Indian Railways clarifies on its computer based test for selecting new employees, says merit was the sole criteria

Faced with a large number of representations from candidates  over the results of the computer -based test (CBT) conducted by railway recruitment Boards(RRB) and its methodology, Indian Railways (IR)  has clarified that short listing was based purely on merit using the normalisation method.

This,IR said was clearly specified  in Para-7 under the heading “Important Instructions” of the Centralized Employment Notification(CEN) 02/2018. 

The maximum normalized marks of any candidate in Level-1 CBT is 126.13, IR said. Marks higher than this, is pure concoction, the statement added.

These tests were conducted over a three-month period between September 17 and December 17, 2018, for 62,907 vacancies. Over 1.89 crore applications were received (1,89,78,913 applications) for which CBT was conducted on 51 days over 152 shifts. The results were announced on March 4, 2019. 

 IR stated that all candidates were made privy to the question papers, master answer key and their own evaluated answer sheet before publication of results. In addition, the‘Objection tracker’ was accessible to candidates from January 14 to January 20, 2019.  During this  period, 1.58 lakh candidates submitted their objections which were considered and reviewed.  

Normalisation method

Normalisation entails adjusting adjusting actual values measure on different scales to a common notional value. In this case, the 152 shifts under which the examination was conducted would have had a different question paper.  

The normalised score of an applicant Xn is calculated by the formula. Normalisation also takes into account invalid questions in a question paper, if any.

Standard deviation is the extent of deviation an applicant displays from the average score of the examination shift in which the applicant appeared for the CBT. It shows how much an individual’s performance deviates from that of a group’s performance under the same conditions. 

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