Designing a Dynamic Network of Knowledge of Micro-learning Content

Imagine accessing a learning platform that presents a world of personalized and linked online learning resources - from free textbooks, in-depth blogs, videos, and podcasts - individually curated for your personal learning experience. These learning tools provide an opportunity to revamp traditional classrooms and enhance asynchronous experiences by identifying and dynamically adapting micro-learning content for each individual learner to elevate their learning journey and illuminate the significance of learning content. Our network science approach expands upon static repositories of instructor-curated content by systematially organizing that content into a Dynamic Network of Knowledge. We present the design through a base network model example representing linear algebra content that is freely available on the WWW. We extend the network to a dynamic model by systematically adding sets of content, and examining the resulting topological effects. This enables a generalized process from our example that can support potential generation of synthetic models for exploring further growth of such a network. The intended use of our network science approach is to bridge learning science concepts to foster adaptive & individualized learning in a meaningful way based on the introduced Dynamic Network of Knowledge content.