Edge computing is often associated with autonomous vehicles, IoT devices, and industrial automation. But its applications are beginning to reshape digital learning environments as well. For eLearning professionals, especially those dealing with large-scale data and latency-sensitive applications like AR/VR , edge computing offers a compelling shift in how content is delivered, tracked, and personalized. In this article, we explore what edge computing is, how it differs from cloud computing, and what it means for eLearning speed, data accuracy, and learner experience. What Is Edge Computing? Edge computing is a distributed computing paradigm that brings data processing closer to the source of data generation—such as a learner's device or a local network node—instead of relying solely on centralized cloud servers. In eLearning contexts, this could mean processing a learner’s quiz results, xAPI statements, or AR/VR interactions locally before syncing with a Learning Management Sy...
The Power of Personalization in eLearning: Tools for Adaptive Learning Pathways In today’s fast-paced world, one-size-fits-all education models no longer meet the diverse needs of learners. Personalized learning has emerged as a transformative approach, offering customized experiences that adapt to individual learning styles, preferences, and progress. Adaptive learning pathways, in particular, are gaining traction for their ability to tailor eLearning experiences, maximizing learner engagement and retention. But what tools can help you create these personalized learning journeys? Let’s explore the power of personalization in eLearning and the tools that can enable adaptive learning. What is Personalized Learning in eLearning? Personalized learning tailors educational content, pace, and methods based on the unique needs and preferences of each learner. In an eLearning context, this means using data to modify the learning path, content presentation, and even the types of assessments pro...