LA 2019 - 1st International Symposium Learning Analytics

Learning Analytics refers to the measurement, collection, analysis and reporting of data on the progress of learners and the micro and macro contexts of learning environment. It uses the data collected from the digital footprint of the learner and applies bigdata concepts to understand the influencing factors that affects learners whether it is educational policy and strategy, or it relates to the micro level module contents and its delivery. This has potential to support designing data and fact-based policy both for campus based and online delivery.
Through Learning Analytics, it is possible to provide tailor-made learning and teaching for a specific group. It can lead to reduce disparity of standard within different systems and optimise the resources required to achieve required standards. Learning Analytics can support the prediction of outcome and guide early intervention to boosting retention rates. It will make significant contribution for quality assurance.
When combined with refined visualization tools and suitable interfaces in an e-learning system, the use of Learning Analytics fosters a student-centred approach, supports self-regulated learning, and eventually helps learners (and teachers) along the road to educational success. This research area is witnessing swift developments since several years, and this Symposium aims to gather contributions to allow for exchange and further advancements. Technology Enhanced Learning advocates are invited to submit their original research work involving the use of Learning Analytics in education.The topics of interests include but are not limited to:
Learning & Teaching tracking
Temporal Analyses of Learning Data
Tool for quality assurance and quality improvement
Tool for boosting retention rate
Tool for adaptive learning
Tool to improve quality of teaching
Technical infrastructure
E-Learning
M-Learning
Game Based Learning
Personalized and Adaptive Learning
Learning analytics warehouse
Learning analytics processor
Alert and intervention system
Dashboards, and a student app
Machine & Deep-learning Analytics
Issues in Data Based Educational Theories and models
Educational Data Model
Data-based methodology for research in education
Ethics and privacy in learning analytic