Improving Undergraduate Scientific Explanations: Exploring the Role of Data Literacy Skills in Scientific Reasoning

该项目旨在通过调查如何教授本科生解释数据和应用科学推理来提高他们的科学解释，从而为国家利益服务。为此，该项目旨在制定战略性、易于实施的方法，以提高学生的数据素养技能。学生将被引导通过一系列步骤，以帮助他们识别和描述数据中的模式。 其他步骤将指导他们使用这些数据模式作为证据，对调查中的现象作出结论。 这些教学策略将在海洋学入门课程中进行测试，使用来自国家科学基金会资助的海洋观测站倡议（OII）的数据集。通过利用与OII相关的教育工作者社区，这项工作的成果将直接与教授类似海洋学课程的人分享。 因此，该项目预计将广泛采用它认为对本科海洋学学生最有效的策略。该项目的结果预计也将适用于各科学学科，并可能用于提高广泛的本科课程。因此，本项目将开发的材料和数据提供给其他教育工作者，使他们能够方便地使用或修改。本项目的核心是通过培养学生的数据素养和推理能力，最终提高他们构建科学准确解释的能力，从而改善本科STEM教育。该项目旨在调查如何修改解释框架可能会影响本科生的科学解释技能的发展，并寻求确定本科生在构建科学解释时遇到的具体挑战。具体而言，本项目将连接两个认知领域，科学推理和数据素养，以制定更有效的教学策略，提高本科生的科学素养。该项目将采用一种趋同的、多阶段的混合方法研究方法，其中将包括一项试点研究，以收集定量和定性数据，为项目的后期阶段提供信息。在导师的指导下，学生将使用OOI数据探索项目中教学上适当和可调整的数据可视化，以及补充的静态（例如，纸）图形表示。将对本项目中使用的教学策略的设计和实施进行评估，以考虑寻求实施干预措施的未来教师的专业发展需求。 制定了传播计划，以确保与科学教师、学习科学家和其他教育研究人员广泛分享有效的战略。该提案是为了回应“亲爱的同事信：促进新机构参与改善本科STEM教育：教育和人力资源计划”（NSF 20-034）。 NSF IUSE：EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national interest by investigating how teaching undergraduate students to interpret data and apply scientific reasoning can improve their scientific explanations. To this end, the project aims to develop strategic, easy-to-implement approaches to enhance students’ data literacy skills. Students will be guided through a sequence of steps to help them recognize and describe patterns in data. Additional steps will guide them to use such data patterns as evidence for making conclusions about the phenomena under investigation. These teaching strategies will be tested in introductory oceanography courses, using data sets from the NSF-funded Ocean Observatories Initiative (OII). By leveraging the community of educators associated with OII, the results of this work will be directly shared with people who teach similar oceanography courses. As a result, the project anticipates wide adoption of the strategies it finds to be most effective for undergraduate oceanography students. The results of the project are also expected to be applicable across science disciplines and might be used to enhance a broad range of undergraduate courses. Consequently, the project plans to provide online access to the materials and data sets it develops, so that they can be easily adopted or adapted by other educators.This project is centered on improving undergraduate STEM education by building students’ data literacy and reasoning skills and, ultimately, enhancing their ability to construct scientifically accurate explanations. The project aims to investigate how a modified explanation framework could influence the development of undergraduate students' scientific explanation skills and seeks to identify the specific challenges undergraduate students experience when constructing scientific explanations. Specifically, this project will link two cognitive realms, scientific reasoning and data literacy, to develop more effective instructional strategies for improving undergraduate students’ science literacy. The project will follow a convergent, multiphase mixed methods research approach, which will include a pilot study to collect both quantitative and qualitative data that will inform the later stages of the project. Guided by their instructors, students will use pedagogically appropriate and adjustable data visualizations from the OOI Data Explorations project, together with complementary static (e.g., paper) graphical representations. The design and implementation of instructional strategies used in this project will be evaluated to consider the professional development needs of future instructors seeking to implement the interventions. Dissemination plans have been designed to ensure that effective strategies are shared broadly with science instructors, learning scientists, and other educational researchers. This proposal was submitted in response to the “Dear Colleague Letter: Stimulating Participation from Institutions New to the Improving Undergraduate STEM Education: Education and Human Resources Program" (NSF 20-034). The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.