Supporting materials for active e-learning in computational models

Abstract

In traditional lecture-driven learning, material to be learned is often transmitted to students by teachers. That is, learning is passive. In active learning, students are much more actively engaged in their own learning while educators take a more guiding role. This approach is thought to promote processing of skills and knowledge to a much deeper level than passive learning. In this paper, a research using supporting materials for active e-learning in computational models and related fields is presented. The contributions of this paper are supporting active tools to improve learning and an evaluation of its use in context. © 2008 Springer-Verlag Berlin Heidelberg.