CAFCLA: An AmI-Based Framework to Design and Develop Context-Aware Collaborative Learning Activities

Ambient Intelligence (AmI) promotes the integration of Information and Communication Technologies (ICT) in daily life in order to ease the execution of everyday tasks. In this sense, education becomes a field where AmI can improve the learning process by means of context-aware technologies. However, it is necessary to develop new tools that can be adapted to a wide range of technologies and application scenarios. Here is where Agent Technology can demonstrate its potential. This paper presents CAFCLA, a multi-agent framework that allows developing learning applications based on the pedagogical CSCL (Computer Supported Collaborative Learning) approach and the Ambient Intelligence paradigm. CAFCLA integrates different context-aware technologies, so that learning applications designed, developed and deployed upon it are dynamic, adaptive and easy to use by users such as students and teachers.

[1]  Guillermo Vega Gorgojo,et al.  Conceptual framework for design, technological support and evaluation of collaborative learning , 2009 .

[2]  Alexander De Luca,et al.  Please touch the exhibits!: using NFC-based interaction for exploring a museum , 2009, Mobile HCI.

[3]  Siobhán Clarke,et al.  An application framework for mobile, context-aware trails , 2008, Pervasive Mob. Comput..

[4]  Tzu-Chien Liu,et al.  Location-Based Adaptive Mobile Learning Research Framework and Topics , 2009, 2009 International Conference on Computational Science and Engineering.

[5]  HwangGwo-Jen,et al.  A context-aware ubiquitous learning environment for conducting complex science experiments , 2009 .

[6]  Juan M. Corchado,et al.  Agents and ambient intelligence: case studies , 2010, J. Ambient Intell. Humaniz. Comput..

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

[8]  Gwo-Jen Hwang,et al.  A context-aware ubiquitous learning environment for conducting complex science experiments , 2009, Comput. Educ..

[9]  Bertram C. Bruce.  Ubiquitous learning, ubiquitous computing, and lived experience , 2009 .

[10]  Robert E. Stake,et al.  Does Ubiquitous Learning Call for Ubiquitous Forms of Formal Evaluation?: An Evaluand oriented Responsive Evaluation Model. , 2009 .

[11]  Mike Joy,et al.  Survey on Context-Aware Pervasive Learning Environments , 2009, Int. J. Interact. Mob. Technol..

[12]  Juan M. Corchado,et al.  Ambient intelligence and collaborative e-learning: a new definition model , 2011, Journal of Ambient Intelligence and Humanized Computing.

[13]  Marlene Scardamalia,et al.  Computer-Supported Intentional Learning Environments , 1989 .

[14]  B. Cope,et al.  Ubiquitous Learning , 2011 .

[15]  Manuel Castro,et al.  M2Learn: Towards a homogeneous vision of advanced mobile learning development , 2010, IEEE EDUCON 2010 Conference.

[16]  Kevin Curran,et al.  Context-Awareness in Ambient Intelligence , 2010, Int. J. Ambient Comput. Intell..