Integrating the statistical investigation process, data visualization, and simulation into high school statistics

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This project is developing curricular materials that utilize best teaching practices in improving student understanding of statistics and data science for use in high school Algebra I, Algebra II, and Geometry courses. Although teachers are encouraged to integrate statistics and data science in these kinds of high school courses, teachers do not have sufficient access to resources to accomplish this effectively. As a result, many high school students do not understand statistics for its relevance and importance in a data-driven world. This has created a significant need for curricular materials that use best teaching practices with documented impact on student learning. This project’s approach is to focus on meaning and interpretation rather than formulaic algorithms, which from students’ perspectives hide what matters. This project will develop curricular materials for high school students, with collaborative high school teachers for “how-to” manuals.The distinctive feature of these curricular materials is the use of simulation-based inference (SBI) methods, data visualization (DV), and the entire statistical investigation process (6STEPS) to improve students’ understanding of the relevance and power of statistics because these approaches are central to statistical thinking and practice. These approaches (as advocated by the American Statistical Association’s Guidelines for Assessment and Instruction in Statistics Education) focus more on meaning and less on mechanics. This project enacts a pilot set of instructor training and student materials tailored to the HS level which use best pedagogical practices (e.g., designed with multiple learning styles in mind, effective use of technology, data visualizations) which seek to improve students’ statistics education at the high school level, while also providing detailed assessment data exploring the effectiveness of SBI, DV, and 6STEPS approaches to statistical education in high school. The project provides critical information about the ability of these teaching approaches to have a positive impact in the HS classroom. The project directly enrolls 60 HS teachers and about 1,800 students. The data collected is providing information about conceptual learning outcomes, student attitudes, teacher confidence, and learning trajectories using the SBI, DV and 6STEPS approaches. The research question that guides the project is: To what extent are newly developed, high school student-facing curricular materials, which leverage SBI, DV, and the 6STEPS, along with an active-learning pedagogy, able to integrate into existing high school courses (e.g., Algebra I, II, Geometry) and lead to improved student learning outcomes? The project supports a website that shares 24 freely available student-facing and instructor-facing modules, as well as professional development resources. 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.