Job Prediction for Students and Program Approval in Universities

There is a problem of unemployment for students graduating from various programs in institutions across India. It is primarily due to lack of information about the employability of people graduating from institutions, especially in particular programs and courses. There is thus a need to know the employment potential of programs beforehand for mitigating unemployment issues. The All-India Council for Technical Education (AICTE), under the Department of Higher Education, is a statutory advisory body for technical education throughout India. The AICTE grants approval for the establishment of technical institutions and programs. In the current situation, it is necessary to determine if a program in a particular institution will engender sufficient employment. The objective is to, based on its performance, determine if a program is eligible to be started or continued, and also assess the improvements needed. The proposed study has been premised upon a framework design with an algorithm for evaluating performance of different programs in universities, and prediction of employability in students graduating from them using data mining. The above findings help to predict if a course is eligible for approval or continuation, using variety of present and historical student and institutional data. The algorithm supports AICTE grant approval for programs in different institutions and also aids in syllabus revision in order to keep up with current job market.