In this thesis, we incorporate information theory into statistical signal processing and machine learning in order to achieve robust learning in presence of outliers (or generally in environments with non-Gaussian structure). In other words, by incorporating information theory especially when structure of environment is non-Gaussian, the…

This dissertation describes an experiment to investigate how learners with different levels of background in computer science learn core concepts of computer science, in particular, algorithms. We designed a study to focus on cognitive task analysis for eliciting the empirical mental elements of learning two graph algorithms. Cognitive workload…

Three studies were conducted to explore machine learning support of novel learning problems. The first was a study of a computer-supported online learning website, which was designed to support teachers improving their pedagogy and this work created a data-first approach for Linguistic pedagogy, and to support improved pedagogy delivery and…