ADA: A System for Automating the Learning Data Analytics Processing Life Cycle

Abstract

Learning analytics is an emerging field focusing on tracing, collecting, and analysing data through learners’ interactions with educational content. The standardisation of the data collected to supporting interoperability and reuse is one of the key open issues in this field. One of the most promising routes to data standardisation is through the xAPI: a framework for developing standard ‘statements’ as representations of learning activity. This paper presents work conducted within the context of the Institute of Coding (https://instituteofcoding.org/). Additionally, we have developed a system called ADA for automating the learning analytics data processing life cycle. To our knowledge, ADA is the only system aiming to automate the turning data into xAPI statements for standardisation, sending data to and extracting data from a learning record store or mongoDB, and providing learning analytics. The Open University Learning Analytics Dataset is used in the test case. The test case study has led to the extension of the xAPI with five new methods: (1) persona attributes, (2) register, (3) unregister, (4) submit, and (5) a number of views information.