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

INSPIRE：在学校、博物馆和网络媒体环境中利用复杂的视觉数据研究和促进定量和空间推理

• 批准号: 1248052
• 负责人: Leilah Lyons
• 金额: $ 79.92万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2016-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1248052&HistoricalAwards=false
• 关键词: INSPIRE; Studying; Promoting; Quantitative; Spatial

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.

该INSPIRE奖的部分资金来自本科教育司的STEM本科教育转型项目和教育和人力资源部学习研究司的发现研究K12项目；社会与行为科学局行为与认知科学部的地理与空间科学项目；以及计算机与信息科学与工程理事会信息与智能系统司的网络学习计划。这是一项研究计划，旨在促进和研究使用交互式可视化工具来理解复杂地理空间数据的有效策略和思维习惯，并在三种情况下为这些工具生成和测试设计策略：在线数据访问网站、交互式博物馆展览和社会科学教室。所有三个研究站点将利用地理信息系统（GIS）可视化工具，使学习者能够访问地理空间参考的历史美国人口普查数据，以检查跨越空间和时间的人口变化。这些复杂的数据工具越来越多地用于不同学科和日常生活的多个方面。然而，人们对学习者如何与它们互动仍然知之甚少。这三个研究地点将战略性地采用多种协调的研究方法，包括设计实验、机器学习分析、多模态交互分析和基于理论的假设生成。这些实证研究的结果跨三种背景进行协调，将用于设计策略的迭代生成和评估，以促进这些学习环境中学习者对复杂数据的有效推理。这个项目也将建立一个连贯的，跨学科的理解跨学习环境的复杂地理空间数据的表示流畅性。智力优势：本研究项目的优势在于其跨学科性，结合了社会学、计算机科学、学习科学、地理信息系统设计和大规模实施的研究方法、概念和设计专业知识，旨在解决人们如何利用社会科学数据学习的紧迫问题。由于拟议的研究并不完全符合任何单一的学术学科，它是INSPIRE计划目标的理想匹配。这个项目的概念和方法的多样性有助于其潜在的变革性质，作为一个跨学科合作的模式，在改变现状的方法来研究数据可视化和学习环境的设计。作为多个研究社区的活跃成员和教育从业者工作的定期贡献者，合作研究者处于独特的位置，可以有效地将实证研究成果转化为可访问的设计和跨多个社区的专业发展机会。更广泛的影响：由于社会探索者项目和纽约科学博物馆的相关装置目前实现了特殊的传播规模，以及在这三种环境（博物馆、教室和基于网络的学习环境）中进行的基于设计的研究的受众的多样性，拟议的项目有可能产生重大影响。此外，研究的核心是历史美国人口普查数据的档案，这是跨社会科学学科研究实践的核心，以及流行的新闻媒体，也与人们对我们社会的理解高度相关。