A Learning Analytics Platform Approach to Seamless Learning

Abstract

Learning takes place in a variety of different environments, both in-class as of formal learning and outside as informal learning. Seamless learning offers the opportunity to learn in different environments regardless of location or time. Students can benefit from learning in many contexts, and it can also provide insights for teachers into how learning is being conducted in informal situations outside the classroom. Previous work into the analysis of seamless learning has mainly focused on purpose build specialized systems that provide an environment for a specific task. In recent years, the field of learning analytics has been growing and learning environments are increasingly being developed across different modular systems that are linked together by standards-based protocols. In order to analyze seamless learning on a larger scale, this paper proposes the integration of an informal learning system, SCROLL, into a wider modular system. The proposed system addresses fundamental problems, such as the protection of user privacy and authentication while increasing the availability of data for analysis from other learning systems. We also examine the ability to analyze and visualize learning across numerous environments and contexts.