This project will develop a set of statistics learning materials, with data visualization tools and an applied social science focus, to design applied data investigations addressing real-world socioeconomic questions with large-scale social science data. This project is designed to promote statistical understandings and interest in quantitative data analysis among high school students and engage students with content that resonates with their interests.
The Strengthening Data Literacy across the Curriculum (SDLC) project seeks to significantly enhance the learning and teaching of Science, Technology, Engineering, and Mathematics (STEM) high school students and teachers through the development of resources, models, and tools. This project is designed to promote statistical understandings and interest in quantitative data analysis among high school students. The project will target students outside mathematics and statistics classes who seldom have opportunities formally make sense of large-scale quantitative data. The population for the initial study will be humanities/social studies and mathematics/statistics high school teachers and their classes. The focus on social justice themes are intended to engage students with content that resonates with their interests. This strategy has the potential to demonstrate ways to provide rich, meaningful statistical instruction to a population that seldom has the opportunity for such learning. By capturing students' imagination and interest with social justice themes, this project has the potential of high impact in today's society where understanding and preparing statistical reports are becoming more critical to the general populace.
This project will build on prior theory and research to develop a new set of statistics learning materials, with data visualization tools and an applied social science focus to design three 2-week applied data investigations (self-contained modules) addressing real-world socioeconomic questions with large-scale social science data. The modules will be aligned with the high school Common Core State Standards for Mathematics and key statistical content for college students. The purpose of the study is to strengthen existing theories of how to design classroom learning materials to support two primary sets of outcomes for high school students, particularly among those historically underrepresented in STEM fields: 1) stronger understandings of important statistics concepts and data analysis practices, and 2) interest in statistics and working with data. The modules will engage students in a four-step investigative process where they will (1) formulate questions that can be answered with data; (2) design and implement a plan to assemble appropriate data; (3) use numerical and graphical methods to explore the data; and (4) summarize conclusions relating back to the original questions and citing relevant components of the analysis that support their interpretation and acknowledging other interpretations.
The project will employ a Design-Based Implementation Research (DBIR) design using both quantitative and qualitative data to determine results of targeted outcomes (noted above) as well track whether there is any evidence to support the conjectures that key module components directly impact targeted student outcomes. Starting with a well-defined, preliminary conceptual framework for the study, the project team will conduct four cycles of iterative design and testing of the proposed SDLC modules over two academic years, with each cycle occurring during a fall or spring semester.