Generally speaking, learning analytics refers to the collection and analysis of data about learners and their environments for the purpose of understanding and improving learning outcomes.

Learning analytics is where big data meets traditional quantitative methods in education. Governments, universities, testing organizations, and massive open online course providers are collecting data about learners and how they learn. All that data, however, has been mostly untapped until the fairly recent development of the methods and tools to do so.

Much of the data currently available does not come in neat, well-organized, and collected formats. It exists in varied forms across systems and locations. Analysts today need the skills to access and transform this data, so we can better understand not only what students know, but how they know it. Learning analytics and educational data mining are the tools to transform this data into knowledge and lead, in the end, to improved education.

How is Learning Analytics Used?

The Horizon Report: 2019 Higher Education Edition, produced by the EDUCAUSE Learning Initiative, identifies learning analytics as one of the digital strategies and technologies expected to enter mainstream use in the near future. As such, skilled data analysts are needed to support these analytics-driven initiatives and bring about institutional success.

“One of the driving forces behind the growth in the learning analytics field is that educational institutions are now facing the challenge of limited resources and increased accountability, which are propelling creativity and discovery,” says Melisa LaCroix, a database administrator and Northeastern University alumna. “The analytics programs that were once reserved for big businesses are now being widely used in higher education and K-12 institutions to measure student growth, inform curriculum decisions, and identify students at risk for failing a course or program.”

In addition to these practical uses of learning analytics, the practice is often used to:

Measure key indicators of student performance

Support student development

Understand and improve the effectiveness of teaching practices

Inform institutional decisions and strategy

“Having an analytics program in place is not a magical solution to educational challenges, however,” LaCroix notes.

Instead, any learning analytics initiative should be complemented by strong communication between the analyst and educators in order to successfully leverage the insights gleaned by the effort.

“To build a successful learning analytics program at an educational institution, it’s important to engage and inform school leaders, listen to the needs of teachers and students, and educate users on how to consume and act on the data that’s presented. Teachers and administrators will only be committed to data-driven decision making if they can see its value and are educated about how to turn insights gleaned from data into action.”

Impacting the Future of Education

Now is the time to enter the learning analytics field and make a difference in the education of current students and lifelong learners. To do so requires a solid foundational understanding of quantitative methods, combined with expertise in constructing, merging, managing, cleaning, and analyzing data using cutting-edge software and techniques.

https://graduate.northeastern.edu/resources/learning-analytics/