Title :
A Personalized Learning System with an AR Augmented Reality Browser for Ecosystem Fieldwork
Author :
Kasahara, Masao ; Takano, Kyoya ; Kin Fun Li
Author_Institution :
Grad. Sch. of Inf. & Comput. Sci., Kanagawa Inst. of Technol., Atsugi, Japan
Abstract :
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.
Keywords :
augmented reality; biology computing; ecology; feature extraction; learning management systems; mobile computing; recommender systems; user interfaces; augmented reality browser; augmented reality user interface; ecosystem fieldwork; ecosystem-related learning content; feature term set extraction; learning content recommender function; mobile learning tool; personalized learning system; user browsing behavior; Animals; Augmented reality; Browsers; Cameras; Databases; Ecosystems; User interfaces; augmented reality; e-Learning; ecosystems; mobile application; recommender systems;
Conference_Titel :
Advanced Information Networking and Applications (AINA), 2014 IEEE 28th International Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
978-1-4799-3629-8
DOI :
10.1109/AINA.2014.16
