Big data is not a wonder cure for productivity and economic growth in every sector. In some fields, such as education, big data, if applied the right way can drive forward innovation and new approaches. But educators have to go about this right way.
Big data solutions have generated a lot of hype and excitement over the last few years. It is – or was – seen as the answer to everything. Capable of generating trillions in new economic activity and opportunities. And then machine learning became a buzzword that soon attached itself to big data. Again, there was considerable hype around the potential impact of combining big data with machine learning, in education and dozens of other sectors.
As Macmillan Learning notes, gaining useful and reliable insights from educational data – big or small – is part science and part art.
In other words, you can’t take a whole load of data sources, a handful of questions, some software and maybe a data scientist or two, and hope for the best. Instead, let’s consider what schools and colleges hope to gain and how they can achieve an advantage through big data.
Challenges of applying big data in education
Comparable to other large organizations, schools and colleges are sitting on a lot of data. Internal and external data. Third-party structured and unstructured data. Extracting insights from all of this data starts with asking the right questions.
It also starts with identifying where big data can potentially play a role, and where any potential impact isn’t needed. Data in education is produced in high volume. It’s a high-velocity asset, with an enormous variety of outputs and formats. All of this makes it difficult to analyze and identify the actionable insights contained within.
One of the challenges – inherent in every big data project – is that most projects start with the necessity to clean the data. Often, whether organizations are dealing with legacy sources or multiple third-party datasets, there is a mismatch. Getting everything to align and work well together isn’t easy. Data scientists spend a lot of their time cleaning data and undertaking painstaking and time-consuming janitorial work.
Making it possible to extract useful value from complex datasets means ensuring they can interact. Whether this means through APIs or algorithms, or a partial manual implementation, the hard work is cleaning data enough so that sharing and interaction are possible. Once this is done, data scientists can work to extract the value an organization needs. Let’s look at what that can and could mean in the education sector.
How to apply big data in education
There are, of course, as many ways to apply big data in education as there are datasets and sources to mine and explore. In many cases, big data is part of an academic project. So for this, we will only look at ways big data can be used to improve the educational experience for students, or in some way potentially benefiting a university or school.
1. Evaluating student’s understanding
Educators are used to going with unconscious bias, or gut instinct when it comes to an understanding how well or not students are responding to learning materials and teaching styles. And yet, ultimately, how well someone understands a course has a noticeable direct impact on the learning outcomes.
If this could be addressed in real-time, using course material analytics within learning management systems (LMS), educators could adapt what they’re presenting more quickly, to the benefit of the students and the grades they produce.
2. Personalizing learning paths
Students often start courses with different levels of prior knowledge, different learning styles and different approaches. Educators can prepare as much as possible, but what if they had a way to adapt and tailor content more effectively? With more data about students before a course starts, coupled with real-time insights during a course, a tutor can create personalized learning paths around the needs of individual students. Grades and satisfaction scores should increase as a result.
3. Tailoring course content
Courses, such as business and marketing are created to help ensure graduates get jobs after college. Requirements are – or should – be tailored as much as possible for the real world. Giving students practical skills and knowledge they can apply in the world of work. At times, this means that the course content needs to adapt to a changing world, and tutors can do that more effectively when they can plug in new concepts, and adapt theory around the needs of students and employers.
Big data can be applied in the education sector in many ways. Some of the most impactful, for students and educators, involve using analytics insights to modify and improve courses, learning outcomes, learning pathways and the materials students use to gain qualifications.
