OUR EDUCATION SYSTEM IS STUCK IN A GRAVEYARD OF OLD IDEAS

1964: Three members of the Pioneer Batch (1960–65) — RC Jain, VS Narang and Aditya Jain working on the 1620 in WL. Picture Credit: Pioneer Batch Golden Jubilee Collection

A few months ago, I walked into my college computer laboratory to write a practical examination. Before I could even enter the room, I had to remove my shoes and leave them outside. Not just my shoes, even wearing socks was discouraged because there was always a concern that students might use them to hide something and cheat. After entering the lab, I sat in front of a modern computer capable of running software thousands of times more powerful than anything available to engineers a few decades ago. Yet I wasn’t allowed to touch the keyboard.

Instead, I was handed sheets of paper.

Before I could write a single line of code on the computer, I first had to write the entire program by hand. Every bracket. Every semicolon. Every variable name. Every line. Once I finished, I had to show it to the examiner, who would inspect it, award marks for it, and only after receiving approval would I be allowed to type that exact same code into the computer sitting right in front of me.

As I sat there copying code from paper to screen, a thought kept bothering me.

What exactly are we trying to achieve?

Not just in my college, but in computer science education as a whole.

Because while I was busy memorizing syntax and reproducing programs from memory, somewhere else in the world a developer was collaborating with a team spread across three continents, using cloud infrastructure, version control systems, documentation, AI assistants, automated testing tools, and decades of collective knowledge available at the click of a button. Somewhere, an engineer was solving real problems. Somewhere, a startup was deploying software to millions of users. Somewhere, artificial intelligence was generating hundreds of lines of functional code in seconds.

And yet here I was, being evaluated on my ability to remember where exactly a bracket should go.

The strange thing is that I understand where this tradition comes from.

In fact, I respect it.

The origins of these practices lie in an era that most students today cannot even imagine. When institutions like IIT Kanpur began pioneering computer science education in India during the 1960s, computers were not personal devices. They were not classroom equipment. They were not tools sitting on every desk. They were rare, expensive, room-sized machines that represented the cutting edge of technology. Through collaborations involving IBM and international academic programs, IIT Kanpur became home to some of India’s earliest advanced computing systems. Access to these machines was limited, and every minute of computing time mattered. Students often had to write programs on paper, convert them into punched cards, submit them for execution, and then wait for results. A single mistake could mean hours or even days of delay before another attempt was possible.

In that world, writing code on paper made perfect sense.

It was not an educational philosophy.

It was survival.

You thought before you typed because typing was expensive. You checked your logic repeatedly because mistakes carried consequences. You approached the machine only after you were confident that your work was correct.

Similarly, the tradition of removing shoes before entering computer laboratories was not irrational. Early computers required carefully controlled environments. Dust, heat, and environmental factors posed genuine risks to delicate equipment. The laboratory was not merely a room full of machines. It was a technological sanctuary housing equipment that few institutions could afford.

The problem is that we no longer live in that world.

The computers in our laboratories today are not fragile relics from the dawn of computing. They are ordinary machines. The scarcity that justified those traditions disappeared decades ago. The constraints that created those rules no longer exist. Yet somehow the rules survived while the world around them transformed beyond recognition.

What fascinates me is how educational systems often become museums without realizing it. A museum preserves things because they are historically valuable. An educational institution should preserve things only if they remain educationally valuable. Those are not the same thing.

Somewhere along the way, we stopped asking why these practices existed and started following them simply because they had always existed. We inherited the rituals but forgot the reasons behind them. We preserved the methods while abandoning the circumstances that made those methods necessary.

The result is a strange contradiction.

Universities proudly advertise courses in artificial intelligence, cloud computing, machine learning, cybersecurity, and data science. They tell students they are preparing them for the future. They speak endlessly about innovation, disruption, and emerging technologies.

Then they walk students into examination halls and evaluate them using methods designed for a technological environment that disappeared half a century ago. The contradiction becomes even more obvious when we compare education with industry.

Imagine a software company telling its developers that they are not allowed to use documentation.

Imagine banning Google searches.

Imagine forbidding collaboration.

Imagine demanding that engineers memorize every function, every library, and every syntax rule before touching a keyboard.

The company would collapse. Because real-world engineering has never been about memorization. It has always been about problem-solving.

A great engineer is not someone who remembers everything.

A great engineer is someone who knows how to find answers, evaluate information, understand systems, and solve problems efficiently.

The modern world rewards adaptability, not memorization. Yet our examinations frequently reward memorization while claiming to measure technical competence. This is not merely a flaw in assessment. It changes how students learn.

When examinations reward memory, students prioritize memory.

When examinations reward reproduction, students prioritize reproduction.

When examinations reward syntax, students focus on syntax.

Students adapt to incentives exactly as every human being does.

As a result, countless students spend hours memorizing programs they barely understand because understanding is not what the system rewards. The goal becomes reproducing the expected output rather than developing genuine computational thinking. Ironically, this approach often produces the exact opposite of what computer science education should achieve.

Programming is not the art of remembering code. Programming is the art of expressing logic. The computer does not care whether I remembered a semicolon from memory. The computer cares whether my solution works. The user certainly does not care how much syntax I memorized. The user cares whether the software solves their problem. At some point, education confused the language with the idea.

Learning programming languages matters. Understanding syntax matters. But they are tools, not objectives.

No one claims a novelist is talented because they memorized the dictionary.

No one claims a scientist is brilliant because they memorized every formula.

No one claims a pilot is skilled because they memorized every page of a manual.

What matters is the ability to apply knowledge effectively. Yet somehow, in computer science, we continue treating memory as a substitute for competence. What frustrates me most is that I am not arguing for the abandonment of discipline.

There is genuine value in forcing students to think before they execute. There is value in understanding algorithms without relying on software tools. There is value in developing logical reasoning independent of technology. Those lessons remain timeless.

But discipline and outdated methodology are not the same thing. We can teach logical thinking without pretending the internet does not exist. We can teach programming without banning access to modern tools. We can assess problem-solving without reducing coding to a memory contest. Most importantly, we can respect the pioneers of computer science without freezing education in their era.

The engineers and educators who introduced these traditions were innovators. They adapted their methods to the realities of their time. They solved problems created by the limitations of their technology.

If they were standing in our laboratories today, surrounded by high-speed internet, artificial intelligence, cloud infrastructure, and computing power beyond anything they could have imagined, would they really insist that students continue following every practice from 1963?

Or would they do what engineers have always done?

Adapt.

That, perhaps, is the question that bothers me every time I sit down for a practical examination.

Not why students once wrote code on paper.

That part makes perfect sense.

The question is why, after sixty years of technological revolution, we still insist that the future be examined through the lens of the past.

Because preserving history is admirable.

But preparing students for the future is far more important.