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Combining computational and science practices in K-12 education

In science education, the use of computational tools brings many possibilities for collecting, manipulating, and visualizing data, opening new pathways for exploring and making sense of scientific phenomena. However, although new types of data can now be easily accessed and collected for educational purposes, there are still few tools designed for children to make sense of these data in diverse and personally meaningful ways. The present study aims to explore new possibilities for integrating computational and science practices in K-12 education, with a focus on data analysis and visualization, in order to make science learning more relevant, contextualized, and meaningful to students. To this end, we intend to (a) develop a data visualization tool that allows students to engage in new ways of exploring and making sense of data through a block-based programming environment, and (b) codesign with middle school science teachers curricular units that will integrate the tool with the investigation of specific scientific phenomena. Interviews with teachers and students and classroom observations will be analyzed to identify affordances and limitations of the tool, as well as relevant pedagogical strategies and design principles that can guide the development and improvement of similar tools and curricular units.