Personalisation in e-learning systems has become a major research area in recent times, as online learning is gradually evolving to become a major part of formal education. While there exist several learning management systems with a wide range of capabilities, one thing that remains inefficient is a standard framework for sharing knowledge across different platforms and, also, the inability of such systems to provide personalisation to the learning process by default. A large number of systems that have been implemented to provide personalisation apply few parameters and are course-specific; thus, flexibility, reusability, and scalability are greatly reduced. In this paper, we propose a framework for personalised learning, Weighted Agent System for Personalised E-learning Curriculum (WASPEC) implemented with Moodle, which is independent of the learning management system and provides the possibility of incorporating multiple personalisation parameters. This is accomplished with the combined use of web services, semantic web ontologies, and pedagogical agents, providing dynamic personalisation in the background of the e-learning system. This also provides added advantages of the possibility of sharing knowledge with other systems and reusability.
Personalised adaptive learning is becoming increasingly popular as a method of providing each student on an online platform with learning experiences that are tailored to their own requirements and peculiarities. This enables learners to go along many learning routes with the shared objective of information and skill development. In such systems, adaptivity and intelligence play distinct roles, with adaptivity being a more data-driven decision-making approach and intelligence being the emulation of human traits in a learning setting. Pedagogical agents, as defined in the field of artificial intelligence, are virtual characters with anthropomorphic features that are introduced for educational reasons. Because e-learning is a continuously growing area, the responsibilities of pedagogical agents change based on the goals that have been established for them. This article provides a systematic evaluation of pedagogical agents’ research and empirical data in e-learning from 2015 to 2022. Their responsibilities will be examined specifically in terms of flexibility and variety, realistic simulation, and their influence on learning: performance improvement, improved motivation, and engagement. The article finishes with a discussion and recommendations on pedagogical agents’ future directions in this ever-changing world of individualised adaptive e-learning.
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