Invigorating Statistics Teacher Education Through Professional Online Learning (InSTEP)

在美国，在初中和高中实施有意义的统计教育一直是一个长期的挑战。统计和数据科学是STEM职业生涯和公民普遍数据素养的关键领域。该项目旨在通过为教师设计和实施在线专业学习环境，加强6-12年级的统计和数据科学教学。专业学习环境旨在支持在职教师发展更强的与统计学有关的教学知识，以及如何在课堂上有效教授统计学的知识。该项目还将评估一种专业发展模式，该模式将个性化在线学习和微认证(获得小规模认证)相结合，以更好地了解其在支持教师学习方面的有效性。该项目将借鉴以前的工作，汇编在线模块，让教师参与高质量的统计和数据科学任务，分析教师和学生处理这些任务的视频，学习教师执行任务的教学框架，并探索确定和制定高质量统计和数据科学任务的指导方针。该项目将通过使用这些模块来研究教师的学习，以及教师通过这些模块选择的途径来了解该模式的有效性。该项目建立在调查人员之前的工作基础上，开发基于研究的教师专业发展模块，以支持6-12年级的统计和统计教育的学习。目前开发的材料包括一系列微证书，其设计特征与有效教师专业发展的研究相一致。它们包括让教师有机会接触到与他们教授的目标年级水平相适应的统计内容，有机会让他们在类似的情况下与教师进行积极的学习机会，以及以教师带来的知识和经验为基础的连贯的重点。该项目将分阶段进行，首先是以初稿为基础的初中和高中教师和地区领导人的重点小组。随后将对参与微证书生态系统的教师进行认知访谈，这将为系统的修改提供信息。在这一阶段之后，一批教师(第一组25人，第二组75人)将参与脚手架专业发展，参与教材，并将根据他们的知识和实践的变化进行评估。该项目将使用可靠和有效的统计、知识和实践措施来评估教师知识的变化。将从在线平台收集有关教师参与度和使用率的数据，以更好地了解材料的使用率和途径。专业学习平台将在项目结束时作为免费和开放的在线资源提供。探索研究预科-12项目(DRK-12)旨在通过研究和开发创新资源、模型和工具，显著提高预科-12学生和教师在科学、技术、工程和数学(STEM)方面的学习和教学。DRK-12计划中的项目建立在STEM教育的基础研究和先前的研究和开发工作的基础上，为拟议的项目提供了理论和经验上的证明。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Implementing meaningful statistics education in middle and high schools has been a persistent challenge in the United States. Statistics and data science are critical domains for STEM careers and the general data literacy of the citizenry. This project seeks to strengthen the teaching of statistics and data science in grades 6-12 through the design and implementation of an online professional learning environment for teachers. The professional learning environment aims to support in-service teachers in developing stronger content knowledge related to statistics, and knowledge of how to effectively teach statistics in their classrooms. The project will also evaluate a model of professional development that integrates personalized online learning and microcredentialing (earning small-scale certifications) to better understand its effectiveness in supporting teacher learning. The project will draw from previous work to assemble online modules that engage teachers in doing high-quality statistics and data science tasks, the analysis of video of teachers' and students' work with those tasks, learning a pedagogical framework for teachers to implement the tasks, and exploring guidelines for identifying and developing high-quality statistics and data science tasks. The project will study teacher learning through the use of these modules, and the pathways that teachers choose through them to understand the effectiveness of the model.The project builds on previous work by the investigators to develop research-based teacher professional development modules that support learning about statistics and statistics education in grades 6-12. Materials currently developed include a series of microcredentials with design features consistent with research on effective teacher professional development. They include opportunities for teachers to engage with statistics content appropriate to the target grade levels they teach, active learning opportunities that engage them with teachers in similar contexts, and a coherent focus that builds on the knowledge and experience teachers bring to the table. The project will take place in iterative phases, beginning with focus groups of middle and high school teachers and district leaders based on first drafts of the materials. This will be followed by cognitive interviews with teachers who engage in the microcredential ecosystem which will inform modifications to the system. Following this phase, cohorts of teachers (25 in the first cohort, 75 in the second) will participate in scaffolded professional development engagement with the materials, and will be assessed with respect to changes in their knowledge and practice. The project will assess changes in teacher knowledge using reliable and valid measures of statistics knowledge and practice. Data will be collected from the online platform regarding teacher engagement and usage to better understand usage and pathways through the materials. The professional learning platform will be made available as a free and open online source at the close of the project.The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.