Learning Analytics Interoperability - a survey of current literature and candidate standards

The ease with which data can be transferred without loss of meaning from a store to an analytical tool whether this tool is in the hands of a data scientist, a learning science researcher, a teacher, or a learner – and the ability of these users to select and apply a range of tools to data in formal and informal learn ing platforms are important factors in making learn ing analytics and educational data mining efficient and effective. Th is paper describes, in summary form, the find ings of a survey into: a) the current state awareness and research or development into this problem of seamless data exchange between multiple software systems, and b) standards and pre-standardisation work that are candidates for use or experimentation.