Last month, students and faculty took part in a key phase of eCampusOntario’s ongoing learning analytics initiative: a sprint designed to gather student insight and understand student learning experiences.
fter a fruitful collaboration between the different partners, the Erasmus+ project “Supporting Higher Education to Incorporate Learning Analytics” (SHEILA) concluded in September 2018. The project aimed to build a policy development framework that supports systematic, sustainable, and responsible adoption of learning analytics (LA) at institutional level.
Probabilistic soft logic (PSL) is a machine learning framework for developing probabilistic models. PSL models are easy and fast, you can define them using a straightforward logical syntax and solve them with fast convex optimization.
The SHEILA project team ran a workshop on “Developing an evidence-based institutional learning analytics policy” at the 13th European Conference on Technology Enhanced Learning on 3 September at the University of Leeds.
Learning Analytics in the Classroom presents a coherent framework for the effective translation of learning analytics research for educational practice to its practical application in different education domains.
The field learning analytics is established with the promise for the education sector to embrace the use of data for decision making. There are many examples of successful use of learning analytics to enhance student experience, increase learning outcomes, and optimize learning environments.
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).