Education Technology | Innovations and Insights - Edinbox

Anupam Yash Vardhan, an IIT Madras graduate, has kicked up the hornet's nest with a frank post on LinkedIn. "School Fees: Rs 34 lakhs. Teacher Salary: Rs 34 lakhs," he posted, and detailed how only about 2% of fees could find its way to teachers.

He calculated the numbers on a model in which five teachers teach one subject each to five sections of 50 students each -- something that happens in the majority of Indian schools.

Now this revenue is primarily supposed to go into paying the salaries of the five subject teachers catering to those 250 students. If each teacher gets Rs 34 lakh annually, it's an expense of Rs 1520 lakhs only.

What happens to the remaining Rs 7.3980 crore?

It's a tidy picture of an arrangement where almost all income gets baked into overhead, administration, and buildings—and the folks actually teaching get crunch crumbs.

TEACHER PAY IN STASIS

The theory gets a bit of traction from actual data: Vardham posted a screenshot of a website that was listing Delhi Public School payrolls updated as of August. Based on 5,300 records, it indicated that the mean teacher salary stood at Rs 3.7 lakh per year.

Full-time PRTs receive Rs 4 lakh, primary teachers Rs 3.9 lakh, principals earn Rs 7.8 lakh.

Vardhan cuts to the chase: "Teachers were earning the same salary in 2005 as well. I am sure today's quality of teachers is nowhere near 2005 though."

So what is the explanation? In an environment where fees continue to go up, paychecks hardly move.

He wasn't mincing words: "If teachers are being paid by schools as much as delivery men and maids, what education are children receiving!" It's a biting observation, and it reflects a widespread frustration—not only with high fees, but the fact that not enough money is making it to classrooms.

WHAT'S REALLY GOING ON HERE?

The larger picture:

• Urban private schools drive fees upwards, often in an unsustainable way.
• Teacher salaries plateau even as inflation and workload increases.
• Lower-grade cities can be more value-for-money, lower fees but good quality.
• Dad and mum are beginning to ask themselves: am I paying for schooling or for packaging?

WHAT'S NEXT?

Two things are important. First, we need openness—what portion of our fees is actually put into teaching, and how schools account for their expenses.e

Second, perhaps it is time to rethink where education value lies. If quality instruction is beyond the Rs 4 lakh range, then why not shine a light on that?

Centre of Excellence in Sustainable Shipbuilding Technology on the CUSAT campus by combining Cochin University of Science and Technology (CUSAT) and Cochin Shipyard Limited (CSL). CSL will provide financial support of ₹3.53 crore for this initiative, say university officials.

According to CUSAT, the Centre is set to bridge the gap between academia and the shipbuilding industry through the provision of state-of-the-art facilities, training, and research. It will focus on software development, skill development, upgradation of technology, and digitisation—largest sectors defining the future of shipbuilding.

The Centre will also have provision for state-of-the-art computing facilities and sophisticated marine software packages in Naval Architecture, Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), and other areas of research. This setup will support innovation in ship design, shipbuilding, and high-level analytical research, and increase India's prowess in sustainable maritime technology.

CUSAT Vice-Chancellor Dr. M. Junaid Bushiri formally received the MoU from CSL Managing Director Madhu S. Nair during a function on Friday. University Registrar Dr. Arun A. U. had signed the agreement on behalf of the university.

For coordination of the project and CSR fund, Vice-Chancellor nominated Dr. Satheesh Babu P. K., Associate Professor of the Department of Ship Technology, as the coordinator of the Centre. Dr. Manoj T. Issac and Dr. Rajesh P. Nair, Assistant Professors, will serve as assistant coordinators.

Speaking of the alliance, the officials said that the Centre would not merely equip students in state-of-the-art shipbuilding technology but also serve as a hub for industry-academia collaboration. The focus on green shipbuilding is expected to align with global green shipping standards and further India's maritime innovation ecosystem.

Based on the career goal of the student, mode of learning, and future aspirations, a Diploma in Automobile Engineering or a BTech in Mechanical Engineering is chosen. Both programs offer a path to the field of engineering, but they are not equal in scope, magnitude, and opportunity.

