Improved user experience and first-of-its-kind data visualization aims to give higher ed administrators a clear look at lecture capture usage and student activity.
This presentation explores shortcomings of learning analytics for the wide adoption in educational organisations. It is NOT about ethics and privacy rather than focuses on shortcomings of learning analytics for teachers and students in the classroom (micro-level).
Data and analytics are at the center of today’s student success movement. Increased interest and access to institutional data are helping colleges and universities identify systematic and structural barriers to retention and graduation. Predictive analytics is making proactive advising possible at scale.
This paper presents a systematic literature review of the state-of-the-art of research on learning dashboards in the fields of Learning Analytics and Educational Data Mining.
OU Analyse is a project piloting machine-learning based methods for early identification of students at risk of failing. All students with their risk of failure are available weekly to the course tutors and the Student Support Teams to consider appropriate support. The overall objective is to significantly improve the retention of OU students.