Ranking of educational institutes starts gaining a significant attention among all the stakeholders to know the comparative status of the institutes. This paper presents a comprehensive ranking framework based on fuzzy logic using multiple criteria proposed in National institutional ranking framework (NIRF). The proposed model presents a hierarchical structure of metrics proposed by NIRF to measure the performance attributes and then the overall performance of the institute. Mamdani fuzzy reasoning approach has been adopted to address the inexact causal relationship between the leading (input) and the lagging (output) metrics. Finally, the behaviour of the responses produced by the proposed model has been analyzed and also a comparative study has been conducted between National institutional ranking framework (NIRF) and rankings with proposed rankings system for various institutes.
Teaching learning process is one of the important aspects in academic performance evaluation of students. This gives an idea of how much a student has gained the knowledge and skill in a particular subject during the entire season. In this paper, a multi criteria-based decision support system based on six levels of revised Bloom’s cognitive domain has been presented to measure the cognitive knowledge and skill acquired by a student. The fuzzy set theoretic approach has been adopted to overcome the vagueness/fuzziness present in the evaluation process and the inexact causal relationship between input and output parameters has been addressed using the Mamdani fuzzy IF-THEN rules. Finally, a comparative study has been depicted between the marks obtain by a group of students in the exam with their cognitive knowledge score.
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