Abstract: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.
Here we describe the use of learning analytics (LA) for investigating inquiry-based science instruction. We define several variables that quantify curriculum usage and leverage tools from process mining to examine inquiry-based pedagogical processes. These are initial steps toward measuring and modeling fidelity of implementation of a science curriculum. We use data from one school district's use of an online science curriculum (N=1,021 teachers and nearly 330,000 page views).
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