... 6. Learning analytics play an important role in informing appropriate and effective student interventions, including through predictive modelling and personalising the learning experience.
The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach for advancing our understanding of the learning process.
"Institutions are bringing this data together into a central database, not just using it for learning analytics, but they are also very keen to make that data accessible and available for students to see" - Rob Wyn Jones, our senior data and analytics integrator, shares an update on learning analytics.
Tutorial, Learning Analytics Summer Institute, Ann Arbor, June 2017 As algorithms pervade societal life, they’re moving from an arcane topic reserved for computer scientists and mathematicians, to the object of far wider academic and mainstream media attention
In the era of increasing technology mediation Learning experiences need to be designed considering the capacity to capture data, the possibility of making sense and derive knowledge from the data, and the need to act on that knowledge.
Blackboard’s data science team conducts analysis of the relationship between the use of academic technologies and student outcomes, in order to inform our understanding of how students and faculty use educational technologies and infer relationships with effective pedagogical practices that can be incorporated at scale
Critical thoughts from a professor (mso) in the Department of Communication and Psychology at Aalborg University who works within the area of educational technology and is more specifically interested in Networked Learning, Problem Based Learning and collaborative learning