Computer Science Meets Social Studies

Abstract

Data science is an emerging 21 st century literacy that promises to support learning in a wide variety of disciplines. It also provides an engaging context in which to learn computational thinking skills in existing classroom contexts. For my dissertation research, I will explore whether and how data science can support inquirybased learning in social studies. I conjecture that data science could provide students with an opportunity to use computing to better understand their social world, while also allowing students to draw from and make sense of their own experiences. I plan to explore this idea by enhancing and evaluating a software tool, Local Ground, and creating a curriculum that helps young people identify and describe salient characteristics of their lived realities, moving from unstructured to structured data representations (e.g., photos to tags to databases). This process may generate a rich, motivating data source to explore subsequent ideas in computational thinking and social science.

Predictors of Academic Achievement in Blended Learning: the Case of Data Science Minor

“…A ubiquitous proliferation of demand for data science-related competences (data literacy) poses new challenges for universities all over the world. On the one hand, high market demand makes it easy to attract students from different disciplines [1], including non-STEM disciplines [2]. On the other hand, it makes the student audience extremely heterogeneous in terms of disciplinary background and the level of mathematical preparation [3], complicating the pedagogical design.…”