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Data Science in education: how data is transforming schools

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Data Science is transforming the education sector, bringing it into the digital age. Discover the multiple possibilities offered by Big Data and AI for school systems, and why it's a prime field for Data Scientists.

The education sector generates large volumes of data. Schools, colleges and universities have at their disposal a vast amount of data on students through their school records, grades and results, or even their information sheets.

This data can be analyzed and exploited in numerous ways to open up new possibilities. In this way, Data Science and Machine Learning are helping to modernize the world of education.

How is Data Science transforming the education sector?

Data Science can be used in many ways in the field of education. Here are the main current possibilities.

Adaptive learning

Every student is unique. Everyone learns in a different way. This makes it very difficult, if not impossible, to choose an ideal method for all students in the same class. By using a uniform method, some will learn very quickly, while others will be “dropped” along the way and remain on the sidelines.

Big Data and Data Science enable teachers to use adaptive learning techniques. Depending on each student’s abilities and learning style, it is possible to choose personalized techniques optimized on an individual scale.

Informing parents

Student data can be analyzed to assess their performance. In this way, teachers can inform parents of any problems that may be affecting their children’s performance in different subjects.

Parents can then better supervise their children and monitor their activities. Similarly, this approach enables schools to take various initiatives to improve the education system and enhance the learning experience for students.

Teacher evaluation

School principals can use Data Science to better “monitor” and evaluate teachers. In particular, this enables them to check their methods, and identify which are the most effective.

The analysis of data such as student results, absenteeism rates or their own feedback can highlight the strengths and weaknesses of individual teachers. Teachers can then use the results as a basis for progress and improvement.

Improving student performance

By analyzing student data, we can assess their performance in depth, and improve it by taking appropriate action. Schools can make changes that benefit students, and help them solve their problems.

When a student’s grades deteriorate day by day, the teacher can use Big Data to identify the cause of the problem and help remedy it. Schools themselves can identify their weaknesses and find areas for improvement to maximize their students’ results.

Predicting student success

Data Science and Machine Learning can also predict a student’s success in a particular course or across all subjects. A system trained on data from previous students can determine whether a student is likely to fail or has every chance of succeeding.

It is therefore possible for AI to alert teachers if a student needs extra attention. The teacher can then create optimal learning conditions for each student.

In the same vein, Big Data also makes it possible to track how quickly students finish their tests. This means they can be given more or less time, depending on their real needs. If a course’s absentee rate soars, changes can also be made.

Helping students choose their path

The world of work is constantly evolving, but school curricula sometimes seem to stand still. As a result, the education sector can be “out of touch” with professional reality.

Data Science enables us to keep abreast of market trends, so that we can better prepare students for the future. Curricula can be updated based on data, and adapted to meet modern business requirements.technology to better guide those struggling to find their way…

Going a step further, artificial intelligence can even predict each student’s vocation. Based on the data, the system will be able to suggest that a student work in the industry or sector that best suits him or her. Guidance counsellors can therefore draw on this technology to better guide those struggling to find their path…

Attracting students

Private and public higher education institutions can use student data analysis to discover which programs captivate and interest students the most.

In this way, institutions can increase their attractiveness. Data Scientists can therefore help schools to better understand their students, and offer them infrastructures and teaching that meet their needs.

Data-driven decision-making

If a school decides to test a new teaching or assessment technique, it can turn to Data Science to verify its effectiveness. For example, these new methods can be tested only in certain classes, and their results compared with those of other students.

If results are up in the class where the method is being tested, and teachers see increased student engagement, it makes sense to generalize it. Data science can therefore help managers and teachers to make the best decisions for the greatest number of people.

Some examples of how Data Science is used in education

Around the world, many educational establishments are already using Data Science in their classrooms and administrations. Here are just a few examples.

The University of Florida uses Data Science to analyze student data. This makes it possible to monitor and predict student performance. The impact is tangible, as student grades have risen since the implementation of this method.

Georgia State University also uses Data Science and Machine Learning tools to discover insights in student data. This makes it possible to identify classes where students’ grades are not satisfactory. A support program was developed to remedy the problem and improve results.

Thanks to this system, the graduation rate rose from 32% in 2003 to 54% in 2014. In addition, student data is used to solve student retention or dropout problems.

Arizona State University, considered one of the best universities in the USA, is of course exploiting Data Science. The mathematics department has developed a system called “Adaptive Learning”, based on the analysis of student data.

This system collects a wide variety of data on students, such as their grades, strengths and weaknesses, and interests. If a student starts to encounter difficulties, teachers will receive a notification.

They can then take the appropriate concrete measures. Once again, this system has significantly improved student performance. In addition, the drop-out rate has fallen by 5.4%.

For its part, the University of Nevada collects and analyzes student data to identify trends. It can then offer a personalized experience to each student.

The challenges of Data Science in education

According to a study published by the Publications Office of the European Union, the main change brought about by Big Data in education relates to the possibility of monitoring and evaluating educational systems.

By analyzing student data, it is possible, for example, to check whether different courses are of interest to them. Courses, programs and assessments can be adapted and personalized to improve results.

However, the use of Big Data in education is still limited by several obstacles. First of all, the use of Data Science in this field can also pose an ethical problem. Student data can be considered personal, even intimate.

Yet some institutions go so far as to monitor students’ personal blogs in order to incorporate them into their analysis systems. It is therefore important that limits are set and that the use of data is supervised.

Furthermore, the immense volume of data generated by students is difficult to process. Education systems have neither the skills nor the tools to analyze it properly. There is therefore a strong demand for data science professionals.

In conclusion, data science offers many opportunities for educational establishmentsnaround the world. The various existing tools enable schools to improve the fruits of their teaching.

Big Data analysis can be used to monitor and improve student and teacher performance. However, to fully exploit the data, the education sector needs Data Scientists.

If you’re interested in this field, you can easily make yourself useful by offering your skills as a data science expert. To acquire these skills, take a Data Scientest training course with us.

Now you know how Data Science will transform the world of education. Find out how it’s being used in the healthcare sector, and discover the different professions involved in Big Data.

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