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Data Science encourages critical thinking in teenagers 


Unschooling

The benefits of integrating concepts of this field in secondary education and high school are already visible.

If you follow our news reporting on a weekly basis, you may have noticed our interest in conveying the importance of data in advancing commercial enterprises and eroding privacy, among other issues. But data science is more than just collecting and processing information.

Experts are now finding ways to use data science to improve students’ critical thinking skills.

Although it is one of the most attractive professions of the 21st century, Data Science is not taught at school. It can be learned in the university or through intense training courses. On many occasions, it is studied by professionals who have worked for years in other areas of knowledge.

The rise of this discipline, promoted in large part by a multisectoral demand of professionals that dominate the processing of vast amounts of information, responds to an important change in our organization as a society. However, a field that seems so transcendent has barely reached compulsory education.

What would happen if we put the data analysis in the center of mathematical education in the institute? What are the benefits of integrating concepts of this field in secondary education and high school?

Competition at young ages is always a motivator

Imagine a school in which 15 and 16-year-old students must demonstrate their competencies to understand data, manage spreadsheets and differentiate causality correlation. Exposing students to this technology and teaching them how to use data-based arguments can help develop their logical reasoning and foster their critical thinking.

By exploring this sector, they would be able to examine the operation of the real estate market by tracking data, for example. They would have a fantastic tool to learn by applying mathematics to real-world problems.

When solving concrete practical problems proposed by the science of data, mathematics ceases to be abstractions and they are truly understood.

Another alternative would be to take the science of data into the classroom to help educate citizens to read the news without being fooled by malicious graphics and data.

The treatment of data for the resolution of real problems and decision-making should be a basic transversal competence at all educational levels.

It is not necessary to create a subject for it; it is enough to introduce the perspective of data science in the different subjects that already exist.

Although mathematics and computing are essential for training in this area, within the framework of data science there are competencies that cannot be lost from our sights, such as creativity, teamwork and communication skills.

It’s about fostering a broad perspective where students understand that data plays a central role in solving real problems.

Math is more than just abstractions

Jo Boaler, professor of mathematics education at Stanford University, is one of the main defenders of an educational reform in this line. However, he admits that there are barriers that hinder the inclusion of this subject in the academic curriculum of adolescents.

“Teachers have not been trained in data science. On the other hand, institutes and universities tend to think that only calculation is important and that all roads should lead there,” he laments. “That is why awareness creation is so important.”

The lack of teacher training to delve into this discipline is one of the main challenges facing data science in its attempt to make part of schools’ curricula.

There are statistical concepts and mathematical models of numerical calculation that are not currently working and that would require major reform of the academic curriculum. In addition to mathematical knowledge, specific digital skills in languages ​​and programming tools are needed.

This implies that it would be necessary to reinforce the entire STEM area of ​​the secondary and high school training cycles and, for that, money is needed.

Aspects of data science can be studied through mathematics, computer science, and science, but teachers need additional skills to teach them. This would require the commitment of the government or relevant organizations to finance the professional development of teachers.

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About the author: Luis R. Miranda

Luis R. Miranda is an award-winning journalist and the founder & editor of The Real Agenda News. His career spans over 23 years in every form of news media. He writes about environmentalism, education, technology, science, health, immigration and other current affairs. Luis has worked as on-air talent, news reporter, television producer, and news writer.

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