Information and digital literacy in education via the digital path

Throughout higher education, institutional learning analytics are inspiring interest and gaining traction as an exciting new strategy for improving college student experiences and success. Together with information technologists and institutional research, effectiveness, and assessment experts, faculty from curricular departments and student support professionals from co-curricular units are using data to assist students and enhance learning environments on our campuses. This effort to make a difference in students’ lives encompasses nearly all areas of the academy.

nternet users leave combined data trail of over 2.5 billion gigabytes a day. That’s a staggering amount of information, and it’s information that can tell us a lot about our futures.

Predictive World is a tool combining big data, demographic information and personalized data to give a creepily accurate look at your life, including what’s to be expected for your future.

You’ve been gathering analytics, reports, and eLearning feedback for weeks, or even months. The next step is using all of that data to plot your next course of action and streamline your eLearning strategy. In this article, we’ll share 7 tips on how to effectively manage and analyze big data in eLearning.

Big data has arrived in education. Educational data science, learning analytics, computer adaptive testing, assessment analytics, educational data mining, adaptive learning platforms, new cognitive systems for learning and even educational applications based on artificial intelligence are fast inhabiting the educational landscape, in schools, colleges and universities, as well as in the networked spaces of online learning.

Big Data is described as the huge sets of electronic data that is available for analysing, whereas Analytics, according to Wikipedia, is "the discovery and communication of meaningful patterns…