A Rough Set Based Total Quality Management Approach in Higher Education - Complex System Modelling and Control Through Intelligent Soft Computations - page 390

Table 2 Attribute normalization and classi cation
S.
no.

Attribute Notation Classi cation

1 Effective learning and teaching a Poor (1)

￿ Appropriateness of learning methods Good (2)

V.good (3)

￿ Curriculum Excellent(4)

￿ Teaching and evaluation

2 Leadership b Poor (1)

￿ Top management composition Good (2)

￿ Departmental/school level supervision V.good (3)

￿ Student leadership Excellent (4)

3 Administrative setup c Poor (1)

￿ Timely availability of information Good (2)

V.good (3)

￿ Implementation of decisions Excellent (4)

￿ Quality of support staff

4 Research d Poor (1)

￿ Faculty research publications Good (2)

￿ Sponsored research projects and consultancy V.good (3)

Excellent (4) ￿ Student research projects

5 Faculty e Poor (1)

￿ Faculty teaching experience Good (2)

￿ Faculty with industrial exposure V.good (3)

￿ Faculty quali cations and communication skills Excellent (4)

6 Industry institute interface f Poor (1)

￿ Special lectures by industrial experts Good (2)

V.good (3)

￿ Industrial tours Excellent (4)

￿ Industrial sponsorship to various events

7 Placement g Poor (1)

￿ Placement cell and staff Good (2)

￿ Campus placements

V.good (3)

￿ Salary package offered Excellent (4)

8 Infrastructure h Poor (1)

￿ Physical environment (class rooms, labs, sports,

canteen)

Good (2)
V.good (3)
Excellent (4) ￿ Academic infrastructure(library, online journals)

￿ Health facilities

9 Students i Poor (1)

￿ Handling of student affairs Good (2)

￿ Monitoring students progress V.good (3)

￿ Student satisfaction

Excellent (4)