Higher Education – RUSA, NIRF, HEFA, etc.

The NEP 2020 must look beyond just data science and AI


From UPSC perspective, the following things are important :

Prelims level: NEP 2020

Mains level: Paper 2- NEP 2020's focus on mathematical and computational thinking

The article deals with the issues with the emphasis on the coding instead of understanding the basic algorithmic process.

Issues with focusing on coding in NEP 2020

  • The National Education Policy 2020 (NEP) envisages putting greater emphasis on mathematical and computational thinking throughout the school years.
  • The framing in the NEP appears to put it at the same level of distinction as the more instrumental ‘coding’, and almost as a mere tool towards the utilitarian goals of artificial intelligence (AI) and data science.
  • An overemphasis on learning the nitty-gritty of specific programming languages prematurely — even from middle school — may distract from focusing on the development of algorithmic creativity.

What is coding?

Coding is basically the computer language used to develop apps, websites, and software. Without it, we’d have none of the most popular technology we’ve come to rely on such as Facebook, our smartphones, the browser we choose to view our favorite blogs, or even the blogs themselves. It all runs on code.

About computation and algorithms

  • Algorithmics is the abstract process of arriving at a post-condition through a sequential process of state changes.
  • It is among the earliest human intellectual endeavours that has become imperative for almost all organised thinking.
  • All early learning of counting and arithmetic is method-based, and hence algorithmic in nature, and all calculations involve computational processes encoded in algorithms.
  • The core algorithmic ideas of modern AI and machine learning are based on some seminal algorithmic ideas of Newton and Gauss, which date back a few hundred years.
  • Though the form of expressions of algorithms — the coding — have been different, the fundamental principles of classical algorithm design have remained invariant.

Algorithms in modern world

  • In the modern world, the use of algorithmic ideas is not limited only to computations with numbers, or even to digitisation, communication or AI and data science.
  • They play a crucial role in modelling and expressing ideas in diverse areas of human thinking, including the basic sciences of biology, physics and chemistry, all branches of engineering, in understanding disease spread, in modelling social interactions and social graphs, in transportation networks, supply chains, commerce, banking and other business processes, and even in economic and political strategies and design of social processes.
  • Hence, learning algorithmic thinking early in the education process is indeed crucial.

So, how coding is different from arithmetics?

  • Coding is merely the act of encoding an algorithmic method in a particular programming language which provides an interface.
  • AS computational process can be invoked in a modern digital computer.
  • Thus, it is less fundamental.
  • While coding certainly can provide excellent opportunities for experimentation with algorithmic ideas, they are not central or indispensable to algorithmic thinking.
  • After all, coding is merely one vehicle to achieve experiential learning of a computational process.

Way forward

  • Instead of focusing on the intricacies of specific programming languages, it is more important at an early stage of education to develop an understanding of the basic algorithmic processes behind manipulating geometric figures.
  • Indeed, this is a common outcome of the overly utilitarian skills training-based approaches evidenced throughout the country.


The NEP guideline of introducing algorithmic thinking early is a welcome step, it must be ensured that it does not degenerate and get bogged down with mundane coding tricks at a budding stage in the education process.

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