Authors :
Dr. M. Pushpalatha; Raya Bandyopadhyay
Volume/Issue :
Volume 7 - 2022, Issue 1 - January
Google Scholar :
http://bitly.ws/gu88
Scribd :
https://bit.ly/3AFgncf
DOI :
https://doi.org/10.5281/zenodo.5905213
Abstract :
Our aim in this project, will be to identify Key
Performance Indexes that can define a student's level of
comprehension after studying certain classes and how we
can apply those Key Performance Indexes in classification
or even use them to calculate the success rate of skills, in
universities or even place specific students in areas where
they can succeed. We can also analyse which data mining
algorithm gives us the highest accuracy based on our data
and, address some of the open problems we may
encounter as we go along, based on existing research
literature.
Understanding the learner's in-depth thinking
process after a lesson or series of lessons, will give us more
information about where the student is lacking or
whether the skills are lacking, in the event that most
students seem to lack a certain pattern. This shall enable
more fluid methods for students and academics to be
classified into a system, we can categorize them based on
class performances or regular assignments, and find a
system which shall give us an understanding about the
grasp of a particular student in a certain subject and
eventually, the group of students performing well in
certain subjects can be placed in opportunities which shall
enhance their skill sets and help them pick a customized
career for them.
The use of multi-phase analysis and cluster analysis
is intended to be based on data on which Key
Performance Indexes will be determined at the end. Based
on these determining Key Performance Indexes, we can
access important information and, if possible, present it
on a working dashboard.
Our aim in this project, will be to identify Key
Performance Indexes that can define a student's level of
comprehension after studying certain classes and how we
can apply those Key Performance Indexes in classification
or even use them to calculate the success rate of skills, in
universities or even place specific students in areas where
they can succeed. We can also analyse which data mining
algorithm gives us the highest accuracy based on our data
and, address some of the open problems we may
encounter as we go along, based on existing research
literature.
Understanding the learner's in-depth thinking
process after a lesson or series of lessons, will give us more
information about where the student is lacking or
whether the skills are lacking, in the event that most
students seem to lack a certain pattern. This shall enable
more fluid methods for students and academics to be
classified into a system, we can categorize them based on
class performances or regular assignments, and find a
system which shall give us an understanding about the
grasp of a particular student in a certain subject and
eventually, the group of students performing well in
certain subjects can be placed in opportunities which shall
enhance their skill sets and help them pick a customized
career for them.
The use of multi-phase analysis and cluster analysis
is intended to be based on data on which Key
Performance Indexes will be determined at the end. Based
on these determining Key Performance Indexes, we can
access important information and, if possible, present it
on a working dashboard.
