Learning and Academic Analytics

go to link

In my previous blog posts I have discussed various technologies that are widely used in Educational institutions. Generally speaking, all these various technological tools help educators to improve the quality of education. In this blog post I will focus on big data and analytics which can help educational institutions to make data-driven decisions, predict the future of the institution and improve its performance.

According to Long and Siemens (2011), higher education is a field that contains a large amount of data about its learners and staff. Analyzing this data will help to get a clear picture of what is happening in that institution; it will help to identify the gaps or even predict and prevent the potential risks. In order to be able to analyze data effectively one needs to decide what he/she needs to know, what the specific type of data can tell you and also try to identify the patterns.

go to link

Next, it is important to identify between learning analitics and academic analytics. The former, is more specific than the latter. Learning analytics is the process of measuring, collecting and reporting information about learners in order to understand and improve the learning environment.

On the other hand, academic analytics is about using business intelligence in education at institutional , regional or international levels (Long & Siemens, 2011).

According to Goldstain (2005), present technologies help to analyse data effectively. As a result of a survey, the institutions that use academic analytics  report that it helps to make more effective decisions and to get a competitive advantage over other institutions.