Big data is offering us the opportunity to look at things we could only guess at before. This allows us to look at things from new angles, study them in ways that were impossible just a few years ago and get new insights that we didn’t even know where out there. In this way it is changing almost every industry it’s touching, like healthcare, logistics and “ yes “ education.
The thing about education is that because it’s quite a conservative industry, many of the changes are still on the horizon. That means that we’re going to see some dramatic changes over the next few years that will transform the industry dramatically. Here we’re going to explore some of those changes and ramifications so that you can see which way the tide is flowing. That will let you make informed decisions and stay ahead of the curve.
It allows us to recognize problems earlier
In traditional teaching atmospheres, children could often struggle in silence for months before the problem really manifested. By that time, they were often so far behind that it made it incredibly difficult for the student to catch up again. It would often take serious help from the teachers, the parents, and even tutors.
And often “ in for example mathematics “ the culprit was that they didn’t understand one step along the way.
Now, with big data, that’s changing. Big data can analyze the patterns in data to identify people who are struggling much earlier. This will allow the teachers to immediately see the problem and in that way step in before the problem had advanced too far. In this way, through only a small amount of effort, teachers can correct the student’s path and make sure that the problem is fixed long before it becomes insurmountable.
Rethinking teaching methods
Did you know that Finland has just scrapped subjects? Instead, they will be replaced by interdisciplinary topics that cover what you will need in particular situations. So, for example, you might not learn math, history or geography, but will instead study the topic of the second world war, which will deal with all three.
We will no doubt see more countries move this way soon, goaded on by statistical models that let us realize how subjects are not “ in fact “ separate branches on the tree of knowledge, but instead are integrated into a unified whole.
This will accelerate further in the years to come as big data crunches over the results of these experiments and allows us to fine tune what ideas do work and where students end up struggling. Then, in a few years or decades, the traditional idea of subjects will be considered just as antiquated as hitting our students with rulers.
Engagement
It is in fact only by applying data algorithms to classes that we now know how important engagement is in classes, as it allows students to learn more effectively and concentrate for a great deal longer.
But big data isn’t stopping there. Now that we understand the importance of engagement, we can start studying in which ways we can really engage students with subjects, rather than the veneer (like gamification) on top. From there, we can then refine the ways we teach until almost every single student thinks it’s an absolute joy to go to class.
And when that’s the case, we’ll know we’re getting closer to teaching at an optimal level.
Comparison of teaching methods
In a similar way, big data is allowing teachers to objectively evaluate if how they’re teaching a topic is actually the best way to do so. Often, some teachers are better in teaching certain aspects of the curriculum and worse elsewhere. The thing is until big data came along, it was hard to know which was which.
That often made it a shot in the dark to know what teaching methods each teacher should adopt from another. That’s no longer the case. Now it is possible through the comparison of scores across classes on things like tests and quizzes to see what subject teachers excel at teaching and where they can use a helping hand.
From there, it then becomes a simple matter for teachers to compare notes, discuss what they do differently and change things up so that they become better teachers and their courses become better at imparting the knowledge the students need.
Guiding students
Another big area where we’ll see changes is in guiding students towards the best choice for them for continued education. As thing are, students are often left struggling in the deep end, to figure out what they should do. Should they go to university, seek out an apprenticeship or go directly into the workforce? If they do continue on, what courses should they consider taking and what should they major in?
Big data can play a hugely beneficial role here, by combing over their results, comparing them to other students and seeing what students excelled best in what environments and thereby can offer reviews of companies and universities that the student might want to attend. From there they can make suggestions about what would be the best fit the student.
Naturally, the student is free to take or leave the suggestion, but just having this offer will make it a great deal easier for them to make decisions about in which direction they want to head. Even better, it might highlight opportunities that they themselves might never have come up with or didn’t even know existed.
Guiding universities
In a similar way, computers can help universities select the students that will do best on their campuses. There are several reasons why algorithms will do this better than people can. For one thing, people can only consider a few variables at a time and will struggle to compare them to each other correctly, with them overweighing some dimensions and underweighting others.
Similarly, people have a lot of implicit biases. These mean that dimensions that shouldn’t even be considered (like the person’s sex, race or religion) might still figure into their decisions. This will not happen with an algorithm (unless it is programmed to do so). Instead, the algorithm will look only at the data that is significant, like grade scores, extra circular activities, test scores and the applicant’s stated values and preferences. That will create a fairer system for everybody and allow people to get into the university of their choice based on merit, rather than somebody’s preconceptions.
Analyze without preconceptions
When you’ve got a hammer, the whole world looks like a nail. This is true in all disciplines, including the analyses of what works best in schools. People have all kinds of ideas about how schools should work and why this idea is better. Sure, some of those ideas are based on a great deal of research. But not all of them. Some of them are just ideas that we’ve taken over from others without any actual proof.
The problem is, we often don’t know the difference between the one and the other. The point of preconceptions is that we’re often blind to them.
An analysis of big data doesn’t have this problem. There the computer is allowed to make the connections that the data suggests, rather than what it believes is right and correct. In this way, big data can reveal problems and solutions that might not have occurred to human researchers. And in that way, it might offer new opportunities that today we’re not even aware of yet “ like doing away with courses like they’ve done in Finland.
Last words
Big data has already changed the world a great deal. And it’s only just getting started. There are a lot more opportunities for big data, particularly as more and more sensors (the internet of things) come online, letting us measure new things that today we can only guess at.
This will allow us to change the world in ways that we can only imagine and thereby reform education so that it is more engaging, more informative and more effective. This is essential, as today’s world is becoming ever more information based and the only way that we can prosper as individuals, as well as countries, is by receiving an education that is both capable of teaching us the facts, as well as how to learn for the rest of our lives.
Big data offers us that opportunities and is therefore a truly exciting opportunity “ particularly for those that are being left behind’ by our modern ways of teaching.
What that means is that the predictions we’ve made here are only the tip of the iceberg. We’re going to see changes and developments in the next few years none of us predicted. And that, to my mind, is probably the most exciting thing of big data. How cool is it that we’re going to discover new ways of doing things and possibly entirely new fields of knowledge that we’ve entirely overlooked so far?
