There’s an uncomfortable truth we need to confront about technical education in India: many of those teaching our future engineers are there not by choice, but by circumstance.
This isn’t about questioning anyone’s dedication or competence. It’s about acknowledging a systemic problem that affects every engineering college, every computer science department, and ultimately, every student like you who will graduate in four years.
How We Got Here: The Pattern Nobody Talks About
Here’s how it works: To teach BTech CSE students, faculty must hold an MTech in Computer Science. On paper, this makes sense. But here’s what actually happens:
A bright BTech graduate faces a choice. Industry offers immediate opportunities: product companies, startups, global tech firms. Those who don’t secure these positions often pursue MTech. After MTech, the pattern repeats. The best opportunities go to the best-positioned candidates. Teaching becomes the fallback, not the aspiration.
The result? We’ve inadvertently created a selection process that filters for those who didn’t get industry jobs, rather than those who are passionate about teaching.
Here’s the Surprising Part: Teachers Actually Earn More
Here’s what surprises most people: thanks to government regulations, faculty salaries have improved significantly. A fresh MTech graduate at a decent institution starts at ₹50,000 per month, substantially more than the ₹30,000 an IT services company might offer to a BTech graduate.
Yet students still choose the IT services role.
This reveals something crucial: we’re not dealing with a compensation problem. We’re dealing with a perception and prestige problem.
Teaching, despite better pay and job security, lacks the aspirational pull that technology careers command. The social capital of saying “I work at a tech company” outweighs the financial logic of a teaching position. This isn’t just about computer science. It happens in mechanical, electronics, civil; every branch where industry jobs feel more exciting than teaching.
The Three Pillars of Teaching: Where We’re Failing
Teaching, at its core, requires three elements:
- Content: What to teach
- Teaching method: How to teach it effectively
- Inspiration: Why students should care
In traditional education, we expect faculty to excel at all three. But in technology education, we’ve set up an impossible standard.
The Content Problem: Technology Changes Faster Than Textbooks
In just the last month, we’ve seen new AI tools released, programming languages updated, and completely new ways of building software emerge. A faculty member who commits to a 30-year teaching career is expected to keep pace with an industry that reinvents itself every few years.
We train faculty through training programs, but look at what these programs focus on: teaching methodologies, classroom management, student engagement techniques. These matter, but they sidestep the real challenge, staying current with content that evolves weekly, not annually.
The Broken Fix: Why Traditional Solutions Won’t Work
The instinctive response is often: “We need better faculty training.” But this misses the point entirely.
You cannot train someone to keep pace with an exponentially evolving field while also expecting them to master teaching methods, inspire students, handle administrative work, and maintain research output. It’s not a training problem. It’s a system design problem.
Imagine asking a pilot to also design the aircraft, maintain the engine, and entertain the passengers. We don’t do this because we understand that complex systems require specialisation and the right tools. Yet this is precisely what we expect from engineering faculty.
A Better Way: Let Technology Handle What Technology Does Best
What if we reimagined the teaching role in the age of AI and intelligent platforms?
Instead of expecting teachers to be content experts, teaching masters, and motivational speakers all at once, what if we built systems that handle what technology does best: keeping content updated, personalizing learning, tracking performance. This would free teachers to focus on what humans do best: inspiring you, mentoring you, and guiding your journey.
This isn’t about replacing teachers. It’s about empowering them.
Consider a platform that:
- Maintains living content that updates with industry changes, so teachers don’t have to worry about outdated textbooks
- Embeds proven teaching methods directly into learning materials, with hands-on coding practice, simulations, and tests that adapt to your level
- Provides real-time insights into every student’s performance, so teachers can give you personal attention instead of treating everyone the same
- Automates evaluation of routine assessments, giving teachers more time to actually talk to students
In this setup, teachers stop being lecture machines and become guides. They’re not struggling to remember the syntax changes in the latest Python release; they’re helping a struggling student understand why they should care about data structures. They’re not spending evenings grading 60 identical coding assignments; they’re having conversations with students about career paths and problem-solving approaches.
What This Means for Making Teaching Attractive
When we remove the impossible content burden and provide intelligent infrastructure, teaching becomes a fundamentally different proposition:
- Faculty can focus on relationships and inspiration, the most rewarding aspects of teaching
- Real-time performance data enables visible impact on student outcomes
- Reduced administrative burden allows for work-life balance that industry increasingly fails to provide
- The role becomes about mentorship and guidance rather than content delivery, inherently more satisfying work
This is how we begin to shift perception. Not by paying more or mandating respect, but by fundamentally changing what the job entails.
Why AI Changes Everything for Education
We’re at an inflection point. AI has proven that just dumping information on students doesn’t work anymore. What students need are guides who can help them navigate complexity, ask better questions, and develop judgment.
This is precisely what human teachers should excel at, if we stop forcing them to compete with systems at tasks systems do better.
Intelligent platforms in the AI era don’t diminish teaching; they elevate it to what it should have always been: a deeply human effort focused on inspiration, guidance, and individual growth.
A Call for Systemic Change
The quality crisis in engineering education won’t be solved by:
- Raising degree requirements
- Forcing more training programs
- Increasing faculty-to-student ratios
- Or even paying significantly more
It requires acknowledging that we’ve designed an impossible job, and then redesigning it around human strengths amplified by intelligent systems.
This conversation applies beyond computer science. Every technical discipline facing rapid evolution (and that’s increasingly all of them) confronts similar challenges. The question isn’t whether we need to change, but whether we’ll change deliberately or wait for the system to fail more dramatically.
The faculty members showing up to teach every day despite these systemic failures deserve better. More importantly, you (the students whose futures depend on quality education) deserve better.
It’s time to build education systems worthy of both.