In my 18 years in Indian education, I’ve watched the same conversation play out at every engineering college I’ve visited.
A senior faculty member, MTech, sometimes a PhD, sits across the table. Sharp. Genuinely cares about students. And somewhere in the conversation, almost in passing, they tell you the truth.
They didn’t plan to be a teacher. They ended up here.
This isn’t about questioning anyone’s competence. It’s about acknowledging something the system rarely admits out loud: most of the people teaching your engineering syllabus weren’t selected for teaching. They were selected by what was left.
How we got here
Here’s how the pipeline actually works.
To teach BTech CSE, you need an MTech in Computer Science. On paper, fair. In practice, the MTech queue fills with people who didn’t get the industry job they wanted at graduation. After MTech, the pattern repeats. The best opportunities go to the best-positioned candidates. Teaching becomes the fallback, not the aspiration.
So we’ve built a selection process that filters for people who didn’t make it to industry, and then we wonder why classroom relevance lags industry by a decade.
Here’s the part that surprises people
Thanks to government regulations, faculty pay has actually moved up. A fresh MTech graduate at a decent institution starts at around ₹50,000 per month. An IT services company offers a BTech graduate around ₹30,000.
Teaching pays more. Students still pick IT.
Read that twice.
We’re not dealing with a compensation problem. We’re dealing with a prestige problem. Saying “I work at Razorpay” carries something that saying “I teach at a tier-2 college” doesn’t, regardless of what the bank statement says.
And this isn’t just CSE. It’s mechanical, civil, electronics, every branch where industry feels more alive than academia.
The three things teaching needs
Teaching, done properly, requires three different things at the same time.
Content. What to teach.
Method. How to teach it.
Inspiration. Why students should care.
In traditional disciplines, that’s hard but doable. One person keeps current in their field, learns to teach over a decade, and slowly builds the conviction to inspire.
In technology education, we’ve set up an impossible standard.
In the last month alone, new models shipped, new frameworks broke, new ways of building software entered production. A faculty member signing up for a 30-year teaching career is being asked to keep pace with a field that reinvents itself every few months.
Faculty training programmes try to fix this, but look at what they actually teach. Classroom management. Engagement techniques. Student-centric pedagogy. All of which matter. None of which solve the actual problem, which is staying current with content that moves weekly.
That’s not a training problem. That’s a job design problem.
The instinctive response is always: better training, stricter qualifications, more refresher courses. But this misses what’s broken.
You cannot train one person to keep pace with an exponentially evolving field, master teaching method, inspire students, handle administration, and publish research. We’re asking a pilot to also design the aircraft, maintain the engine, and entertain the passengers.
We don’t do this in any other complex system. Software has specialised roles. Hospitals have specialised roles. Only in education do we still expect one person to carry every layer.
What changes when we let machines do what machines do best
The interesting question isn’t “how do we train teachers better.” It’s “what if we stopped asking one person to do five jobs.”
What if intelligent platforms carried the content layer? Living curriculum that updates as the industry shifts. Coding practice that adapts to where a student is actually struggling. Real-time performance data so teachers know who needs help on what, before the end-semester exam reveals it.
That doesn’t replace the teacher. It removes the part of the job that was breaking them, and frees them to do what humans actually do better than any system: notice a struggling student, ask the right question, sit through the hour where it finally clicks.
Teachers stop being lecture machines. They become mentors. Which, if you ask any teacher honestly, is the part of the job they signed up for in the first place.
Why this is also how we fix the prestige problem
When you remove the impossible content burden, the job changes shape entirely.
Less time grading 60 identical assignments. More time having one real conversation about why someone is stuck. Less time chasing what’s new in PyTorch. More time helping a third-year figure out whether they want to be a developer, a researcher, or something they haven’t named yet.
That’s a different job. A more satisfying one. The kind of job a strong engineer might actually choose, not settle for.
You can’t legislate respect for teaching. You can redesign the work until it becomes worth respecting.
What this means for you
If you’re picking an engineering programme this year, ask one question that nobody on the brochure team will be ready for.
How does your faculty stay current with what the industry is doing right now? Not what’s in the textbook, what’s in production.
The honest answer tells you everything. If the answer is “annual training programmes” or “faculty development cells,” that institution is still trying to solve a content problem with a training intervention. If the answer involves a system that carries the content layer and frees faculty to mentor, you’re looking at a programme that has at least understood the question correctly.
The faculty showing up every day despite all of this deserve better. So do the students whose futures depend on them.
We’ve designed an impossible job. The fix isn’t more pressure on the people doing it. It’s a job worth doing.