A Diploma in Automobile Engineering is a 3-year industry-oriented course with emphasis on practical training of vehicles in design, manufacturing, maintenance, and servicing. There is more time given in workshops, and students gain hands-on experience of engines, automotive electronics, aerodynamics, and emission control systems. The graduates get placed in automobile OEMs, component testing, and electric vehicle startups with starting salaries of INR 2–4.5 LPA. Companies that recruit are Tata Motors, Mahindra & Mahindra, and Honda.

In comparison, BTech in Mechanical Engineering is a 4-year undergraduate degree that combines theory and practice. It covers a wide area of mechanical concepts such as thermodynamics, manufacturing technology, robotics, energy systems, and automotive engineering. With such a wider exposure, the graduates can be part of diverse industries such as aerospace and oil & gas or automotive and robotics. The average salary begins from INR 3–6 LPA with extensive scope for growth (up to INR 10 LPA and beyond). Key companies recruiting are Larsen & Toubro, Tata Motors, and even multi-nationals such as Goldman Sachs and JPMorgan, since they need analytical and technical skills.

The principal distinction is one of career mobility. While a diploma allows for an earlier insertion into the motor industry, a BTech introduces greater opportunities, superior remuneration, and eligibility for postgraduate research or study posts.

For car passionista students who dream of premature exposure to the industry, a diploma would be appropriate. But for those looking for long-term growth, broad professional opportunities, and chief-executive roles, a BTech in Mechanical Engineering remains the superior choice

The Delhi government on Thursday unveiled a ₹170-crore initiative to modernize 15 government Industrial Training Institutes (ITIs) into technology centers with courses in artificial intelligence, electric vehicles and robotics, officials said.

Industries minister Manjinder Singh Sirsa asserted the scheme will make students job-ready for new industries. "By including EV, AI, robotics and green energy modules in the curriculum of ITIs, we are developing the launchpad for our young generation to make Delhi and Bharat future-ready. These advanced ITIs will give students 21st-century skills so that they go out as job-creators, not as job-seekers," he added, while also accusing earlier governments of slowing down central welfare schemes.

The nodal agency for implementation will be the Department of Training and Technical Education (DTTE), which is chaired by education minister Ashish Sood. Three ITIs, namely Pusa (Central Delhi), Shahdara (east Delhi) and Mangolpuri (north-west Delhi), will be hub institutes, with each mentoring up to four spoke ITIs in the way forward on infrastructure development, faculty development and industry association. "Blended learning content, smart classrooms and simulation labs will be launched together with compulsory internships and apprenticeship facilitated diploma programs," Sirsa announced.

Officials informed that apprenticeship-associated degree courses would be introduced at Delhi Skill and Entrepreneurship University (DSEU) and Delhi Technological University (DTU) shortly. "Quarterly apprenticeship melas will be organized, with a special ₹1,000 top-up for women and disabled persons. Mobile skilling vans equipped with solar panel rigs and VR welding simulators would also be introduced. Entrepreneurship and innovation cells would be established in all hub ITIs," said an official.

The government also intends to set up centres of excellence in ITIs at Dheerpur, Mayur Vihar and Pusa where students will be provided training in industrial automation, robotics and advanced welding. "Under the PM Vishwakarma Yojana, more than 1,300 artisans have already received verified training in Delhi ITIs, whereas outreach programs like Jan Shikshan Sansthan in Jahangirpuri have impacted over 1,000 women," the official mentioned.

Sirsa said Delhi’s Skill Roadmap 2.0 has been designed as an open-source blueprint. “Any state can adopt, adapt and empower its youth. From integrating skill credits in school curricula to setting up incubation and seed-fund cells in every hub ITI, Delhi is demonstrating the importance of skill development,” he said.

The All-India Council for Technical Education (AICTE), along with the Department of Science (DST), has declared a curriculum for the MTech course on quantum technologies.

The course covers various quantum verticals ranging from computing, communications to sensing and materials, with a focus to give practical training through projects.

