This project is developing a data literacy curriculum for 7th grade students which will be composed of four two-week units to be taught in social studies, mathematics, science and English courses. The curriculum will utilize data on water use and quality in Ohio, chosen because other communities will have comparable data to modify the curriculum to meet their needs. Central to the curriculum will be the issue of fairness and how data are used to make societal decisions. The curriculum will be pilot tested and field tested in three middle schools in Ohio.
Research will be conducted on the efficacy of an instructional model called Preparation for Future Learning (PFL). The underlying tenant of this model is that learning is enhanced if students become familiar with a problem and its context before a solution is developed. In this case, the social studies unit will be the preparation for the learning that will occur in mathematics and science.
"We use data every day—to choose medications or health practices, to decide on a place to live, or to make judgments about education policy and practice. The newspapers and TV news are full of data about nutrition, side effects of popular drugs, and polls for current elections. Surely there is valuable information here, but how do you judge the reliability of what you read, see, or hear? This is no trivial skill—and we are not preparing students to make these critical and subtle distinctions." -- Andee Rubin Thinking with Data (TWD) is an Instructional Materials Design project which developed and tested a cross-curricular unit designed to cultivate middle school students’ deep understanding of data literacy. The TWD unit consists of four, two-week replacement modules for interdisciplinary implementation in seventh grade Social Studies, Mathematics, Science, and English Language Arts. The modules address issues of data representation, proportional reasoning, and data-based argumentation using real data in discipline-specific, problem-solving contexts aligned with relevant subject area standards. The context for the TWD modules is a compelling one: world water issues. Activities and materials are designed around student investigations of water issues in the Tigris/Euphrates and six US watersheds using real world data. Data manipulation across the unit centers on use of proportional reasoning, an important part of middle school curricula and the foundation for higher mathematics. In Social Studies, students use existing data to explore water availability and usage in Turkey, Syria, and Iraq, and try to devise fair ways of sharing available water. In Mathematics, they learn techniques of proportional reasoning to expand on their Social Studies work and develop data-based solutions and arguments for fair use. In Science, they learn about the science behind water issues in the Tigris/Euphrates basin, beginning with how the water cycle manifests itself in the region, and how ditch irrigation contributes to soil salinity. Students then explore water issues in six US watersheds. In English Language Arts, students develop reports on these (US watershed) issues and present possible solutions to them as persuasive arguments developed within both written essays and oral presentations. The TWD unit is grounded in a Preparation for Future Learning (PFL) pedagogical approach (Bransford & Schwartz, 1999). It investigates how preparing students to learn in one curricular context (Social Studies) with formal learning occurring in another (Mathematics) can improve students’ deep understanding of data literacy. The project further explores extending the PFL approach to include application and communications activities in still other curricular contexts (Science / ELA), which we believe will further enhance their learning of data literacy (see Figure 1). Field testing of the Thinking with Data modules and materials took place with seventh graders in two middle schools in northeast Ohio. Schools were selected because they utilized a team teaching approach which kept students together for math, science, social studies and English language arts. This allowed researchers to explore the efficacy of the TWD unit through observations, interviews with teachers and students, and the comparison of data literacy gains between students in the teams participating in the unit and their classmates on other teams. All seventh grade students were pre- and post-tested using a scenario-based, five-question test of data literacy. The test assessed students’ ability to interpret and argue from data presented in tables (Q1), to synthesize data across table to explore explanations (Q2), to glean data and data-based explanations from newspaper articles (Q3), to perform proportional calculations and interpret their meaning (Q4), and to know what data they were missing and would need to further investigate the issues presented (Q5). As can be seen in Figure 2, TWD students in both schools made greater pre- to post-test gains on all questions than did their classmates who didn’t participate in the unit. The findings support the usefulness of both the TWD unit and the PFL framework within a cross-curricular context. Other pre- and post-testing with just TWD participants showed that students learned important seventh grade math and science content as they were acquiring data literacy skills. Broader Impacts: The TWD unit uses authentic school settings to promote the teaching and learning of data literacy, a critical skill. It provides a scientific basis for conducting school-based data literacy activities that cut across disciplines. The notion that we cannot separate literacy in Reading from comprehension in Science is becoming commonplace. Similarly, we expect that it will soon become generally accepted that we should not separate data literacy into distinct discipline-specific components. Our research contributes to a future in which the importance of teaching data literacy is recognized as an urgent public policy matter. By reevaluating the overall curriculum structure, policy makers can enhance education and increase the range of students both interested in and capable of analyzing data as informed and responsible citizens. For more information, visit the Thinking with Data website at: www.rcet.org/twd/index.html
