Opening Learner Profiles across Heterogeneous Applications
Triomphe Ramandalahy, Philippe Vidal, Julien Broisin · 2009
The more learner information is shared across a wide range of heterogeneous applications and tools, the more learner profiles will be relevant, reusable and useful for many systems and environments. This proposal stands on a widely used management standard, and introduces an open and generic learner profile supported by a service-oriented architecture ensuring exchange and reuse of learner information. The profile is characterized by (1) a core model integrating the LIP standard but also some metacognitive properties, and (2) a high abstraction level offering the possibility to extend the core model. The architecture facilitates sharing and reusing of learner profiles while providing scalability. Two use cases are presented and demonstrate (1) how heterogeneous applications can transparently collaborate to strengthen shared learner profiles, and (2) how resulting profiles can easily be consulted and extracted for further exploitation.