HT Analysis: Girls outperform boys in every major subject in CBSE Class 12
For instance, 55% of all the boys who appeared in the 2015 exam took mathematics as a subject, compared to just 36% girls. Biology was opted by 22% girls and 12% boys.
The subjects that are opted by students in the Central Board of Secondary Education Class 12 examinations varies in terms of gender, an analysis of data for the CBSE results from 2015 shows.
For instance, 55% of all the boys who appeared in the 2015 exam took mathematics as a subject, compared to just 36% girls. Biology was opted by 22% girls and 12% boys.
Other subjects with a prominent difference were home science and political science, which were opted by a higher number of girls as compared to boys. The reverse was true for physics and chemistry.
The following charts show the difference. The orange bars are the subjects opted by more boys than girls, while the purple ones show those in which uptake of girls was higher. The name of the subject and corresponding percentage difference in uptake is stated next to the bars.
Press the play button or manually move the slider to view data for different years, from 2004 to 2015.
Girls outperform boys
Girls have consistently performed better than boys in the CBSE exams over the last one decade. The average score of girls—best five—was four marks higher than that of boys. In 2004, females scored 62 on an average, and boys 58. In line with the CBSE marks inflation trend that has been observed over the years, the mean score for girls increased to 69 in 2015 while it was 64 for boys.
Not just average score, girls score more across subjects
In 2015, barring three language subjects — Urdu Core, French and German — the average of score of girls was higher in all others, our analysis shows. In psychology, while girls got an average score of 75, it was 65 for boys, a difference of 10 marks. In economics and sociology, the difference stood at eight marks.
Note: Students’ gender—not available in the results database accessed by HT—was estimated from their names. To do this, we queried a name-gender database prepared from various public sources. If at least 90% of a student’s first name or last name belong to the male or female name dataset only, and if there were at least 30 instances of the said first name or last name in the database, the student was assigned the respective gender.
If a name seemed ambiguous—less than 90% of people belonged to a single gender—it was not included while calculating gender-based statistics. Using this methodology, 88% students were classified.
