Invigorating Statistics Teacher Education Through Professional Online Learning (InSTEP)

在美国初中和高中实施有意义的统计学教育一直是一个挑战。统计和数据科学是STEM职业和公民一般数据素养的关键领域。本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年级统计和数据科学的教学。专业学习环境旨在支持在职教师发展与统计相关的更强的内容知识，以及如何在课堂上有效地教授统计知识。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与小额认证（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。该项目将借鉴以往的工作，组装在线模块，让教师参与高质量的统计和数据科学任务，分析教师和学生完成这些任务的视频，学习教师执行任务的教学框架，并探索确定和开发高质量统计和数据科学任务的指导方针。该项目将研究教师通过使用这些模块学习的情况，以及教师通过这些模块选择的途径，以了解该模型的有效性。该项目以调查人员以前的工作为基础，开发以研究为基础的教师专业发展模块，支持6-12年级的统计和统计教育学习。目前开发的材料包括一系列与有效教师专业发展研究相一致的设计特征的微证书。这些机会包括让教师有机会接触与他们所教的目标年级相适应的统计内容，让他们在类似背景下与教师接触的主动学习机会，以及以教师带来的知识和经验为基础的连贯关注。该项目将在迭代阶段进行，首先以初稿为基础，由初中和高中教师和地区领导组成焦点小组。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，教师队伍（第一组25人，第二组75人）将参与与材料相关的专业发展活动，并将评估他们在知识和实践方面的变化。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情况的数据，以便更好地了解材料的使用情况和途径。该专业学习平台将在项目结束时作为免费开放的在线资源提供。探索研究preK-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preK-12学生和教师对科学、技术、工程和数学（STEM）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实证依据。该奖项反映了美国国家科学基金会的法定使命，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。

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.