An Adaptive Semantic Annotation Tool for Teachers Based on Context-Aware and Internet of Things

Abstract

Annotation has demonstrated its importance in several areas, notably in the modeling of annotation activity in the automation and adaptation phase. However, the context sensor is commonly manual or semi-automatic. The use of the Internet of Things with annotation gives a qualitative leap in the field of higher education and universities. In this field, teachers, during their pedagogical activities, require more information found in different textual documents, tools, and databases. In addition, they organized several meetings and took considerable time to make appropriate and right decisions during the deliberation process. In this paper, we propose an adaptive annotation tool based on the Internet of Things addressed for teachers during their educational tasks. The presented tool automatically adapts according to the context of the teacher’s tasks and it enables the annotation of all documents written in different languages. To consider all the parameters of the teaching activities when interfacing with the annotation and to give the useful information for teachers during decision-making, we have adopted an architecture based on the ontology of context and the multilingual ontology of deliberation and redemption. To implement this tool, we used Semantic Web and Internet of Things technology to achieve the desired architecture. Likewise, the usability of the proposed annotation tool has been tested with a real case in coordination with teachers and administrators during the deliberation operation to decide to rescue and redeem students at the university.