Laboratory for the Study of Extra Solar Planets: Fostering Data Literacy

太阳系外行星研究实验室：培养数据素养提供了一个虚拟环境，在这个环境中，物理课的高中生从事研究系外行星的前沿科学。 该项目建立在以前的工作基础上，并作为一个例子和测试平台，整合科学实践，跨领域概念和科学内容，如下一代科学标准框架所要求的。 该项目产生了七个微型实验室，帮助学生探测系外行星围绕恒星的轨道。 这些包括学习使用模型，学习使用望远镜，使用数据，应用概念来解释数据以及基于数据创建3D交互式模型。 在另外三个红外和光谱实验室中，学生学习应用核心概念和建模来识别系外行星的一些特性。 使用在线望远镜和学习软件，学生可以更深入地了解科学探究，包括模型推理，收集评估和解释真实数据，并从多条证据中得出结论。 教师支持包括在启动，在线专业发展，并与科学界的互动类支持。 先前的工作已被证明具有很大的潜力，可以让女孩和城市地区服务不足社区的学生参与进来。 首要的研究问题是学生如何学习理解数据。 有什么工具可以帮助他们有效地从最初的想法转向更复杂的理解？ 该研究侧重于对数据素养至关重要的三个领域：模型推理，评估数据质量，解释数据和理解不确定性。 第一年收集定性数据，并使用专家制定的标准进行评分。 在第二年，采用了更多的量化措施。 评估工具，使用项目从验证的评估，创建和心理测量验证。 该项目的成果是一个独特的在线实验室，可供所有教室使用，并让学生参与有意义的科学数据收集，分析，可视化，建模和解释，这是当前科学中最令人兴奋的研究前沿之一。 这些活动和评估将天文学转变为一个以探究为基础的主题，大大提高了学生对科学实践和内容的理解，以及他们的科学态度，兴趣和身份。 这项研究推进了我们对提高学生数据素养知识的方法的理解，这在所有学科的科学教育中都非常有用。

The Laboratory for the Study of Extra Solar Planets: Fostering Data Literacy provides a virtual environment in which high school students in physics classes engage in the cutting edge science of studying exoplanets. The project builds on previous work and serves as an example and test bed for integrating science practice, crosscutting concepts and science content as called for in the Framework for the Next Generation Science Standards. The project produces seven mini-labs that scaffold students in the detection of orbits of exoplanets around their stars. These include learning to use models, learning to use the telescope, working with data, applying concepts to interpret data and creating a 3-D interactive model based on their data. In three more laboratories on infrared and spectroscopy, students learn to apply core concepts and modeling to identify some of the properties of the exoplanets. Using online telescopes and learning software, students gain a deeper understanding of science inquiry, including reasoning from models, gathering assessing, and interpreting authentic data, and drawing conclusions from multiple line of evidence. Teacher support includes in-class support on start-up, online professional development, and interaction with the scientific community. The previous work has been shown to have strong potential for engaging girls and also students in underserved communities in urban areas. The overarching research question is how students learn to make sense of data. What are the tools that can help them move efficiently from their initial ideas to more sophisticated understandings? The research focuses on three areas that are fundamental to data literacy: reasoning from models, assessing the quality of the data and interpreting data and understanding uncertainty. Qualitative data are gathered in the first year and scored using a rubric developed by experts. In year two, more quantitative measures are employed. Assessment instruments, using items from validated assessments, are created and psychometrically validated. The outcomes of this project are a unique online Laboratory that is universally accessible to all classrooms and that engages students in meaningful scientific data collection, analysis, visualization, modeling and interpretation at one of the most exciting research frontiers in current science. The activities and assessments transform astronomy into an inquiry-based subject that significantly increases students' understanding of science practice and content as well as their science attitudes, interest, and identity. The research advances our understanding of ways to increase students' knowledge of data literacy, which is widely useful in science education across all disciplines.