Cultivating Visualization Literacy for Children Through Curiosity and Play

Bae, S. Sandra; Vanukuru, Rishi; Yang, Ruhan; Gyory, Peter; Zhou, Ran; Yi–Luen, Ellen; Szafir, Danielle Albers

doi:10.1109/tvcg.2022.3209442

Cited by 18 publications

(7 citation statements)

References 57 publications

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“…Various studies confirm the benefits of using 3D input devices, such as reducing mental effort, compared to the traditional keyboard and mouse setup [11,41,70]. The explanatory case aligns with how physical models have also been used to richly explain abstract concepts (e.g., visualization [7,43], biology [5]) for educational purposes and general science communication [68,75]. The third usage scenario emphasizes our network physicalization's capabilities as a sensor.…”

Section: Usage Scenariosmentioning

confidence: 63%

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Bae

Yang

Gyory

et al. 2021

Interaction Design and Children

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Interaction is critical for data analysis and sensemaking. However, designing interactive physicalizations is challenging as it requires cross-disciplinary knowledge in visualization, fabrication, and electronics. Interactive physicalizations are typically produced in an unstructured manner, resulting in unique solutions for a specific dataset, problem, or interaction that cannot be easily extended or adapted to new scenarios or future physicalizations. To mitigate these challenges, we introduce a computational design pipeline to 3D print network physicalizations with integrated sensing capabilities. Networks are ubiquitous, yet their complex geometry also requires significant engineering considerations to provide intuitive, effective interactions for exploration. Using our pipeline, designers can readily produce network physicalizations supporting selection-the most critical atomic operation for interaction-by touch through capacitive sensing and computational inference. Our computational design pipeline introduces a new design paradigm by concurrently considering the form and interactivity of a physicalization into one cohesive fabrication workflow. We evaluate our approach using (i) computational evaluations, (ii) three usage scenarios focusing on general visualization tasks, and (iii) expert interviews. The design paradigm introduced by our pipeline can lower barriers to physicalization research, creation, and adoption.

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Section: Usage Scenariosmentioning

confidence: 63%

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Bae

Yang

Gyory

et al. 2021

Interaction Design and Children

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“…28,29 Interdisciplinary insights have also been proposed, such as Bae et al's assessment of how curiosity and play in physicalizations improve data visualization literacy in children's education. 30 Moreover, Adar and Lee 13,15 built on previous studies to develop an affective learning objective framework that aligns with Bloom and Krathwohl's affective taxonomy. 31 They conceptualized the visual data communication problem between designers and users as a learning problem in a teacher-student relationship.…”

Section: Human Cognitive Processes and Visual Data Communicationmentioning

confidence: 99%

“…28,29 Interdisciplinary insights have also been proposed, such as Bae et al’s assessment of how curiosity and play in physicalizations improve data visualization literacy in children’s education. 30…”

Section: Related Workmentioning

confidence: 99%

An empirical study of counterfactual visualization to support visual causal inference

Wang,

Borland,

Gotz

2024

Information Visualization

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Counterfactuals – expressing what might have been true under different circumstances – have been widely applied in statistics and machine learning to help understand causal relationships. More recently, counterfactuals have begun to emerge as a technique being applied within visualization research. However, it remains unclear to what extent counterfactuals can aid with visual data communication. In this paper, we primarily focus on assessing the quality of users’ understanding of data when provided with counterfactual visualizations. We propose a preliminary model of causality comprehension by connecting theories from causal inference and visual data communication. Leveraging this model, we conducted an empirical study to explore how counterfactuals can improve users’ understanding of data in static visualizations. Our results indicate that visualizing counterfactuals had a positive impact on participants’ interpretations of causal relations within datasets. These results motivate a discussion of how to more effectively incorporate counterfactuals into data visualizations.

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“…Most statistics classes present data with minimal context; however, data derives meanings from contexts and interpreters (Acker and Bowler, 2018). Research in information visualization has shown the advantages of using students’ experience to enhance visualization understanding (Bae et al , 2022). Work that situates students’ data reasoning within personally meaningful data generally falls into two categories: student-created data and preexisting data of potential interest to students.…”

Section: Introductionmentioning

confidence: 99%

Using network visualizations to engage elementary students in locally relevant data literacy

Zhou,

Steinberg,

Stiso

et al. 2023

ILS

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Purpose This study aims to explore how network visualization provides opportunities for learners to explore data literacy concepts using locally and personally relevant data. Design/methodology/approach The researchers designed six locally relevant network visualization activities to support students’ data reasoning practices toward understanding aggregate patterns in data. Cultural historical activity theory (Engeström, 1999) guides the analysis to identify how network visualization activities mediate students’ emerging understanding of aggregate data sets. Findings Pre/posttest findings indicate that this implementation positively impacted students’ understanding of network visualization concepts, as they were able to identify and interpret key relationships from novel networks. Interaction analysis (Jordan and Henderson, 1995) of video data revealed nuances of how activities mediated students’ improved ability to interpret network data. Some challenges noted in other studies, such as students’ tendency to focus on familiar concepts, are also noted as teachers supported conversations to help students move beyond them. Originality/value To the best of the authors’ knowledge, this is the first study the authors are aware of that supported elementary students in exploring data literacy through network visualization. The authors discuss how network visualizations and locally/personally meaningful data provide opportunities for learning data literacy concepts across the curriculum.

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Cultivating Visualization Literacy for Children Through Curiosity and Play

Cited by 18 publications

References 57 publications

Touching Information with DIY Paper Charts & AR Markers

Touching Information with DIY Paper Charts & AR Markers

An empirical study of counterfactual visualization to support visual causal inference

Using network visualizations to engage elementary students in locally relevant data literacy

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