With 12.5 lakh students registered and 9.9 lakh applications submitted in its initial edition, the CUET-UG is the second-largest entrance test in the nation. Between May 21 and July 5, there were nine phases of the exam, each lasting three shifts. The equi-percentile technique uses each candidate’s raw score in comparison to others taking the same exam to determine their percentile.
UGC Chairman M Jagadesh Kumar stated that the equi-percentile method for normalizing CUET-UG scores is a fair mechanism without luck. The Common University Entrance Test (CUET)-UG results were announced on Saturday, and some candidates complained about scores being reduced due to normalization.
“First, we must remember that we were required to conduct CUET in multiple shifts in a given subject due to the large number of students participating in the test. For example, if the test is in economics, NTA experts prepare multiple economics papers for use in different shifts. Despite our best efforts, the difficulty level of each paper will slightly differ from the other. Therefore, one needs to use normalized scores instead of scores obtained by a student,” Kumar said.
“To do this, we apply a scientific technique known as the equi-percentile method in order to normalize the degree of difficulty across various shifts. As a result, some students’ normalized scores will be less than their actual scores, while for others they might rise.
“This technique, a statistical tool for determining the association of scores on various examinations, has been popular throughout the world for decades. As a result, there is no unfairness or chance. Students shouldn’t be concerned about it, he continued.
Candidates’ performance in different sessions of a subject is made comparable by equating and converting their percentiles into normalized marks. Sessions with fewer candidates are merged with larger sessions. The normalized marks obtained through this process can be treated similarly to raw marks in a conventional single-session exam. Consequently, in a university, the weightage assigned to the skill component’s raw marks can be combined with the remaining weightage of the normalized marks to create the rank list, explained Kumar.
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