Smartwatches for Context-Aware Ubiquitous Learning

Abstract

Context-aware ubiquitous learning systems use real-time or almost real-time sensor data that is an integral part of learning design for anytime, anywhere learning. Typical examples are situated learning in museums, parks, or gardens where sensors are used to enact unique learning scenarios. This type of embedded learning can be easily extended to cities, continents, or indeed the world. Traditionally, PDAs and smartphones have been used as edge devices in such learning systems; smartphones or PDA’s typically collect sensor data and communicate with back-end servers to enact learning scenarios. Smartwatches can easily replace smartphones to perform these functions. Smartwatches today include a variety of sensors, are wirelessly connected to heterogeneous networks, and possess significant processing power. This paper presents a survey and design framework for using smartwatches in ubiquitous learning. The design framework views smartwatches for ubiquitous learning through the IoT lens and various types of learning designs. In addition, micro-services to implement these pedagogical services are enumerated and evaluated with respect to smartwatches. An analysis of network requirements for smartwatches is also presented. The overall conclusion is that while some challenges like power optimization remain, smartwatches represent a promising next platform for context-aware ubiquitous learning.