An Architecture for an Adaptive and Collaborative Learning Management System in Aviation Security

Abstract

The importance of aviation security has increased dramatically in recent years. Frequently changing regulations and the need to adapt quickly to new and emerging threats are challenges that need to be addressed by airports, security companies and appropriate authorities across the world. Learning management systems (LMS) have been developed as effective tools for enhancing the management, integration and application of knowledge in organizations. In the aviation security domain, we need mechanisms to quickly adapt to new learning content, to different roles ranging from screeners to supervisors, to flexible training scenarios and solid job assessments. For that, a learning system has to be flexible and adaptive both in knowledge, organizational and in collaboration dimensions. Current LMS do not meet these requirements. In this paper we present a software architecture that is apt to support the adaptability and collaboration needs for such a system in aviation security. We discuss the requirements, roles, learning objects and course configuration in terms of adaptive and collaborative learning. We present a six-layer architecture and discuss some of its application scenarios. Our aim is to improve the quality and usefulness of LMS in aviation security by utilizing knowledge-based analysis for data analysis and integrating a process engine for collaborative learning. We briefly report on our prototype and the gained first feedback from the users.