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INSPIRE: Studying and Promoting Quantitative and Spatial Reasoning with Complex Visual Data Across School, Museum, and Web-Media Contexts: 1248052

Principal Investigator: Leilah Lyons
CoPrincipal Investigator(s): Joshua Radinsky, Andrew Beveridge
Organization: University of Illinois at Chicago

Abstract:
This INSPIRE award is partially funded by the Transforming Undergraduate Education in STEM Program in the Division of Undergraduate Education and the Discovery Research K12 Program in the Division of Research on Learning in the Directorate for Education and Human Resources; the Geography and Spatial Sciences Program in the Division of Behavioral and Cognitive Sciences in the Directorate for Social and Behavioral Sciences; and the Cyberlearning program in the Division of Information and Intelligent Systems in the Directorate for Computer & Information Science & Engineering.

This is a research program to promote and study effective strategies and habits of mind for understanding complex geospatial data using interactive visualization tools, and to generate and test design strategies for such tools in three contexts: an online data access website, interactive museum exhibit, and social science classrooms. All three research sites will utilize geographic information system (GIS) visualization tools to give learners access to geospatially-referenced historical U. S. Census data for examining changing populations across space and time. These complex data tools are increasingly used in different disciplines and in multiple aspects of everyday life. However, how learners interact with them is still poorly understood. The three research sites will strategically employ multiple, coordinated research methods, including design-experimentation, machine-learning analyses, multimodal interaction analyses, and grounded-theory generation of hypotheses. The outcomes of these empirical studies, coordinated across three contexts, will be used for iterative generation and evaluation of design strategies to promote effective reasoning with complex data for learners in each of these learning environments. This project also will build a coherent, interdisciplinary understanding of representational fluency for complex geospatial data across learning contexts.

Intellectual Merit: The merit of this research program derives from its fundamental interdisciplinarity, combining research methods, concepts, and design expertise from Sociology, Computer Science, the Learning Sciences, and GIS design and large-scale implementation, in the service of addressing pressing questions about how people learn with social-scientific data. Because the proposed research does not fit neatly within any single academic discipline, it is an ideal match for the goals of the INSPIRE program. The conceptual and methodological diversity of this project contributes to its potentially transformative nature, as a model for cross-discipline collaboration in transforming status-quo approaches to studying data visualization and the design of learning environments. The collaborating investigators, as active members of multiple research communities and regular contributors to the work of educational practitioners, are uniquely situated to effectively translate empirical research findings into accessible designs and professional development opportunities across multiple communities.

Broader Impacts: The proposed project has the potential to have substantial impact due to the exceptional scale of dissemination currently realized by the Social Explorer project and related installations at the New York Science Museum, as well as the diversity of audiences for design-based research conducted in these three contexts (museum, classroom and web-based learning environments). In addition, the core of the research is the archive of historical U. S. Census data, which is central to research practices across social science disciplines, as well as popular news media, and is also highly relevant to people’s understandings of our society.

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