A Strategy for Incorporating Learning Analytics into the Design and Evaluation of a K-12 Science Curriculum

Carlos Monroy
Virginia Snodgrass Rangel
Reid Whitaker


In this paper, we discuss a scalable approach for integrating learning analytics into an online K–12 science curriculum. A description of the curriculum and the underlying pedagogical framework is followed by a discussion of the challenges to be tackled as part of this integration. We include examples of data visualization based on teacher usage data along with a methodology for examining an inquiry-based science program. With more than one million students and fifty thousand teachers using the curriculum, a massive and rich dataset is continuously updated. This repository depicts teacher and student usage, and offers exciting opportunities to leverage data to improve both teaching and learning. In this paper, we use data from a medium-sized school district, comprising 53 schools, 1,026 teachers, and nearly one-third of a million curriculum visits during the 2012–2013 school year. This growing dataset also poses technical challenges such as data storage, complex aggregation, and analyses with broader implications for pedagogy, big data, and learning.


Learning analytics; science education; online curriculum; K12

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DOI: http://dx.doi.org/10.18608/jla.2014.12.6


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