The increasing amount of data generated in digital learning contexts provides opportunities to benefit from learning analytics as well as challenges related to interoperability, privacy, and pedagogical and organizational models. As a consequence, new methodologies and technological tools are necessary to analyse and make sense of these data and provide personalized scaffolding and services to stakeholders including students, faculty/teachers and administrators, as well as parents. Pedagogical and organisational models must also be incorporated in order to take advantage of the personalized scaffolding and services to ensure productive learning and teaching. In addition, access to data from different sources raises a number of concerns related to data sharing and interoperability, and protection of privacy for individuals and business interests for institutions.
All accepted papers for mini-conference-style workshop will appear in one volume of workshop proceedings with ISBN and will be indexed by Elsevier Bibliographic Database. All paper should follow the paper format of the main conference.
All papers must be original and not simultaneously submitted to another journal or conference. The following paper categories are welcome:
We also welcome submissions on some of the topics concerning LA from the following (though not restrictive) list: