Learner Processing of Feedback in Intelligent Learning Environments
This project will develop our understanding the kinds of feedback provided to learners in an intelligent learning environment (ILE) that work best with learners of differing ability levels. It will begin with categorising the types of feedback provided in three different ILEs and analysing how the assistance they provide varies in terms of representation (symbolic, text, audio, etc.), timing, frequency and depth. Then learners will be observed in the Learning Interaction Classroom at the University of Melbourne to determine how they react to and benefit from the forms of assistance. Once that is understood, we will study learners using the ILEs in the Educational Neuroscience Classroom at the University of Queensland to understand from a neural perspective how they react and benefit from the assistance. The outcome of the project will be a report that draws out some general principles on how the different forms of assistance might be optimised for different learners using ILEs.