Self Regulated Learning and Analytics - What can analytics tell us about how learners regulate their learning? - How can analytics help learners to better regulate their learning? Deadline for submissions: August 15, 2014 Anticipated publication date: March, 2015 Guest editors: Ido Roll, University of British Columbia Phil Winne, Simon Fraser University This special issue focuses on the use of analytics to study and support self-regulated learning, broadly defined. Topics include, and are not limited to, - Analytical and data-mining methods to study self- and co-regulation of learning - Development and evaluation of visualizations that help learners and researchers understand SRL - Evaluation of manipulations and platforms that seek to improve students’ self-regulated learning - Assessment and modelling of self-regulated learning The Journal of Learning Analytics is peer-reviewed, open-access, and is the official publication of the Society for Learning Analytics Research (SoLAR). With an international Editorial Board comprising leading scholars, it is the first journal dedicated to research into the challenges of collecting, analysing and reporting data with the specific intent to improve learning. It is expected that articles would be no longer than 10,000 words. Please see http://learning-analytics.info for additional information about the submission process. Please contact the editors with any additional questions.
Journal of Learning Analytics