Engineering Syllabus – The Favourite Scapegoat

Engineering Syllabus – The Favourite Scapegoat

India produces 30 Lakhs engineering graduates per year. About 15 Lakhs are from circuit branches like Computer Science, Electronics and Communication and Electrical Engineering. Statistically 5% to 10% have employable skills. While the quantity of engineers has been increasing steadily over the years, quality in terms of skills continue to travel south. In Emertxe  we have been trying to address this challenge for a long period of time. Over the years I have been part of many invited conferences where potential solution for this challenge is been discussed. One of the frequent topic of discussion is about engineering course syllabus. Often it is concluded that syllabus needs a revamp, sighting syllabus remained the same from 1970s.

BTech in AI / ML ?

The topic of discussion further extends by saying it is time for us to teach the new generation engineering students about the latest technologies like Internet-Of-Things (IoT), Artificial Intelligence (AI),  Machine Learning (ML), Electric Vehicles (EV), Robotics etc. Some Engineering Colleges have even went to the extent of starting  branch in AI, just how ISE / IT branches were spawned from Computer Science and Engineering branch few years ago. This old wine in new bottle concept will continue, even the students are made to believe that the curriculum is very old, by joining new branches like BTech in Artificial Intelligence will solve the skill building problem. 

I have a quite different perspective when it comes to this topic. I have taken a closer look into undergraduate engineering curriculum across all colleges I could hardly notice 15% difference. Let us take an example of Computer Science branch, where I come from. At high-level curriculum can be divided into three buckets.

Computer Science Syllabus : A High-Level View

Job Role Expectations

If you ask any company working in web application development, mobile application development, Artificial Intelligence, Machine learning, Embedded Systems, or IoT about their entry-level engineer hiring expectations, they will be more than satisfied with the syllabus mentioned above. In fact, they claim that a combination of one programming language and deep understanding of the 4-5 topics listed above should be sufficient to get them selected. In fact, this is exactly what we do in our 6-month job-oriented Embedded Systems programmes. We put entry-level engineers through the four levels of transition described below.

  • Level-1: Get hands-on with one programming language (C in our case)
  • Level-2: Linux Operating System
  • Level-3: Embedded Programming with PIC Microcontroller
  • Level-4: An impressive profile with 7-8 projects build from previous three levels

We can clearly see the transition where our students are able to crack core company interviews around 6 months. The continuous testimony we receive from our 1000+ hiring partners clearly demonstrates its effectiveness on the ground. What they couldn’t accomplish in four years, they are able to achieve in six months. Indeed, modern boot camps in fields such as Full-Stack Web Development, Machine Learning, and Artificial Intelligence take a similar approach. In summary, we hardly cover 15% of overall Computer Science Curriculum mentioned above, which is sufficient for them to land in a core job.

So, Where Exactly Is the Issue?

Given my belief that 85% of the syllabus can be retained as is, I’m always perplexed as to why no one discusses how these engineering subjects are taught. The core issue lies in the way subjects are taught. Instead of hands-on practical learning, it has become rote-based. Let’s look at a simple C programming example. During my close interactions with many students, I could clearly see them mugging every line of source code (say, C programming), believing that this is the best way to learn programming. They believe they have learned programming by memorizing a few programmes such as the Fibonacci series, printing number triangles, odd or even numbers, prime numbers, and so on. In fact, we have a difficult time guiding them through the cycle of unlearn-learn-relearn

Of course, results follow naturally from real-world experience and the creation of demonstrable output in the form of projects. Concerning the remaining 15% of the required changes, I am still in favour of adding more elective options and promoting more internships. However, the core 85% of the syllabus can be preserved in its current form by implementing radical changes in the mode of delivery.

Conclusion

I would like to conclude this post by asking a few questions:

  • Why have Faculty Development Programs not scaled to the expected level, still having this gap?
  • Is the establishment of corporate labs within colleges yielding enough results?
  • What role will EdTech play in the future?
  • How can traditional higher education and EdTech coexist?

There are no easy answers as there are many stakeholders involved. I would like to keep this as a open thread and write more posts as we move forward.

Stay Tuned!