Supporting Place/Space Based Patterns of Citywide Mobile Learning through Multi-Agent Framework

There are numerous possible patterns consisting of learners, technological components and physical locations (i.e. Spaces) which can be identified in the context of citywide mobile learning (CML). By patterns, we mean to refer to the different ways in which learners are associated with the Spaces where the learning occurs, with technology that supports learning and among the learners themselves. Envisioning the entire set of possible scenarios, which can exist in the citywide context and designing to support them is not only difficult, but also practically impossible. Therefore, there is a need to condense and generalize all the numerous possible scenarios of CML into few core patterns, which can be use as basic building blocks to construct and support more complex CML scenarios. A regular trend in the currently existing literature is to consider only one or two use-cases while neglecting others. In this paper we address this problem by presenting six general patterns instead of use-cases that can exist in citywide context. These patterns take into account three fundamental aspects of CML, (1) learner, (2) Place/Space and (3) the technological components needed to support CML.