Akshaya
24 posts







Barely 48 hours ahead of the exam, medical aspirants have flooded social media with their concerns concerning the ensuing exam. hindustantimes.com/education/comp… #NEETPG2024








LONG POST ALERT! Here is my take on Normalization in MD/MS exams, in a country like India. 1. Loss of Individual Performance Insight: Obscures detailed individual performance, making it harder to distinguish between high and low performers accurately. 2. Potential for Misrepresentation: Scores can be misrepresented due to over-reliance on statistical adjustments, potentially leading to unfair outcomes. 3. Complexity and Lack of Transparency: The process is often complex and difficult for students to understand, leading to perceptions of unfairness. 4. Overemphasis on Statistical Parity: Can ignore differences in exam difficulty, disadvantaging students who took a harder or easier version. 5. Introduction of Bias: If not done correctly, normalization can introduce biases, especially if all relevant factors are not considered. 6. Reduced Motivation: Students may feel demotivated if they perceive their raw scores are significantly altered, reducing the perceived value of their effort. 7. Data Dependency: Relies heavily on the quality and quantity of data available. Poor-quality data can lead to incorrect adjustments and unfair results. 8. Diverse Exam Content: MD/MS exams cover fundamentally different content areas and competencies. Normalization assumes comparability of scores across different subjects, which is not applicable given the varied nature of the exams. 9. Potential for Over-correction: Excessive normalization may over-correct scores, diminishing the accuracy of performance assessment. 10. Loss of Original Score Integrity: Original scores may lose their integrity and meaning after normalization, affecting their reliability as a measure of performance. Finally - Even if the paper is leaked and a candidate scores 200/200, normalization will make sure no one knows it. Last but not least, has the statistical method been tested already in a group of the population and agreed to be unbiased? If not, how can it be applied in an exam to a large population, especially in an exam that means life or death to the students? #NEETPG2024 #needfairassessment









SANJAY SIR AND ANAS SIR ARE CARRYING THE DREAMS OF 2.5 LAKH DOCTORS! @Vakeel_Sb @sanjayuvacha THANK YOU FROM EVERYONE. WHEN NO ONE HEARD US, YOU DID! FOREVER GRATEFUL! @ShashiTharoor PLEASE help! #neetpg #neetpgsingleslot #NEETPGUPDATE #NeetPG_mismanagement



