Academic analytics Essay Example | Topics and Well Written Essays - 1000 words

Academic analytics - Essay Exampleadley review acknowledges that benchmarking activities such as student engagement serve as indicators for gauging the institutions quality (Commonwealth Government of Australia, 2008).Increased competition, accreditation, assessment and regulation are the major factors encouraging the adoption of academic analytics in institutions of high learning. Although institutions of higher learning gather a lot of vital data that can significantly aid in solving problems like attrition and retention, the collected data is not being analysed adequately and hence translated into useful data (Goldstein, 2005.) Subsequently, higher education leadership are forced to make critical and vital decisions establish on inadequate information that could be achieved by properly utilising and analysing the available data (Norris, Leonard, & strategic Initiatives Inc., 2008). This gives rise to strategic problems. This setback also depicts itself at the tactical level. Lea rning and teaching at institutions of higher education if often a diverse and complex experience. Each and every teacher, student or course is quite different. However, LMS is tasked with taking care of them all. LMS is at the centre of academic analytics. It records each and every student and staffs information and results in a click at heart the system. When this crucial information is added, compared and contrasted with different enterprise information systems provides the institution with a vast array of useful information that can be harvested to gain a competitive edge (Dawson & McWilliam, 2008 Goldstein, 2005 Heathcoate & Dawson, 2005).In order to retrieve meaningful information from institution sources i.e. LMS, the information has to be correctly acted against a basis of educational efficiency, and this action requires thorough analysis from people with learning and teaching skills. Therefore, a collaborative approach is required from both the people guarding the data an d those who will interpret