Please note some features of the review process, designed to increase the quality of both submissions and reviews as the conference grows.
Double-Blind Review Process
To maintain the technical quality of the conference as it continues to grow in size and variety, LAK19 is adopting double-blind review for all categories of submission, with the exception of the Doctoral Consortium (for which supervisor letters of support are required) and Demo Movies (software can be hard to disguise).
In double-blind review:
- Reviewers’ identities are not disclosed to authors, which LAK has always adopted. Moreover, reviewers will respect the spirit of the double-blind process, treating each submission on its own merits, and not seek to research the authors’ identities.
- Authors omit from their submission author names, affiliations, acknowledgements, and omit/disguise other details (such as URLs and project/product names) that may disclose identity. Do not eliminate self-references to your published work that are relevant and essential to a proper review of your submission. Instead, write self-references in the third person (e.g. “Previous work by Smith  has shown…”). The goal and spirit of double-blind review is to create uncertainty about authorship, which is sufficient to realize most of its benefits.
In order to develop an overview of research evidence in the field, we are once again aligning the EasyChair submission system with the LACE Evidence Hub. EasyChair will therefore ask whether your paper provides positive / negative / ambivalent evidence about four statements. These focus on whether learning analytics support learning, support teaching, are rolled out at scale and are applied ethically. We recognise that papers may not provide evidence in relation to any of these criteria and so your answers to these questions will have no influence on the review of your paper.
For an overview on the current state of the evidence, based on a review of the LACE Evidence Hub, see Ferguson and Clow (2017).