Situated learning theory and geo-collaboration for seamless learning

Abstract

Situated learning stresses the importance of the context in which learning takes place. It has been therefore frequently associated with informal learning or learning outside the classroom. Therefore, this theory offers an excellent basis for developing applications supporting collaborative learning activities implementing seamless learning. In this chapter, we present and analyze two applications designed with the principles of situated learning, which implement learning activities taking place inside and outside the classroom without interruptions of either learning methodology or technical platforms. The first one supports the learning of models for wireless signal propagations. It starts with a classroom activity for learning the theoretical models, and then a field trip is used to measure actual signal strengths and compare them with the data generated by the models. The second one is a learning system and a methodology based on the use of patterns. Students learn about patterns by finding instances of them in the field or by recognizing new patterns unknown to them so far. The teacher proposes tasks to the students consisting of finding instances of patterns or discovering new ones along a path or inside a predefined area on a map. Both systems support the features of seamless learning across various scenarios in and outside the classroom, due to the encompassing formal and informal learning, personalized and social learning, physical and virtual worlds, across time and location, and ubiquitous knowledge access by contextaware in real learning scenarios.