Effectiveness of Temporal Change Visualization using Augmented Reality in Learning
CHEN ANGIE (1251122)
In this research, we aim to improve the observation stage in the learning process. We categorize observation scenarios which are difficult to accomplish in the real world into limitation of senses, occlusion, and temporal changes. The scope of this research lies on the evaluation of temporal changes. We developed an AR prototype which generates synthesized images of the target plant and be displayed using the visualization methods of side by side and overlay. We further conducted an experiment to evaluate our proposed method and are able to identify the most suitable visualization method for observation under temporal changes.