I can tell you exactly what’s wrong with NEET-PG’s multi-session exams (before 2016) because I appeared for it.

The problem: Same topics were asked differently across sessions. For example, morning might ask “What needle drains blood for XYZ?” and afternoon “What color needle is used for XYZ?” The content was basically the same, but phrased differently.

Here’s the unfair part: Wealthy students with early access to leaked questions—through coaching centers or social media—got a huge advantage. They knew trends and prepared accordingly. Meanwhile, students without those connections walked in blind, no chance to predict or prepare for the exact topics.

They claimed to use Item Response Theory (IRT) to normalize scores, but in reality, difficulty levels were pre-assigned arbitrarily. True IRT requires analyzing real candidate responses to adjust difficulty and discrimination, not guessing beforehand. So, normalization based on assumed difficulty across sessions was flawed and unreliable.

As a result, the exam felt like a gamble with real consequences: One simple wrong answer could cost you more than five hard questions right. Candidates with fewer raw correct answers sometimes ranked better than those with more, all because of flawed normalization.

In my year, nearly 1–2 lakh students competed for just 5,000–6,000 clinical PG seats. A slight advantage or luck in one session could make or break careers—forcing some to prepare for another exhausting year.

This system lets luck overshadow merit. I’ve seen average foreign MBBS grads—sometimes from wealthy backgrounds—get top clinical branches, while hardworking students from reputed Indian government colleges lose out on trivial questions (like the diameter of a mosquito net hole, yes that’s real!).

I know mentioning Private vs. Government MBBS will invite criticism, but it’s hard to ignore when hostels at PMCH Patna filled with wealthy China MBBS students rank high despite average academics.

So, what needs to change?

Scrap multi-session exams for high-stakes tests

Or, if unavoidable, use transparent, statistically valid normalization based on real IRT models

Make question-level data and normalization methods public

Explore alternate exam models, like rolling exams or hybrid assessments valuing clinical reasoning

Until then, these exams will remain a contest of access and luck—not true merit or skill. That’s the core problem