Zoom In! Learning Science with Data

This project will address the need for high quality evidence-based models, practices, and tools for high school teachers and the development of students' problem solving and analytical skills by leveraging novel research and design approaches using digital tools and two well-established online instructional platforms: Zoom In and Common Online Data Analysis Platform.            

Award Number: 
1621289
Funding Period: 
Thursday, September 15, 2016 to Saturday, August 31, 2019
Full Description: 

This project will expand the DRK-12 portfolio by contributing to a limited program portfolio on data science, and also by being responsive to a broader, national discourse on data science, exemplified in the data-dependent scientific practices emphasis in the Next Generation Science Standards (NGSS). With the impetus toward data literacy, an acute need has emerged for high quality evidence-based models, practices, and tools to better prepare high school teachers to teach data skills and for students to develop the problem solving and analytical skills needed to interpret and understand data, particularly in the sciences. This project will address these challenges by leveraging novel research and design approaches, using digital tools and two well-established online instructional platforms; Zoom In and Common Online Data Analysis Platform.

With a user base of over 27,000 teachers and students, the existing Zoom In platform has proven successful in fostering evidence-based inquiry among social studies teachers. This project will test the feasibility of the platform to facilitate data-focused inquiry and skill development among high school science teachers and their students. In Year 1, two NGSS-aligned digital curriculum modules and supporting materials focused on scientific phenomena and problems in biology and earth science will be developed for high school science teachers and embedded in a modified iteration of Zoom In. The Common Online Data Analysis Platform (CODAP) will be integrated into the modules to make hierarchical data structures, modeling, visualizations, and dynamic linking possible within Zoom In. A pilot and usability test will be conducted with 16 teachers and 100 students from diverse New York City public high schools. Two teacher focus groups and think-aloud sessions with the students will be held. In Year 2, the remaining four modules will be developed. Guided by four research questions, field testing with teachers and students will be done to assess the content, CODAP data tools, Zoom-in student supports, teacher supports, and outcome measures. In Year 3, final revisions to the tools will be completed. A small-scale efficacy test will be conducted to assess aspects of the implementation process, practices, and overall impact of the modules on student learning. For the efficacy study, a two-level cluster-randomized design will be employed to randomly assign schools to the Zoom In intervention. A comparison group will use another existing well-designed data literacy digital instructional platform but without key aspects of Zoom In. Outcome measures will be administered at the beginning and end of the school year to the treatment and comparison groups. Back-end data, observational data, and teacher log data will be collected and analyzed. Qualitative data will be gathered from teacher and student observations and interviews and analyzed. Researchers will analyze the impact on student learning using hierarchical linear models with an effect treatment condition and student-and-class-level covariates. The research findings will be broadly disseminated through the Zoom In platform, conferences, publications, and social media.

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