  In recent years, the role of big data analytics has exponentially grown and
is now slowly making its way into the education industry. Several attempts are
being made in this sphere in order to improve the quality of education being
provided to students and while many collaborations have been carried out
before, automated scoring of answers has been explored to a rather limited
extent. One of the biggest hurdles to choosing constructed-response assessments
over multiple-choice assessments is the effort and large cost that comes with
their evaluation and this is precisely the issue that this project aims to
solve. The aim is to accept raw-input from the student in the form of their
answer, preprocess the answer, and automatically score the answer. In addition,
we have made this a real-time system that captures "snapshots" of the writer's
progress with respect to the answer, allowing us to unearth trends with respect
to the way a student thinks, and how the student has arrived at their final
answer.
