| Abstrakt: |
Ubiquitous learning environments move learners out of a classroom and into the real world where learners engage in experiential and tangible learning involving instrumented physical things. Learners use peer-to-peer networks connecting learners, teachers, and a host of learning “things,” such as instrumented pieces of art, flower pots, and even buildings. A key component of such systems is wireless-enabled edge devices augmented with various types of sensors to represent the state of physical things and their context. This article presents a novel generic architecture for context-aware ubiquitous learning systems based on the Internet of Things (IoT) computing paradigm. A commonly used IoT edge device was used to implement four variants of the proposed architecture. The variants were based on advanced message queuing protocol, constrained application protocol (CoAP), message queue telemetry transport, and extensible messaging and presence protocol. All variants provided more than adequate performance for implementing ubiquitous learning scenarios. As expected, CoAP was generally more resource-efficient. However, practical differences in performance were so small that the choice of which architectural variant to use may depend on nonfunctional requirements such as reliability, security, maximum payload size, and ease of implementation. [ABSTRACT FROM AUTHOR] |
