Universities should enrol equal numbers of male and female students in all subjects. Do you agree or disagree?

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The idea that
universities
should receive an equal amount of
gender
in each course is a frequent topic of discussion.
This
essay disagrees with
this
idea completely because it reduces academic competition and increases
gender
discrimination.
To begin
with,
universities
should consider students based on their abilities and profiles. Limiting application by
gender
will make qualifying conditions unfair for some people that have high potential. Each person has different strengths, weaknesses, attitudes, skills. These factors should be considered rather than their physical.
For example
, in computer programming, men usually perform better than women and have a higher chance to be programmers in the future. Forcing a number of
genders
to be equal might reduce the number of quality programmers that the
universities
can produce yearly.
Moreover
, equalization of
gender
doesn't give positive goodness to
universities
,
instead
, it provokes inequality of
genders
. Recently,
genders
are not classified only as male and female. There are other types of
genders
that should be accepted
such
as LGBTQ. Classification of male and female will leave a question to other
genders
and can misguide to an intention of
gender
discrimination from the university. In conclusion,
universities
should not use
gender
as a factor to
enroll
Change the spelling
enrol
show examples
students in all subjects because it will not qualify the most suitable person to study in a subject and it can create misunderstanding of
gender
perspective from the university. In my opinion,
universities
are academic providers. The provider should focus only on developing the potential of a student. There is no evidence proving that
gender
is related to academic excellence.
Therefore
, they should not make the number of males and females equal in all subjects.ควย
Submitted by ekkawin.v on

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Topic Vocabulary:
  • gender equality
  • stereotypes
  • workforce
  • discrimination
  • gender biases
  • STEM (Science, Technology, Engineering, Mathematics)
  • humanities
  • underrepresentation
  • meritocracy
  • quotas
  • academic standards
  • qualifications
  • personal interest
  • enforced gender parity
  • dropout rates
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