Learning Analytics Infrastructure for Seamless Learning

Abstract

Seamless learning offers the opportunity to learn in different environments regardless of location or time. 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. However, as the field of learning analytics matures, we are increasingly seeing the development of modular systems that can be linked together by standards based protocols. This paper proposes the integration of the SCROLL system into a wider modular system to increase the possibilities of seamless learning analytics to inform blended learning design. 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. Data is collected and stored centrally in a unified form that provides the ability to analyze and visualize learning across numerous environments and contexts.