Machine learning based computational methods for development of personalised e-learning systems

The aim of the project is to develop computational methods to do a study into human learning trends to drive development of novel e-learning software systems. The goal is to develop a completely new approach in designing e-learning systems using a machine learning based computational methods, to learn a mapping between the learning material (content, form, delivery) and its effectiveness in the learning process of the user. We will use machine learning techniques to learn the relationship between the features of learning videos (such as duration, amount of text, speed) and user feedback (such as frequency of usage and satisfaction). The goal is to be able to predict the user feedback and performance based on the features of the learning material, and develop a highly personalised computational learning assistant that continuously learn from its user and adapts itself to the user's needs