Semantically Annotated Learning Media for Reduced Cognitive Load

Abstract

The use of Semantic Web in education has become more significant in recent years. A topic that has received less attention to date is the use of such technologies for supporting special educational needs (SEN). Semantic annotation is now one of the challenges for building the semantic web and dealing with all the different data that exist on the web such as text, pictures or media. Research tries to annotate educational web resources with concepts and relations from explicitly defined formal ontologies. This formal annotation is usually created manually, semi-automatically or automatically. The Semantic Web initiative has had an impact in the educational field and offers potential support for better understanding of learning content. This paper presents an augmented World Wide Web (WWW) vision utilising annotation to more effectively support special educational need students. Students are supported in part by a SEN Teaching Platform (SENTP). This platform is designed with additional support for cognitive load using specific annotation formats within the Amaya annotation tool and coordinated with web application. We present details of the SENTP structure, design and practically how this SENTP is implemented for a poetry topic in literacy lesson. The potential of our approach has been confirmed by a positive user evaluation building on field-testing study at seven UK schools and interviewing twenty-three participants. The findings indicate that applying cognitive load principles to annotated content can improve both learning and class behaviour.