A ubiquitous learning model focused on learner interaction

Ubiquitous learning refers to learning supported by the use of mobile and wireless communication technologies, sensors and location/tracking mechanisms, that work together to integrate students with their environment. In this paper, we present a ubiquitous learning model called location and context-aware learning (LOCAL). The model is self-sufficient since it does not require complement of an ubiquitous middleware. Moreover, LOCAL uses location information and learner profiles in a generic approach, it was not designed to any specific kind of learning application. The main goal of the model consists in stimulating interaction among learners. The model was implemented and the initial results attest its usefulness. Two functionalities tests proved that LOCAL can be used to stimulate the learner interaction and to distribute contextualised learning objects. In a third test, LOCAL usefulness was positively evaluated by 20 individuals of a computer engineering undergraduate course.

[1]  Débora Nice Ferrari Barbosa,et al.  Globaledu - An Architecture to Support Learning in a Pervasive Computing Environment , 2005, EDUTECH.

[2]  Gaetano Borriello,et al.  Location Systems for Ubiquitous Computing , 2001, Computer.

[3]  Débora Nice Ferrari Barbosa,et al.  Context-Aware Model in a Ubiquitous Learning Environment , 2007, Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PerComW'07).

[4]  Débora Nice Ferrari Barbosa,et al.  Learning in a large-scale pervasive environment , 2006, Fourth Annual IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOMW'06).

[5]  Martin V. Butz,et al.  Advanced Distributed Learning , 2012 .

[6]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[7]  James H. Aylor,et al.  Computer for the 21st Century , 1999, Computer.

[8]  Matthias Baldauf,et al.  A survey on context-aware systems , 2007, Int. J. Ad Hoc Ubiquitous Comput..

[9]  Débora Nice Ferrari Barbosa,et al.  A management model of learning objects in a Ubiquitous Learning environment , 2010, 2010 8th IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops).

[10]  Pedro Merino,et al.  Mobile Application Profiling for Connected Mobile Devices , 2010, IEEE Pervasive Computing.

[11]  Mahadev Satyanarayanan,et al.  Fundamental challenges in mobile computing , 1996, PODC '96.

[12]  Andreas Schmidt.  Potentials and Challenges of Context-Awareness for Learning Solutions , 2005, LWA.

[13]  Jorge L. V. Barbosa,et al.  Mobio threat: A mobile game based on the integration of wireless technologies , 2008, CIE.

[14]  Jorge L. V. Barbosa,et al.  A Framework for the Design of Ubiquitous Learning Applications , 2009, 2009 42nd Hawaii International Conference on System Sciences.

[15]  Yvonne Rogers,et al.  Ubi-learning integrates indoor and outdoor experiences , 2005, CACM.

[16]  Deborah Estrin,et al.  GPS-less low-cost outdoor localization for very small devices , 2000, IEEE Wirel. Commun..

[17]  Wolfgang Nejdl,et al.  Elena: A Mediation Infrastructure for Educational Services , 2003, WWW.

[18]  Eyal de Lara,et al.  Location-Based Services , 2010, IEEE Pervasive Computing.

[19]  Hiroaki Ogata,et al.  Supporting Awareness in Ubiquitous Learning , 2009, Int. J. Mob. Blended Learn..

[20]  Débora Nice Ferrari Barbosa,et al.  Mobile and ubiquitous computing in an innovative undergraduate course , 2007, SIGCSE '07.

[21]  Sandeep K. S. Gupta,et al.  Smart classroom: Enhancing collaborative learning using pervasive computing technology , 2003 .

[22]  Stephen J. H. Yang,et al.  Context Aware Ubiquitous Learning Environments for Peer-to-Peer Collaborative Learning , 2006, J. Educ. Technol. Soc..

[23]  R. Likert.  “Technique for the Measurement of Attitudes, A” , 2022, The SAGE Encyclopedia of Research Design.

[24]  Steven J. Vaughan-Nichols,et al.  Will Mobile Computing's Future Be Location, Location, Location? , 2009, Computer.

[25]  Hiroaki Ogata,et al.  Supporting the acquisition of Japanese polite expressions in context-aware ubiquitous learning , 2010, Int. J. Mob. Learn. Organisation.

[26]  Débora Nice Ferrari Barbosa,et al.  Learning in Small and Large Ubiquitous Computing Environments , 2008, 2008 IEEE/IFIP International Conference on Embedded and Ubiquitous Computing.

[27]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[28]  Nicolas Spyratos,et al.  SeLeNe Report: Metadata Management and Learning Object Composition in a Self eLearning Network , .

[29]  Paramvir Bahl,et al.  The Case for VM-Based Cloudlets in Mobile Computing , 2009, IEEE Pervasive Computing.

[30]  Hiroaki Ogata,et al.  Computer Supported Ubiquitous Learning Environment for Vocabulary Learning Using RFID Tags , 2004 .

[31]  Gregory D. Abowd,et al.  Charting past, present, and future research in ubiquitous computing , 2000, TCHI.

[32]  Ichiro Satoh,et al.  Modeling and Processing Information for Context-Aware Computing: A Survey , 2009, New Generation Computing.

[33]  Jorge L. V. Barbosa,et al.  ISAM, Joining Context-Awareness and Mobility to Building Pervasive Applications , 2004, Mobile Computing Handbook.

[34]  Anthony LaMarca,et al.  Practical Lessons from Place Lab , 2006, IEEE Pervasive Computing.

[35]  Mahadev Satyanarayanan,et al.  Pervasive computing: vision and challenges , 2001, IEEE Wirel. Commun..

[36]  Cheolho Yoon,et al.  Convenience and TAM in a ubiquitous computing environment: The case of wireless LAN , 2007, Electron. Commer. Res. Appl..