EAGER: Development of a Novel Online Visual Survey Data Analysis Tool and Assessment of its Capabilities to Enhance Learning of Quantitative Research Methods

随着民意和其他调查成为许多背景和学科领域中无处不在的工具，非专业人员可以使用的在线调查分析系统的需求也在增加，以快速准确地分析不同类别受访者的答复模式。该项目开发的系统将在依赖问卷数据收集的几个领域极大地扩大调查数据获取和在线数据共享和探索的机会。注释回复模式并与其他人共享注释的能力为调查分析带来了宝贵的新质量，使其成为一种协作和互动的在线体验。预计在教育和学习方面会有重要的好处。许多社会科学专业的学生报告说，由于对量化方法的根深蒂固的恐惧，在线学习研究方法经常受到阻碍。将推断结果与易于使用的社交数据集的可视化交互探索相关联的能力将帮助学生测试分布假设，计算以图形方式选择的受访者群体的模型，并发现和解释离群值。这种功能的组合有可能改变在线共享和分析调查数据的方式，并通过促进可用数据的重复使用来增加社会学和相关研究的研究投资价值。这个项目的目标是建立一个探索性调查数据分析的在线工具，研究人员和学生可以使用它来检查、分析、共享和发布民意调查和其他问卷调查。这一在线工具为分析调查和直观地揭示关系模式提供了一种新的视觉隐喻，使调查数据易于共享、易于探索，并且易于从受访者的任何子集导航到个别案例。该项目利用图像分析、分面搜索和在线地图导航的技术方法，将它们结合到一个新的调查创作和在线发布系统中，该系统允许用户将互动探索与常见推理统计并列，并分享和注释分析结果。该系统在研究生和本科生的几个研究方法课程中作为学习工具进行了评估。此外，在该项目和咨询小组成员进行的若干调查中对其进行了实地测试。调查分析系统的一个重要新特点是其高效和直观的探索性数据分析界面，可供广泛的专家和非专家用户访问。另一个关键的新功能是它支持基于标准的数据共享、协作和社会调查分析师和学生之间的交流。该项目包括为侧重网络学习的调查分析系统开发体系结构和信息模型；将推论统计和探索性方法整合到一个易于使用的可视化分析界面中；探索调查数据共享、协作性在线分析和注释。

As public opinion and other surveys become a ubiquitous tool in many contexts and disciplinary domains, the need for online survey analysis systems that can be used by non-professionals to quickly and accurately analyze patterns of responses in different subsets of respondents is also increasing. The system developed by the project will vastly expand opportunities for survey data access and online data sharing and exploration in several domains that rely on questionnaire data collection. The ability to annotate patterns of responses and share the annotations with others leads to a valuable new quality in survey analysis, making it a collaborative and interactive online experience. Important benefits are expected in education and learning. Online learning of research methods is often hampered by a deep-seated fear of quantitative approaches reported by many social science majors. The ability to relate inferential results with easy to use visual interactive exploration of social datasets will help students test distributional assumptions, compute models for graphically selected groups of respondents, and find and explain outliers. This combination of features has the potential to transform how survey data are shared and analyzed online, and increase the value of research investment in sociological and related studies by promoting reuse of available data. This project's goal is to build an online tool for exploratory survey data analysis, which can be used by researchers and students to examine, analyze, share, and publish public opinion and other questionnaire surveys. The online tool offers a new visual metaphor for analyzing surveys and intuitively uncovering patterns of relationships, making survey data easy to share, appealing to explore, and simple to navigate from any subsets of respondents to individual cases. The project leverages technical approaches from image analytics, faceted search, and online map navigation, combining them into a novel survey authoring and online publication system which allows users to juxtapose interactive exploration with common inferential statistics, and share and annotate analytical results. The system is evaluated as a learning tool in several research method classes for both graduate and undergraduate students. In addition, it is field tested in a number of surveys conducted by the project and the advisory team members. A key novel feature of the survey analysis system is its efficient and intuitive exploratory data analysis interface accessible by a wide group of expert and non-expert users. Another key novel feature is its support of standards-based data sharing, collaboration, and communication among social survey analysts and students. The project includes development of architecture and information models for a cyberlearning-focused survey analysis system; integration of inferential statistics and exploratory approaches in a single easy to use visual analytical interface; and exploration of survey data sharing, collaborative online analysis and annotations.