A Modular and Semantic Approach to Personalised Adaptive Learning: WASPEC 2.0

Abstract

The ubiquity of smart devices and intelligent technologies embedded in e-learning settings fuels the drive to tackle the grand challenge of personalised adaptive learning. Personalised adaptive learning, which combines the core concepts of personalised learning and adaptive learning, attempts to take individual needs and features into account for personal development through adaptive adjustment. Personalised adaptive learning is supported at its heart by efficient real-time monitoring of the learning process and robust managerial capabilities, which are driven by data, as well as human intuition. The absence of reusable personalised content and logic is one of the key limitations of systems that adopt personalised learning. This is mostly due to the fact that business logic is frequently entangled with the system’s primary functionality. As a result, such systems are unable to interact with other systems that do not adhere to identical design standards. The application of modular frameworks and the semantic web has the potential to be leading technologies that foster reusable personalised content and systems that can efficiently share information. WASPEC, a modular framework for personalised adaptive learning, is evaluated in this paper. An improved architecture, WASPEC 2.0, ensuring more flexibility is also presented in the concluding sections.