Critical Thinking with Data Visualization (CTDV)

数据分析（Data Analytics， DA）是一个融合了统计学、数据挖掘和计算机科学中的定量方法来发现和总结数据中的信息的领域。在实践中，数据分析的良好应用需要全面的批判性思维技能，这些技能包括：(1)超越定量统计或计算方法的应用；(2)包括定性思维形式，如形式化潜在偏见、沟通个人判断、探索多种解决方案、新旧信息融合以及评估发现的意义。不幸的是，目前的数据分析教学方法主要集中在其定量方面；只有在学生掌握了定量理论和方法之后，他们才有机会对应用进行批判性思考。没有完成当前数据分析课程的学生既不能培养全面的数据分析技能，也不能体验到复杂的定量总结是如何推进知识的。研究人员正试图彻底改变目前在大学一年级和二年级学生中教授数据分析入门课程的做法。具体来说，他们正在开发一门新课程，“批判性思维与数据可视化”（CTDV），该课程将数据分析的教学方法与批判性思维相同步，使数据分析能够为不同的学习者所接受。CTDV包括四个模块，每个模块都是由不同的现实世界案例研究驱动的，并专注于一种数据分析方法（例如，多维缩放）。CTDV使用新颖的交互式数据可视化软件（以及其中的技术）作为一个平台，让学生从他们所知道的知识中构建他们对(1)如何批判性思考，(2)数据在解决问题中的作用，以及(3)总结复杂数据集的一些数学和计算方法的理解。该软件基于贝叶斯可视化分析（baa）方法，该方法由研究人员开发（见NSF奖励号0937071）。BaVA使领域专家——例如：在没有统计学或计算机科学方面的技术培训的情况下，评估复杂的数据集，并将他们的专业知识纳入严格的定量数据表征。因此，BaVA培养了创造性、批判性思维和解决数据问题的能力，是在课堂上体验式学习数据处理概念的理想选择。项目团队正在开发CTDV（包括其目标、课程、教案、案例研究和课程材料），设计交互式数据可视化软件（包括可用性测试），实施CTDV（或其中的模块），评估CTDV的成功。评估包括在学生体验CTDV之前、期间和之后进行的定量（例如，测试）和定性措施（例如，调查和访谈）。此外，该团队还通过综合网站、论文和会议研讨会传播CTDV。

Data Analytics (DA) is a field that merges quantitative methods in statistics, data mining, and computer science to discover and summarize information in data. In practice, a good application of DA requires comprehensive critical thinking skills that (1) extend beyond the application of quantitative statistical or computational methods and (2) include qualitative forms of thought, such as formalizing potential biases, communicating personal judgment, exploring multiple solutions, assimilating new information with old, and assessing implications of discoveries. Unfortunately, current methods in teaching DA focus primarily on its quantitative aspects; only after students master quantitative theory and methods do they have an opportunity to think critically about applications. Students who fail to complete current DA courses neither develop comprehensive DA skills nor experience how complex quantitative summaries may advance knowledge.The investigators are attempting to revolutionize current practice in teaching introductory DA to first- and second-year college students. Specifically, they are developing a new course, "Critical Thinking with Data Visualization" (CTDV), which synchronizes teaching methods in DA with critical thinking and makes DA accessible to diverse learners. CTDV includes four modules, each of which is motivated by a different real-world case study and focuses on one DA method (e.g., multidimensional scaling). CTDV uses novel interactive data visualization software (and techniques therein) as a platform for students to build from what they know and construct their understanding of (1) how to think critically, (2) the role of data in problem solving, and (3) some mathematical and computational methods for summarizing complex datasets. The software is based on methods called Bayesian Visual Analytics (BaVA), which have been developed by the investigators (see NSF Award No. 0937071). BaVA enables domain experts--e.g., biologists or homeland security analysts--to assess complex datasets and incorporate their expert knowledge within quantitatively rigorous data characterizations, without technical training in statistics or computer science. For this reason, BaVA fosters creative, critical thinking and problem solving with data and is ideal for experiential learning of DA concepts in the classroom.The project team is developing CTDV (including its objectives, curriculum, lesson plans, case studies, and course materials), designing the interactive data visualization software (including tests of usability), implementing CTDV (or modules within it), and assessing the success of CTDV. The assessment includes both quantitative (e.g., tests) and qualitative measures (e.g., surveys and interviews) that take place before, during, and after the students experience CTDV. In addition, the team is disseminating CTDV via a comprehensive Web site, papers, and conference workshops.