Learning analytics in support of video corpus construction and exploration

The OpenMWS project applies learning analytics to university students' engagements with the videos hosted on social media platforms. Part of the online MWSWeb platform for Higher Education, OpenMWS is a specialised interface for video corpus construction and analysis that functions as an overall pedagogical support for video-based investigations into multiliteracies. At a basic level, it currently provides sequence-based viewings for YouTube videos. It splits these videos into sequences by interpreting the instructions contained in two uploaded Excel files, the first an Overview file containing a list of YouTube videos, the second, a Transcript file, containing students' division of each video into time-based sequences that also include multimodal transcriptions and analyses of the characteristics of each sequence. A further level of engagement with videos is provided by tools for the online annotation of the each of the video sequences made available. The application of student-defined descriptors to these sequences creates a searchable corpus. Search tools then use these descriptors to identify sets of video sequences with similar characteristics. In this way, patterns are detected that highlight the presence (or absence) of specific sociocultural, methodological and genre features. Learning analytics help guide students through the various stages of corpus building. They also provide teachers and researchers with data about students' performance in the various tasks to be accomplished as well as indications of what additions and improvements are to be made to the individual corpora, and, more generally to the functionalities of the MWSWeb platform and its OpenMWS interface.