SCoE: Learning Analytics in K-12

See a list of books on educational research in our Sage Knowledge database.

See a list of recommended resources, by methodology or design.

Provides a novel approach for interpreting student behavior and performance and then adaptively supporting students working in open-ended computer-based learning environments. Author: James R. Segedy, Vanderbilt University.

Establishes ADAGE as an assessment data framework for learning games; empirically, it then investigates ADAGE-generated performance data to assess learner trajectories in a biology videogame. Author: Elizabeth V. Owen, The University of Wisconsin - Madison.

Proposes an analogous methodology for pedagogy called Computer-Supported Agile Teaching (CSAT). The CSAT framework is founded on the principles of agile teaching, active learning, and a reliance on technology in achieving pedagogy design that is efficient with decision-making that is evidence-based. Author: William T. Tarimo, Brandeis University.

Presents an initial validation argument for a novel constraint- referenced analytics method for measuring cognitive processes during algebra learning in the context of activities conducted with a classroom network of handheld devices. Author: Scot McRobert Sutherland, University of California, Davis.

Examined how Dr. Scratch, a CT assessment tool, functions as an assessment for computational thinking. This study compared strengths and weaknesses of the CT skills of 360 seventh- and eighth-grade students who were engaged in a Scratch programming environment through the use of Dr. Scratch. Author: Kevin N. Lawanto, Utah State University.

Provides a novel approach for the systematic design and implementation of a CT-based science learning environment for middle school students, which can be integrated into the middle school curricula by teachers with little prior programming experience. Author: Satabdi Basu, Vanderbilt University.

Explores the application of various machine learning techniques to the problem of predicting which students may be at risk of some adverse outcome. Author: Everaldo Aguiar, University of Notre Dame.

A content analysis of US Department of education reports, personalized learning advocacy narratives, and published research monographs reveals how big data is moving educational decisions from public school classrooms to private corporate spaces and changing the very conceptions of public and private. Author: Heather M. Roberts-Mahoney, D'Youville College.

Focuses on creating and scaffolding shared student/system control over problem selection in ITSs by redesigning an Open Learner Model (OLM, visualizations of learning analytics that show students’ learning progress) and integrating gamification features to enhance students’ domain level learning and enjoyment. Author: Yanjin Long, Carnegie Mellon University.