Develop insights into student performance and content quality through analytics of learner activities.
360AI’s Learning Analytics includes the measuring, collecting, analysis and reporting on student data and their context. The goal of Learning Analytics is to better understand and improve the learning process and the resources (eg. content) that are used. 360AI provides predictive models that recognise and explore underlying patterns of teaching, learning and educational organisations.
360AI Learning Analytics algorithms leverage the educational data and relationships stored in the learner, content and outcome model to create valuable new insights for educators, teachers and learners. This means real-time insights in organisational processes surrounding education.
360AI is able to enhance the education value chain by faster decisions, interventions and personalised recommendations on the basis of structured and unstructured big data.
- Learning Graph reinforcement - Learning activities are constantly monitored and fed back into the 360AI Learning Graph to reinforce existing relationships in the learner, outcome and content model. This way the Learning Graph learns from these interactions, enabling it to generate more precise recommendations and predictions.
- Pattern Detection - Identifies trends and patterns in large quantities of temporal educational big data.
- Predictive Modelling - Uses statistical analysis of educational data to predict learning outcomes, in order to allow teachers or even learners themselves to intervene in ineffective study behaviours.
360AI Learning Analytics allows you to answer questions such as:
- When are learners ready to move on to the next subject?
- What learning behaviours are likely to lead to positive learning results and should be reinforced?
- When are learners at risk to fall behind?
- What grade is a learner expected to obtain for a given subject?
- Are interventions by teachers needed to support the learners with reaching his goals?