Context metadata to adapt Ambient Learning Environments

Pawlowski, Jan Μ.; Bick, Markus; Veith, Patrick

doi:10.1109/portable-polytronic.2008.4681275

Cited by 4 publications

(1 citation statement)

References 3 publications

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“…These needs are determined by the time, place, pace and context that best suits the individual learner. Ambient learning through the provision of content integration and composition allows access to, new e-learning material as well as existing catalogues/e-learning resources [18]. Although ambient learning is based on Ambient Intelligence Technologies (AmI) [19] its use is not only limited to rooms and buildings.…”

Section: Towards Using Mashups For Personal Learning Environmentsmentioning

confidence: 99%

Identifying Middlewares for Mashup Personal Learning Environments

et al. 2009

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The common understanding of e-learning has shifted over the last decade from the traditional learning objects portals to learning paradigms that enforces constructivism, discovery learning and social collaboration. Such type of learning takes place outside the formal academic settings (e.g., seminars or lectures) where a learning environment is created by using some kind of web application mashup tools. The use of these mashup tools moves the learning environment further away from being a monolithic platform towards providing an open set of learning tools, an unrestricted number of actors, and an open corpus of artifacts, either pre-existing or created by the learning process – freely combinable and utilizable by learners within their learning activities. However, collaboration, mashup and contextualization can only be supported through services, which can be created and modified dynamically based on middlewares to suit the current needs and situations of learners. This article identifies middlewares suitable for creating effective personal learning environment based on Web 2.0 mashup tools. This article also proposed a general framework for constructing such personal learning environments based on Ambient Learning realized by learning agents and the use of Enterprise Mashup servers

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Section: Towards Using Mashups For Personal Learning Environmentsmentioning

confidence: 99%