Data collected from online learning and tutoring systems for individual students showed strong autocorrelation or dependence because of content connection, knowledge-based dependency, or persistence of learning behavior. When the response data show little dependence or negative autocorrelations for individual students, it is suspected that…

This chapter details the process the University of Michigan developed to build institutional capacity for learning analytics. A symposium series, faculty task force, fellows program, research grants, and other initiatives are discussed, with lessons learned for future efforts and how other institutions might adapt such efforts to spur cultural…

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

A recent trend in data-informed continuous improvement efforts is the practice of student-involved data use (SIDU), wherein teachers guide students in tracking and analyzing their own learning data. However, as SIDU is a newer emphasis in educational data use, research is scarce as to how teachers (preservice or veteran) develop the knowledge and…