Multimedia design for learning: An overview of reviews with meta-meta-analysis

Multimedia is ubiquitous in 21st-century education. Cognitive Load Theory and the Cognitive Theory of Multimedia Learning both postulate that the quality of multimedia design heavily influences learning. We sought to identify how to best design multimedia, and review how well those learning theories held up to meta-analyses. We conducted an overview of systematic reviews that tested the effects of multimedia design on learning or cognitive load. We found 29 reviews including 1,189 studies and 78,177 participants. We found 11 design principles that demonstrated significant, positive, meta-analytic effects on learning, and five that significantly improved management of cognitive load. The largest benefits were for captioning second-language videos, temporal/spatial contiguity, and signaling. We also found robust evidence for modality, animation, coherence/removing seductive details, anthropomorphics, segmentation, personalisation, pedagogical agents, and verbal redundancy effects. Good design was more important for more complex materials, and in system-paced environments (e.g., lectures) than self-paced ones (e.g., websites). Results supported many tenets of both theories. We highlight a range of evidence-based strategies that could be implemented by educators.

Developing an Analysis Framework for Studies on Pedagogical Agent in an e-Learning Environment

Pedagogical agents (PAs) are a crucial aspect of the e-learning environment. A PA is defined as a virtual character presented on an interface, and they are designed to promote student learning. PAs have been widely discussed in academic papers. However, an appropriate analysis framework has not been proposed because of the diversity and complexity of PAs. Therefore, we reviewed the literature and proposed a list of related clues, including environmental, learner, role, appearance, and social clues. We used this framework to analyse the learning effectiveness of PAs in specific areas. The keyword ‘pedagogical agent’ was used to search for related papers from 2000 to 2019. A total of 136 related papers were obtained. A meta-analysis was performed using a random effects model (Hedges’ g was used to measure the effect size). The effect size of the learning effectiveness of PA was small to medium (g = 0.423). The results of subgroup analysis (Hedges’s g) revealed that subjects, grades, additional support, appearance style, and facial expression changes had a different moderating effect on the effect of PA on learning effectiveness. We discussed the moderating effect of related clues and suggested future research directions.

The Design of WASPEC: A Fully Personalised Moodle System Using Semantic Web Technologies

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.