Data-Header

Data.

It’s all around us. Each and every day we create an abundance of data simply by using our mobile phones and computers. This data is whizzed off into hyperspace, analysed and used to tailor content to our personal desires. There are many aspects that can be rendered into a data format, such as our location, the calories we consume, the exercise we complete each day or the websites we visit.

Educators have been using data for many years to analyse student results and see if they are meeting their academic needs, but with the advent of numerous technologies and the data that can be collected using such platforms teachers now have more sophisticated ways to monitor student progress.

Until now teachers have been limited in the ways that they can interpret data. Data is not merely a measuring stick, it is a way of climbing inside the minds of students to see not just what they learn, but how they learn it best.

You may have heard of personalised learning, and data-driven teaching is a way of fostering this movement. Just as you or I have different preferences in terms of food, students all learn in a different manner. Some respond to learning styles more positively than others. By drilling down data sets teachers can now tailor students learning experiences to their own individual needs rather than just sticking to a one-size-fits-all approach.

As an example, Mayer-Schönberger and Cukier (2014) illustrated how Professor Ng made use of student data to improve instruction to students.

In tracking the sequence of video lessons that students see, a puzzling anomaly surfaced. A large fraction of students would progress in order, but after a few weeks of class, around lesson 7, they’d return to lesson 3. Why?

He investigated a bit further and saw that lesson 7 asked students to write a formula in linear algebra. Lesson 3 was a refresher class on maths. Clearly a lot of students weren’t confident with their maths skills. So Professor Ng knew to modify his class so it could offer more maths review at precisely those points when students tend to get discouraged – points that the data alerted him to.

Although this example is not specific to an individual student, you can see how data trends can be utilised to meet students where they are, so they are not left behind or bored by the work being too easy.

What technology around us now also allows us to monitor is live student data. Instead of a snapshot of a students results at a particular point in time, resources such as Mathletics let teachers view live data of their students or classes for a powerful and visual comparison.

From here teachers can then identify the strengths and weaknesses of an individual student or even a whole class to create a truly tailored learning experience for the whole class.

It’s true, data is creating limitless possibilities for teachers and students alike. We’re already a part of the age of big data, it’s now time for educators to make the most of the tools available and use this data with precision to make the the most of its potential.

References

Mayer-Schönberger, V & Cukier, K 2014, Learning with big data: the future of education, Houghton Mifflin Harcourt, New York.