The education landscape is shifting rapidly and with it the manner in which students learn. The latest generation of students—digital natives—is the most digitally connected of any previous generation. They’ve grown up on technology such as Facebook, Instagram, Twitter and YouTube composed of many social media avenues to communicate and share information about themselves, consume content and navigate through every part of their daily lives.
This trend naturally impacts learning as well. Over the last several years we’ve seen an explosion of digital content for learning. The rise of massive open online courses (MOOCs) and massive open online degree programs (MOODs) has opened up learning opportunities to the masses. Organizations such as the Kahn Academy and Kaplan University launch online learning institutions, and those institutions take off. Traditional brick-and-mortar elementary and secondary schools and higher education institutions also offer a range of online learning programs. This shift toward a heavy online focus begs the question: what is the best way for a student to learn?
Through data and analytics, education institutions can track enormous amounts of learning data. Traditional learning management systems such as the Design2Learn (D2L) platform track vast amounts of information that can shed light on student learning. By combining that information with other patterns we know about students, a clear picture of students’ preferred learning modes surfaces. Then, by applying deep analytics to the learning data, we can understand more clearly how a student learns.
Today, the potential of analytics-driven approaches to a personalized learning approach helps students learn at their own pace and consume content at a rate at which they are comfortable. And these approaches can free teachers and instructors to focus on those students who need extra assistance.