Art. 05 – Vol. 23 – No. 2 – 2013
Abstract: Educational systems based on augmented reality have specific features such as: 3D visualization, animation, vocal interface for teaching and guidance, direct manipulation, and haptic feedback. This paper presents a causal model for the analysis of the contribution of these features on the faster learning of Chemistry. The model was developed by carrying on a path analysis that is based on a multilevel multiple regression. The results show the contribution of these features and enable the identification of direct and indirect effects of each factor on a faster learning.
Key words: e-learning, learning efficiency, causal relations, path analysis, augmented reality.