Open Education Handbook/Open Data and Learning Analytics

Online education is producing vast amounts of data about students. Much of these online courses are openly available and the data from them should be too. The data will enable academic institutions and course providers to deliver their courses more efficiently and more appropriately to their students. It will also allow students to personalize their educational experience to best suit their needs. Data collected can include administrative data, demographic information, grade information, attendence and activity data, engagement metrics, course selection etc. Learning analytics is defined as the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs. Data from online courses can: Enable grade prediction and student success Improve student retention Determine what learners know and what they currently do not know Monitor learner engagement Personalize learning Ensure relevant content is delivered Reduce classroom administrative work Measure student performance Have other uses yet to be discovered Open data can support students: Through creation of new tools that enable new ways to analyse and access data e.g. maps of disabled access, tools for disciplines By enriching resources, making it easier to share and find them, and how to personalize the way they are presented By allowing student to explore resources, concepts, ideas and objects in various areas To make informed choices on education e.g. by comparing scores, course data etc. Open data can support education institutions: Learning analytics data can help retain students Use data can enable efficiencies in practice e.g. library data can help support book purchasing Benchmarking and performance measuring Providing real world examples for learning