Interoperability Standards for Adaptive Instructional Systems: Vertical and Horizontal Integrations

Abstract

Adaptive instructional systems (AISs) – tools and methods that tailor each student’s instructional experiences to their needs within a set of domain learning objectives – are becoming increasingly common. In an ideal configuration, AISs work in concert using open interoperability standards to provide a seamless experience for students and instructors, while leveraging high-frequency contextual data to inform the learning flow. With the large amount of learning interactions that can take place in AISs, however, existing industry standards are unable to support the interoperability and extensibility of components within an AIS and among different AISs. In this paper, we propose extensions on top of current industry standards to enable interoperability among components within an AIS. We also discuss the need of interoperability standards across different AISs on the learning ontology and data models, and the opportunity to leverage recent advances in federated machine learning to enable horizontal integration across separate AISs.