Big data: how is it impacting education?

**This is an updated article**

What is ‘big data’ and why does it matter? 

Big data is any very large data set that can be computationally analyzed to reveal patterns, trends, and insights about a specific user group or demographic. It can provide valuable insights and uncover trends.  

The importance of big data isn’t so much the volume, but how you use it.  

Typically, it is used as a predictive tool which can be used to anticipate human behavior, spot business trends, prevent diseases, combat crime, and perform other large-scale statistical assessments. 

How is big data being used in schools? 

In the business world, big data is used to iimprove operations, provide better customer service and create targeted marketing campaigns with the end goal of increasing profitability.  

In schools, big data is used to gather data on learning styles and outcomes, predict career paths, identify problem areas like unequal opportunity, and understand motivation. But how well does it really work as a tool for improving education? 

Schools shouldn’t be using it just for the sake of using it, but rather using it wisely and applying it where necessary.  

Useful applications include: 

• Simultaneously advancing and assessing student learning with machine learning algorithms 

• Continuously gauging performance 
• Identifying problem areas before tests are taken 
• Identifying students who are advancing faster than their classmates 
• Evaluating where students need deeper understanding or haven’t grasped concepts fully 
• Helping teachers decide when to spend more time on material or move on 

• Creating customized lesson plans and curricula for optimal educational outcomes 
• Reducing dropout rates 
• Recruiting specific types of students (if you’re a university) 

Many institutions are already making progress in improving outcomes by leveraging  big data in this way. 

Here’s a bit more about how big data is affecting these areas:

1. Improving student outcomes

Over the course of their educational career, each student leaves a unique paper trail of their learning data. Much of this is left behind unless schoolwork is saved. The main measure we have of progress is exams. But big data can help us keep track of a student’s educational career over time in order to improve overall outcomes, help her choose the right career, and optimize lifelong learning. Collecting big data in such a way can offer us insight into creating the right test questions and environment to enhance learning for each student.

2. Personalizing curricula

Big data can help educators create customizable curricula and programs based on feedback from machine learning algorithms. Leveraging a blended learning approach (both offline and online learning), these programs allow students to work at their own pace and pursue topics they are interested in. Massive online open courses (MOOCs), for example, provide educational opportunities to a much wider pool of students, allowing them to have more control over how and when they learn.

3. Encouraging advancement

Students advance through the school system based on their age. However, with the help of big data, teachers would be able to easily identify if a particular student is especially talented, and move them onto a more appropriate level of learning. With big data, students’ performance can be continuously evaluated.  

4. Reducing the dropout rate

Big data provides schools with predictive analyses to anticipate the likelihood of dropouts and to take action against it accordingly. Based on outputs like these, they can even predict how students might perform in a certain job market and readjust the student’s educational path to prevent dropout if, for instance, the data suggests the student would fare better in a different market.

5. Designing recruitment strategies

Educational institutions can use big data to anticipate how many students will apply, which student profiles may be most likely to apply, where there may be gaps in diverse representation, and more. Once schools are aware of which variables affect the application process, with the help of big data they can adjust their recruitment process accordingly. 

Want to learn more? 

You can visit the OC learning library or, if you’re interested in following a career in IT, you can take a look at our Certified Cybersecurity Professional course. This course will teach you the ins and outs of cybersecurity, so you’ll be ready to step into an entry-level position as a Cybersecurity Analyst. If you begin a career in cybersecurity, it will be part of your job to effectively protect and manage big data to ensure that it’s used for its intended purpose, and to prevent it from getting into the wrong hands.