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...
Gen Z —the first generation of true digital natives—has reshaped expectations around how learning content should be delivered. Born between the mid-1990s and early 2010s, this generation grew up with smartphones, high-speed internet, and on-demand information. Traditional instructional design models, while still relevant, must adapt to meet their cognitive and behavioral preferences. In this article, we explore strategies, tools, and platforms that align with the expectations of Gen Z learners in today’s eLearning environments. Understanding Gen Z’s Learning Preferences Before developing content strategies, it’s important to recognize the characteristics that define Gen Z as learners: Visually-driven : Video and multimedia play a critical role. Mobile-first mindset : Most learning is consumed on smartphones or tablets. Short attention spans : Content needs to be concise and interactive. Autonomous learners : They value self-paced learning and flexible pathways. Social...