Student Engagement in Statistics Using Technology: Making Data Based Decisions

在改善本科生统计和数据科学教育方面，国家在两个重要方面持续存在需求。美国居民需要对这些领域有更深入的了解，以便在一个日益多样化和复杂的社会中作出明智的决定。同样，国家有根本需要培养科学、技术、工程和数学(STEM)领域的大学毕业生，他们能够应用统计和数据科学，帮助国家提供具有全球竞争力的STEM劳动力。该项目的调查人员将通过设计、开发和评估基于查询的在线技术来满足这些需求，该技术将模拟统计和数据科学中当前的真实世界情景，使学生认识到解决问题和基于数据的决策的调查过程的重要性以及这些活动所需的技能。在这方面，该项目将利用现在很容易获得的大量公开可用的数据集，让学生获得类似研究的经验和技术互动的教育材料，以培养学生理解和应用统计和数据科学的能力。除了为学生提供的材料外，还将专门设计资源，帮助教师融入传统教科书中通常没有教授的关键思想，如交互式可视化、处理杂乱的数据、偏差、数据相关性、可靠性，以及涉及真实世界数据的全面研究体验。该项目的一个主要目标是通过创建、实施和测试基于探究的、互动的在线调查实验室来促进STEM学习，这些实验室将模拟基于数据的决策。该项目的目标包括：(1)将学生的研究体验融入到他们的学习中；(2)解决数据科学日益重要的问题，并挑战当前课程和教科书中不易涉及的统计概念；(3)使用类似游戏的模拟开发真实世界场景的完整故事情节模型；以及(4)创建和审查可纳入各种传统入门和高级本科课程的材料。项目团队的行动理论建立在根据这些目标开发、实施和评估每个模拟实验室和项目的其他组件的基础上。一个重要的动机是让学生开发他们自己的研究问题，生成并使用他们自己独特的数据来做出决策，然后观察和学习通过他们与技术的互动所做的选择。为了评估所采取方法的成功，该项目将采用混合方法方法，比较从更传统材料获得的学习收益与使用这些新材料获得的收益，评估学生的态度和参与度，使用数据分析来评估每个实验室中嵌入的组成部分的有效性，并确定将资源纳入各种传统入门和高级本科课程的最佳实践。这些完全身临其境的在线游戏类实验室将与其他当前的教科书和在线教育材料显著不同，因为每个实验室都将包括基于探究的案例研究，其中包含真实世界的数据分析复杂性，从而提供对统计学和数据科学的知识内容和广泛适用性的坚实介绍。随着软件实验室的开发，该团队将创建和审查一个新的学生评估工具，该工具将被实施，以评估学生在理解概念联系、沟通技能、批判性思维和解决问题方面的能力，以及他们理解和处理来自现实世界的非结构化数据集的挑战的能力。总体而言，该项目将通过激发STEM研究和应用中发生的创新、创造力和兴奋的力量，对STEM教育产生重大影响。

There are ongoing national needs on two important fronts for improvements in undergraduate statistics and data science education. There is a need for United States residents to establish a deeper understanding of these arenas in order to make informed decisions in an increasingly diverse and complex society. Likewise, there is a fundamental need for the country to produce college graduates in science, technology, engineering, and mathematics (STEM) areas who can apply statistics and data science to help provide the Nation with a globally competitive STEM workforce. The investigators on this project will address these needs by designing, developing and evaluating inquiry-based online technology that will simulate current real-world scenarios in statistics and data science to connect students to the importance of the investigative process of problem-solving and data-based decision making and to the skills needed for these activities. In connection with this, the project will take advantage of large, publically available datasets which are now easily accessible to engage students with research-like experiences and technologically interactive educational materials to foster students' abilities in understanding and applying statistics and data science. In addition to materials for students, resources to be developed will be specifically designed to help instructors incorporate key ideas typically not taught in traditional textbooks, such as interactive visualizations, working with messy data, bias, data relevance, reliability, and full research-like experiences involving real-world data. A key aim of the project is to advance STEM learning through the creation, implementation, and testing of inquiry-based, interactive, online investigative labs that will simulate data-based decision making. Goals of the project include: (1) incorporating research-like experiences for students into their studies; (2) addressing the increased importance of data science and challenging statistical concepts not easily addressed in current courses and textbooks; (3) developing full story line models of real-world scenarios using game-like simulations; and (4) creating and vetting materials that can be incorporated into a variety of traditional introductory and advanced undergraduate courses. The project team's theory of action is built on developing, implementing and assessing each simulation lab and other components of the project according to these goals. An important motivation is to allow students to develop their own research questions, generate and use their own unique data to make decisions, and then observe and learn from the choices made through their interactions with the technology. To evaluate success of the approaches taken, the project will employ a mixed methods approach to compare learning gains from more traditional materials to the gains made with these new materials, evaluate student attitudes and engagement, use data analytics to assess the effectiveness of the components embedded in each lab, and determine best practices for incorporating the resources into a variety of traditional introductory and advanced undergraduate courses. These fully immersive online game-like labs will be significantly different from other current textbook and online sets of educational materials as each lab will include inquiry-based case studies that contain real-world data analysis complexities, thereby providing a solid introduction to the intellectual content and broad applicability of statistics and data science. In concert with the software lab development, the team will create and vet a new student assessment tool that will be implemented to evaluate students' abilities related to understanding of conceptual connections, communication skills, critical thinking, and problem-solving, as well as their ability to understand and work through challenges emanating from real-world, unstructured datasets. Overall, this project will have significant impact in STEM education by stimulating the power of innovation, creativity, and excitement that occurs within STEM research and applications.