Implementation a Context-Aware Plant Ecology Mobile Learning System

Abstract

Mobile devices are becoming ubiquitous methodologies and tools, providing application for learning and teaching field. On the basis of the widespread use of wireless devices and mobile computing technology, this study proposes a context-aware plant ecology learning system (CAPELS) based on context-aware technology; adapting deep neural networks (DNN) and leaf vein and shape identification algorithm which can identify plant leaves, this system automatically provides relevant botanical and growth environment knowledge to the learners. Therefore, during outdoor education, it can assist learners in accurately obtaining the required relevant botanical and growth environment knowledge. The experimental results indicate that students who used CAPELS performed better learning about plant ecology than those who did not. We also delivered questionnaires to those who used CAPELS and analyzed the results by using the partial least squares (PLS) method. The results have shown that CAPELS can encourage student’s learning motivation and thus improve their learning effectiveness. Thus, CAPELS provides a new educational platform for promoting ecology learning approach and effectively improves student learning efficiency and motivation.