An Autoethnography on Visualization Literacy: A Wicked Measurement Problem
Lily W. Ge, Anne-Flore Cabouat, Karen Bonilla, Yuan Cui, Yiren Ding, Noëlle Rakotondravony, Mackenzie Michael Creamer, Jasmine Tan Otto, Maryam Hedayati, Bum Chul Kwon, Angela Locoro, Lane Harrison
摘要
We contribute an autoethnographic reflection on the complexity of defining and measuring visualization literacy (i.e., the ability to interpret and construct visualizations) to expose our tacit thoughts that often exist in-between polished works and remain unreported in individual research papers. Our work is inspired by the growing number of empirical studies in visualization research that rely on visualization literacy as a basis for developing effective data representations or educational interventions. Researchers have already made various efforts to assess this construct, yet it is often hard to pinpoint either what we want to measure or what we are effectively measuring. In this autoethnography, we gather insights from 14 internal interviews with researchers who are users or designers of visualization literacy tests. We aim to identify what makes visualization literacy assessment a "wicked" problem. We further reflect on the fluidity of visualization literacy and discuss how this property may lead to misalignment between what the construct is and how measurements of it are used or designed. We also examine potential threats to measurement validity from conceptual, operational, and methodological perspectives. Based on our experiences and reflections, we propose several calls to action aimed at tackling the wicked problem of visualization literacy measurement, such as by broadening test scopes and modalities, improving test ecological validity, making it easier to use tests, seeking interdisciplinary collaboration, and drawing from continued dialogue on visualization literacy to expect and be more comfortable with its fluidity.
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它引用的顶会 Paper10
- CALVI: Critical Thinking Assessment for Literacy in VisualizationsLily W. Ge, Yuan Cui, Matthew KayCHI 2023 · 被引用 68 次
- Designing Narrative-Focused Role-Playing Games for Visualization Literacy in Young ChildrenElaine Huynh, Angela Nyhout, Patricia Ganea, Fanny ChevalierIEEE VIS 2020 · 被引用 58 次
- Challenges and Opportunities in Data Visualization Education: A Call to ActionBenjamin Bach, Mandy Keck, Fateme Rajabiyazdi, Tatiana Losev 等IEEE VIS 2023 · 被引用 58 次
- Troubling Collaboration: Matters of Care for Visualization Design StudyDerya Akbaba, Devin Lange, Michael Correll, Alexander Lex 等CHI 2023 · 被引用 41 次
- BeauVis: A Validated Scale for Measuring the Aesthetic Pleasure of Visual RepresentationsTingying He, Petra Isenberg, Raimund Dachselt, Tobias IsenbergIEEE VIS 2022 · 被引用 32 次
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