A Personalized Learning System with an AR Augmented Reality Browser for Ecosystem Fieldwork

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.

[1]  Elaine Lawrence,et al.  M-Fieldwork for Information Systems Students , 2008, Proceedings of the 41st Annual Hawaii International Conference on System Sciences (HICSS 2008).

[2]  Susan T. Dumais,et al.  Stuff I've Seen: A System for Personal Information Retrieval and Re-Use , 2003, SIGF.

[3]  Naiara Vicent,et al.  Mobile devices: a tool for tourism and learning at archaeological sites , 2012, Int. J. Web Based Communities.

[4]  Christophe Claramunt,et al.  An experimental virtual museum based on augmented reality and navigation , 2011, GIS.

[5]  Mariano Alcañiz Raya,et al.  E-Junior: a serious virtual world for natural science and ecology learning , 2009, Advances in Computer Entertainment Technology.

[6]  Maria del Carmen Juan Lizandra,et al.  Lessons learnt from an experience with an augmented reality iPhone learning game , 2011, Advances in Computer Entertainment Technology.

[7]  Djamel Fawzi Hadj Sadok,et al.  Context routing in heterogeneous pervasive computing fieldwork environments , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[8]  David R. Morse,et al.  Using while moving: HCI issues in fieldwork environments , 2000, TCHI.

[9]  Jonathan L. Case,et al.  P69 Using the NASA-Unified WRF to Assess the Impacts of Real-Time Vegetation on Simulations of Severe Weather , 2012 .

[10]  Teruhisa Hochin,et al.  On the Dissimilarity of Videos Considering Visibility for Similarity Retrieval of Plasma Videos , 2011 .

[11]  Han Yu,et al.  Mobile G-Portal supporting collaborative sharing and learning in geography fieldwork: an empirical study , 2007, JCDL '07.

[12]  Yasukawa Masaki,et al.  A Data Analysis Tool for Butterfly Monitoring , 2011 .

[13]  David Heckerman,et al.  Empirical Analysis of Predictive Algorithms for Collaborative Filtering , 1998, UAI.

[14]  Naokazu Yokoya,et al.  AR Cultural Heritage Reconstruction Based on Feature Landmark Database Constructed by Using Omnidirectional Range Sensor , 2010, ACCV Workshops.

[15]  Emanuela De Vita,et al.  SEARCHY: An Agent to Personalize Search Results , 2008, 2008 Third International Conference on Internet and Web Applications and Services.

[16]  James Pycock,et al.  Representing fieldwork and articulating requirements through VR , 1998, CSCW '98.

[17]  Yvonne Rogers,et al.  Enabling live dialogic and collaborative learning between field and indoor contexts , 2011, BCS HCI.

[18]  Paul-Alexandru Chirita,et al.  Personalized query expansion for the web , 2007, SIGIR.

[19]  David R. Morse,et al.  FieldNote: a Handheld Information System for the Field , 1999 .

[20]  I. Couzin,et al.  Emergent Sensing of Complex Environments by Mobile Animal Groups , 2013, Science.

[21]  Loriene Roy,et al.  Content-based book recommending using learning for text categorization , 1999, DL '00.

[22]  Maarten Vergauwen,et al.  3D Recording for Archaeological Fieldwork , 2003, IEEE Computer Graphics and Applications.

[23]  Yuichi Ohta,et al.  Visual support for medical communication by using projector-based augmented reality and thermal markers , 2005, ICAT '05.