Why include Artificial Intelligence (AI), Machine (ML), and Data Science in K12 Curricula?

Overview

According to a report from PwC, the growing influence of AI and ML in business routines, and the imperative need to automate business processes, will cause AI to replace 30% of the jobs by 2030!

Now, that’s with AI and ML – the branches of data science. The situation with data science, in entirety, isn’t much different either. The ever-increasing significance and criticality of data in the context of new-age businesses will make data scientists the most valuable of all the professionals around.

These facts and figures are crucial for K12 educators to prepare a curriculum that incorporates AI, ML, and data science. While some are planning to do it, some have already proved themselves futuristic by including these subjects in the regular syllabus.

But then, career growth, job security, and amazing salary packages aren’t the only reasons that point towards learning data science and AI in the early years. These subjects develop the skills to prepare students for the more significant race and strengthen their chances of excelling in the competitive world.

So, let us look at how AI, ML, and data science prove advantageous from the technical as well as an intellectual point of view for K12 students.

Reasons why Schools must include AI and ML in the K12 Course Curricula

AI is everywhere, and that constitutes the first reason why schools must seriously consider including AI in their course curricula. But there are a few other reasons that highlight the significance of learning AI in the early years. Here are some of them.

Exploring Real-World Problems where Students can apply AI

The modern-age student is much more different than the one you may have come across a decade ago or so. These days, students are daring enough to encounter real-world problems and develop the intellect that helps them resolve them. AI is one such technology that gives students the opportunity to explore real-world problems and solve them through its application.

This isn’t usual, and neither was it practiced in the past. Conventionally, students, at the most, went across illustrative problems that often limited them to a theoretical perspective of the concern.

Preparing for the Future

They say AI is the future, and most of the tools, technologies, devices, applications, software products in the future will incorporate AI. AI is slated to cover almost every industry, including healthcare, banking, insurance, automobile, manufacturing, education, etc.

If that’s true, and of course, as it is, learning AI will prove beneficial, as it will help students develop the competence they will require to qualify to work in the AI-governed future. So, schools and colleges must not limit themselves to conventional course curricula but include AI to ensure sustainable competence.

Students Learn AI and Develop Solutions Collaboratively

A single brain may not prove as effective and useful as a group of minds would. AI offers students the opportunity to learn the technology and develop solutions in a collaborative manner. Such a collaborative learning environment helps students develop team playing skills, and qualify them for better team playing job opportunities, and leadership positions in the future.

Why include Data Science in the High School Course Curriculum?

As mentioned earlier, the students of the 21st century are clever and courageous. They are ready to face real-world problems, and the fact that technology can help them devise solutions excites them. Something which was a grave problem a couple of decades ago has become a child’s play for the modern age students. The introduction of data science further helps students develop better skills.

Many schools have already introduced programming languages such as Java, C, C++, etc. in their course curriculum. However, the entry of data science seems delayed, despite the growing significance of the technology. But, in the future, and with companies increasingly leveraging data science to increase bottom lines, the demand to introduce data science in the course curriculum will soon increase.

If regularizing data science in the course curriculum seems a challenge, schools, in the initial stages, may open students the access to interactions with experienced and successful data science professionals. It will help students develop insights and a practical understanding of data science.

Conclusion

At CITIS Infotech, we help schools and colleges with vital academic recommendations in the data science stream and help them develop an industry-oriented data science curriculum. We work as the educational technology partners of schools and colleges to enable them to develop the students' sustainable competence.