Faculty Performance Appraisal | Original Article

ABSTRACT:

Appraisal as a lively process produces data, which acts as a performance indicator for an individual and subsequently impacts on the decision making of the stakeholder’s as well as the individual. The idea proposed in this paper is to perform an analysis considering number of parameter s for the derivation of performance prediction indicator’s needed for faculty performance appraisal, monitoring and evaluation. The aim is to predict the quality, productivity and potential of faculty across various disciplines which will enable higher level authorities to take decisions and understand certain patterns of faculty motivation, satisfaction, growth and decline. The analysis depends on many factors, encompassing student's feedback, organizational feedback, institutional support in terms of finance, administration, research activity etc. The data mining methodology used for extracting useful patterns from the institutional database is able to extract certain unidentified trends in faculty performance when assessed across several parameters.