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

随着民意调查和其他调查在许多背景和学科领域中成为普遍存在的工具，对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子集的受访者的响应模式。该项目开发的系统将极大地扩大在依赖调查问卷数据收集的若干领域访问调查数据和在线数据共享和探索的机会。注释响应模式并与他人共享注释的能力为调查分析带来了宝贵的新质量，使其成为协作和交互式在线体验。预期在教育和学习方面会有重大的好处。许多社会科学专业的学生报告说，研究方法的在线学习经常受到对定量方法根深蒂固的恐惧的阻碍。将推理结果与社交数据集的易于使用的可视化交互式探索联系起来的能力将帮助学生测试分布假设，为图形选择的受访者群体计算模型，并找到和解释离群值。这种功能组合有可能改变在线共享和分析调查数据的方式，并通过促进现有数据的重用来增加社会学和相关研究的研究投资价值。本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，共享和发布民意和其他问卷调查。在线工具提供了一个新的视觉隐喻，用于分析调查和直观地揭示关系模式，使调查数据易于共享，吸引人探索，并且易于从任何受访者子集导航到单个案例。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颖的调查创作和在线发布系统中，该系统允许用户将交互式探索与常见的推理统计并置，并共享和注释分析结果。该系统被评估为研究生和本科生的几个研究方法类的学习工具。此外，在项目和咨询小组成员进行的一些调查中对该系统进行了实地测试。调查分析系统的一个关键的新功能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社会调查分析师和学生之间基于标准的数据共享，协作和通信。该项目包括为一个以网络学习为重点的调查分析系统开发架构和信息模型;在一个易于使用的可视化分析界面中整合推理统计和探索方法;探索调查数据共享、协作在线分析和注释。

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.