Ontology-based approach for the validation and conformance testing of xAPI events

Learning analytics (LA) looks for a better understanding of learning and ways to optimize both the learning and the environments in which it occurs. One of its key research areas is focused on data interoperability, specifically on how to collect and store learning data. Proprietary systems usually store data in their own unique format and thus make difficult to reuse LA solutions. Some approaches have appeared in the last years to overcome this issue and the Experience API (xAPI) has been the most successful in this area, primarily because of its transversal approach not tied to any Learning Management System (LMS). However, the xAPI specification is informal, with some loose definitions, that may lead to unexpected mistakes. In order to avoid ambiguity, in this paper we present an xAPI ontology that captures the concepts and semantics of the specification, and has been validated with two datasets of the xAPI community. In addition, a web client has been developed to provide a validation tool that can check the correctness and conformance of individual xAPI files as well as complete xAPI datasets.

keywords: Experience API, Ontologies, Ontology validation, Conformance testing