding the Notion Of Sensemakingmentioning

confidence: 99%

Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics

Campos

Ahn

DiGiacomo

et al. 2021

JLA

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With the spread of learning analytics (LA) dashboards in K--12 schools, educators are increasingly expected to make sense of data to inform instruction. However, numerous features of school settings, such as specialized vantage points of educators, may lead to different ways of looking at data. This observation motivates the need to carefully observe and account for the ways data sensemaking occurs, and how it may differ across K--12 professional roles. Our mixed-methods study reports on interviews and think-aloud sessions with middle-school mathematics teachers and instructional coaches from four districts in the United States. By exposing educators to an LA dashboard, we map their varied reactions to visual data and reveal prevalent sensemaking patterns. We find that emotional, analytical, and intentional responses inform educators’ sensemaking and that different roles at the school afford unique vantage points toward data. Based on these findings, we offer a typology for representing sensemaking in a K--12 school context and reflect on how to expand visual LA process models.

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Section: Expanding the Notion Of Sensemakingmentioning

confidence: 99%

Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics

Campos

Ahn

DiGiacomo

et al. 2021

JLA

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“…For the interaction itself, interactive surfaces such as tablets or digital whiteboards are interesting environments for editing. Specifically, the additional input modalities of these environments, e.g., touch [33,64], pen [20,63], or speech [70], can potentially simplify edit operations and improve precision at lower LoDs. For example, in order to update an attribute value, the new value could simply be spoken, written with a pen, or indicated by "slicing" a bar at a certain height via touch.…”

Section: Facets Of Responsivenessmentioning

confidence: 99%

Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs

Horak

Berger

Schumann

et al. 2021

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. Responsive matrix cells are a focus+context approach that provides details for a multivariate graph via embedded visualizations in a matrix representation and allows analysts to go from the overview in the matrix to details as well as editing within the cells. c b Abstract-Matrix visualizations are a useful tool to provide a general overview of a graph's structure. For multivariate graphs, a remaining challenge is to cope with the attributes that are associated with nodes and edges. Addressing this challenge, we propose responsive matrix cells as a focus+context approach for embedding additional interactive views into a matrix. Responsive matrix cells are local zoomable regions of interest that provide auxiliary data exploration and editing facilities for multivariate graphs. They behave responsively by adapting their visual contents to the cell location, the available display space, and the user task. Responsive matrix cells enable users to reveal details about the graph, compare node and edge attributes, and edit data values directly in a matrix without resorting to external views or tools. We report the general design considerations for responsive matrix cells covering the visual and interactive means necessary to support a seamless data exploration and editing. Responsive matrix cells have been implemented in a web-based prototype based on which we demonstrate the utility of our approach. We describe a walk-through for the use case of analyzing a graph of soccer players and report on insights from a preliminary user feedback session.

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“…For example, digital twins have the potential to visualise data associated with a design in a spatially bound manner [14,51], which is particularly suited for the visually oriented practices of many designers. Meanwhile sense-making around visualised data can be supported by annotation [40,59] and collaborative data exploration [31].…”

Section: Developing Data-driven Practicesmentioning

confidence: 99%

Exploring The Future of Data-Driven Product Design

Gorkovenko

Burnett

Thorp

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Connected devices present new opportunities to advance design through data collection in the wild, similar to the way digital services evolve through analytics. However, it is still unclear how live data transmitted by connected devices informs the design of these products, going beyond performance optimisation to support creative practices. Design can be enriched by data captured by connected devices, from usage logs to environmental sensors, and data about the devices and people around them. Through a series of workshops, this paper contributes industry and academia perspectives on the future of data-driven product design. We highlight HCI challenges, issues and implications, including sensemaking and the generation of design insight. We further challenge current notions of data-driven design and envision ways in which future HCI research can develop ways to work with data in the design process in a connected, rich, human manner.

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ActiveInk

Cited by 44 publications

References 39 publications

Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics

Making Sense of Sensemaking: Understanding How K–12 Teachers and Coaches React to Visual Analytics

Responsive Matrix Cells: A Focus+Context Approach for Exploring and Editing Multivariate Graphs

Exploring The Future of Data-Driven Product Design

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