Abstract:
Students that fail courses have to retake those courses, often during regular
semesters, sometimes during summer semesters. Every summer, NUST has
to keep their departments open to o er courses to allow students to graduate
from their programs without incurring excessive delays. The cost of engaging
faculty to stay back for the summer is an additional nancial burden on
universities' budgets. There is a cost to universities even when students retake
courses during regular semesters. These losses and delays are a result
of students failing courses because they underestimate the e ort they need
to put in. In case of elective courses, students sometimes select courses that
are not aligned with their inherent talents and abilities. In this research we
propose to develop an academic grade prediction system (Acad-GPS), which
predicts a student's future grades based on his/her academic history. This
will allow students to prepare themselves for the academic rigour of upcoming
courses. We have formulated this problem as a recommender system problem.
The successful development of Acad-GPS will provide better guidance for
university students, lead to fewer students failing courses, which will not only
result in immediate cost savings to universities and the national exchequer,
but also reduce average graduation times for students, avoid unnecessary
delays of new entrants into the job market.
