Publication

Abstract : When MultiModal Learning Analytics (MMLA) are applied in authentic educational scenarios, multiple stakeholders (such as teachers, researchers and developers) often communicate to specify the requirements of the envisioned MMLA solution. Later on, developers instantiate the software solution for the MMLA data processing needed, as per the stakeholders’ specification, to fit the concrete setting of implementation (e.g., a set of classrooms with a certain technological setup). Current MMLA development practice, however, is relatively young and there is still a dearth of standardized practices at different phases of the development lifecycle. Such standardization may lead to interoperability among solutions that the current ad-hoc and tailor-made solutions lack. This chapter presents the Contextualized Data Model for MultiModal Learning Analytics (CDM4MMLA), a data model to represent, organize, and structure contextualized MMLA process specifications, to be later used by MMLA solutions. To illustrate the model’s expressivity and flexibility, the CDM4MMLA has been applied to three authentic MMLA scenarios. While not a definitive and universal proposal yet, this kind of common computer-interpretable models can not only help in specification reusability (e.g., if the underlying processing technologies change in the future), but also serve as a sort of ‘lingua franca’ within the MMLA research and development community to more consistently specify its processes and accumulate knowledge.