National Quantum Mission (NQM) is one of the projects envisioned under PM's Science, Technology and Innovation Advisory Council to position India among the leaders in quantum technology globally.

The curriculum suggests theory and lab courses in this curriculum. The course scheme is split into core courses, specialization electives, open electives and a project. Project-based learning approaches are encouraged to be included by institutions and students wherever feasible to create greater impact through the curriculum. At least 80 credits, it will be distributed over four semesters.

Dr Abhay Karandikar, DST Secretary, added, "Conceived by top experts, the programme weaves together theory, lab training, applied research and actual problems. It will enable students to become innovators, researchers, entrepreneurs and technology leaders in one of the most revolutionary frontiers of science."

He called upon institutes to implement the curriculum voluntarily. "Universities and technical institutions are advised to adopt and implement this programme, creating a sustainable talent pipeline for India's quantum future," Karandikar said.

As per the MTech programme curriculum, systematic training programmes for teachers are required to prepare them to deliver justice to the objectives of the MTech programme.

"Such consistent teacher training initiatives will also improve the quality of the training given to students over years with a long-term payoff and make India a world leader in this area. We also think that a textbook writing exercise should be undertaken to address the requirements of this graduate-level course on quantum technologies," the model curriculum states.

It appears scientists are working quickly to create artificial intelligence models that mimic human brains when it comes to reasoning. A new AI model, according to reports, can perform high-level reasoning, as opposed to widely used large language models (LLMs) like ChatGPT. Scientists report seeing improved performance in major benchmarks.

Researchers at Singapore AI firm Sapient have christened the new reasoning AI a hierarchical reasoning model (HRM), and it is said to be based on the hierarchical and multi-timescale processing that the human brain uses. This is really the manner in which various regions of the brain combine information over different periods, from milliseconds to minutes.

Based on the scientists, the new model of reasoning has shown improved performance compared to current LLMs and can function more efficiently. All this, they say, is made possible due to the model requiring fewer parameters and training samples. The scientists asserted that the HRM model requires 27 million parameters as it employs 1,000 training samples. Parameters in AI models are the learned variables during training, including weights and biases. However, the majority of sophisticated LLMs have billions or trillions of parameters. How does it fare?

When the HRM was tested in the ARC-AGI benchmark, which is known to be among the toughest tests to find out how close models are to attaining artificial general intelligence, the new model showed remarkable results, according to the study.

The model scored 40.3 per cent in ARC-AGI-1, whereas OpenAI’s 03-mini-high had scored 34.5 per cent, Anthropic Claude 3.7 scored 21.2 per cent, and DeepSeek R1 scored 15.8 per cent. In the same vein, HRM performed better in the harder ARC-AGI-2 test with a 5 per cent score, leaving the other models far behind. Although the majority of current advanced LLMs rely on chain-of-thought (CoT) reasoning, researchers at Sapient maintained that the technique has some major limitations, i.e., 'brittle task decomposition, extensive data requirements, and high latency.' HRM, however, applies sequential reasoning tasks within one forward pass and not step-by-step. It consists of two modules: one high-level module that does slow and abstract planning and one low-level module that does fast and precise calculations.

This is based on how various parts of the human brain do planning versus rapid response. Additionally, HRM uses a process called iterative refinement, i.e., it begins with an approximate solution and refines it with many bursts of short thinking. Apparently, after every explosion, it verifies whether it should continue to refine or if the obtained results are satisfactory enough as the final result. Based on the scientists, HRM was able to solve Sudoku puzzles that typical normal LLMs are incapable of solving.

The model was also highly proficient in identifying the optimal routes in mazes, proving that it can solve structured and logical problems significantly better than LLMs. Although the findings are staggering, there is a point to be made that the paper, published in the arXiv database, is still to be peer-reviewed. However, the ARC-AGI benchmark team tried to reproduce the results after the model became open-source. The team did verify the numbers; however, they also discovered that hierarchical architecture did not accelerate performance significantly as reported. They discovered that a lesser-documented improvement process in the course of training was probably the cause for the robust figures.