A Personalized Learning System with an AR Augmented Reality Browser for Ecosystem Fieldwork
Masato Kasahara, Kosuke Takano, Kin Fun Li · 2014
In this paper, we present a mobile learning tool for ecosystem study using an augmented reality user interface. Our system provides a recommender function of learning content according to a learner's interest, which is extracted in the form of a feature term set that is based on the user's browsing behavior of learning content and its related objects, which are displayed through the augmented reality user interface. Using a prototype, we confirmed that our system can properly personalize the recommended results for ecosystem-related learning content, and we have the promising vision that our system can be utilized in a practical way for mobile learning in fieldwork for ecosystem studies.