This study aims at providing explanations of students’ behaviors on LMS by incorporating dispositional dimensions (e.g., self-regulation and emotions) into conventional learning analytics models. Using a combination of demographic, trace, and self-reported data.
Should students be told what the data predict about their chances of success? Corporate leaders in predictive analytics business consider the issue posed by an Inside Higher Ed blogger.
The Inspire plugin implements open source, transparent next-generation learning analytics using machine learning backends that go beyond simple descriptive analytics to provide predictions of learner success, and ultimately diagnosis and prescriptions (advisements) to learners and teachers. From Moodle HQ.
Jeff Greene and Matt Bernacki are learning scientists in the UNC-Chapel Hill School of Education. They leverage the data that students create when they use digital resources to help them learn.