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students from various demographics being ignored.
Further, these students
have no mechanism to get
feedback on how their skills
compare to those required
by the industry.
Having systems that can
intelligently and scalably
assess a wide variety of
skills is essential to address-
ing this broader problem
affecting every modern-day
spoken skills using such
formats over MCQs. Evalu-
ating such responses is an
expensive, time-consuming
process involving human
graders, and suffers from
standardization concerns.
Automated grading has the
potential to address these
issues and impact millions
of job seekers, trainers,
and corporations.
At Aspiring Minds, we
have, over the last decade,
distilled a framework to cast
the question of subjective
assessments as problems in
computer science, and spe-
cifically, in machine learn-
ing (ML).
1 In it, candidate
responses are data points in
a high dimensional space,
from which we predict their
true, latent, underlying
score. This is a different
paradigm altogether that
we envision. While there
labor market. Aspiring Minds
was formed 10 years ago to
address this challenging
problem. We have devel-
oped a scalable platform to
deliver standardized assess-
ments to test job skills. The
platform tests more than
two million students every
year and is used by 5,000+
companies including 100+
Fortune 500 companies.
A particular challenge
in designing scalable assessment technologies
is evaluating subjective,
open-ended responses
to questions. Such questions directly simulate a
skill or a job task within
the constraints of a test-like environment and are
generally more informative
than multiple-choice questions (MCQs). For instance,
it is almost necessary to
evaluate programming or
UPWARD OF FOUR million gradu- ates enter the labor market every year in India alone.
India boasts of a large
services economy, wherein
a single company hires
thousands of new employees every year. Meanwhile,
product companies and
small and medium enterprises (SMEs) look for a
few skilled people each.
This requires cost-effective and scalable methods
of hiring. Interviewing
every applicant is not a
feasible solution.
On the other hand,
graduates from 30,000+
institutes of higher education spread across 20+ Indian states face a constant
challenge in signaling their
competence to potential
employers. Companies,
most of which are located
in the top 20 biggest cities
in the country, bias their
search by relying on proxies
like university name and
the city a college is located
in. Applying such crude
filters results in meritorious
A particular challenge in
designing scalable assessment
technologies is evaluating
subjective, open-ended
responses to questions.
JOB PLACEMENT | DOI: 10.1145/3355268
Skill Evaluation
BY SHASHANK SRIKANT, ROHIT TAKHAR,
VISHAL VENUGOPAL, AND VARUN AGGARWAL
