Computational Intelligence for Mapping Academic Competency in Technical Institutes

This thesis deals with two of the most important competency mapping aspects of faculty members in technical institutes: Allocation of academic load to faculties using computational intelligence and subsequently, determining variable pay of faculties in proportion to performance. In this study both the objectives have been dealt with proven computational approaches. The motivation behind the objectives stemmed from a very appalling problem i.e. lack of employability skills in technical graduates. The ischolar_main cause of the problem reveals several contributing factors, but the one factor which can be isolated, is the impact of the faculty members. The faculty members are at the helm of an eûective teaching learning process and have a major impact on students’ achievements. This necessitates that the faculty members be motivated enough to have the required impact. In this context two aspects that are of paramount importance for the performance of a faculty are: being in the right place in terms of teaching load and getting rewards in tandem with performance. The research was conducted using various data of faculty members of a technical institute.