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...
In today’s data-rich eLearning environments, dashboards have become essential tools—not just for tracking learner progress, but for informing strategic decisions. When built thoughtfully, a learning analytics dashboard does more than display numbers—it tells a story, uncovers insights, and empowers stakeholders to take meaningful action. In this article, we explore how to design dashboards that move beyond passive data presentation and truly drive outcomes for instructors, administrators, and organizational leaders. Why Learning Dashboards Matter The growth of xAPI, SCORM, cmi5, and Learning Record Stores (LRS) has made it easier than ever to collect granular learning data. However, the real value lies in how that data is used. Dashboards that simply report completion rates or test scores are no longer enough. Today’s stakeholders need: Real-time insights into learner performance Correlations between training and business outcomes Early-warning systems for disengaged lear...