Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…

National testing and reform agendas, with their focus on school improvement, has led to increased collection and scrutiny of student data. The analysis of these data usually occurs at a school level, often by school leaders. What is less common is the opportunity for students to scrutinise their individual data and take ownership over the results…

User clustering algorithms have been introduced to analyze users' learning behaviors and help to provide personalized learning guides in traditional Web-based learning systems. However, the explicit and implicit coupled interactions, which means the correlations between user attributes generated from learning actions, are not considered in these…

Disorder and linearity are essential to science, but empirically derived laws indicate that counts do reflect underlying structure and can support inference. Starting from the premise that a linear structure underlies data, G. Rasch deduced that the necessary and sufficient mechanism to convert from counts to linear measures is the logistic ogive.…

This paper addresses two audiences--those who design education trend studies that simultaneously have longitudinal and intercohort implications, and the secondary analysts who use such trend data. Four study series conducted for the U.S. Department of Education's National Center for Education Statistics (NCES) provide material for the paper: the…