The aim of this research is identify the effectiveness of a multiple representation-based learning model, which builds a mental model within the concept of atomic structure. The research sample of 108 students in 3 classes is obtained randomly from among students of Mathematics and Science Education Studies using a stratified random sampling…

We present an inference algorithm for perturbation models based on Poisson regression. The algorithm is designed to handle unclassified input with multiple errors described by independent mal-rules. This knowledge representation provides an intelligent tutoring system with local and global information about a student, such as error classification…

This paper describes a narrative-based interactive learning environment which aims to elucidate reasoning using interactive scenarios that may be used in training novices in decision-making. Its design is based on an approach to generating narrative from knowledge that has been modelled in specific decision/reasoning domains. The approach uses a…

This paper presents a hybrid course framework at the Teachers College at Columbia University (New York) that seamlessly integrates a traditional course plan designed for on-campus students with an online course plan designed for distance learning students. Based on innovative teaching and learning principles, the course encourages active…