Towards a Small-Scale Model for Ubiquitous Learning

The ever-increasing use of mobile devices allied to the widespread adoption of wireless network technology has greatly stimulated mobile and ubiquitous computing research. The adoption of mobile technology enables improvement to several application areas, such as education. New pedagogical opportunities can be created through the use of location systems and context-aware computing technology to track each learner’s location and customize his/her learning process. In this chapter, the authors discuss a ubiquitous learning model called LOCAL (Location and Context Aware Learning). LOCAL was created to explore those aforementioned pedagogical opportunities, leveraging location technology and context management in order to support ubiquitous learning and facilitate collaboration among learners. This model was conceived for small-scale learning spaces, but can be extended in order to be applied to a large-scale environment. Initial results were obtained in a real scenario, attesting the viability of the approach.

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

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

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

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

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

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

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

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

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

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

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

[12]  Mark Weiser The computer for the 21st century , 1991 .

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

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

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

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

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

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

[19]  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).

[20]  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).

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

[22]  Gregory D. Abowd,et al.  Towards a Better Understanding of Context and Context-Awareness , 1999, HUC.

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