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Abstract:
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Multiple Criteria Decision Making (MCDM) has recently been recognized as an efficient statistical technique to describe situations where there is a need for integration of the results of different studies to make an overall judgement. Many case studies and applications are available covering different domains of MCDM methods. In this study, we apply TOPSIS method--one of the most classical MCDM methods that was first developed by Hwang and Yoon--to rank the instructors based on several criteria, such as, students' attendance, quiz, project, and exam. Data were collected from an introductory statistics course taught at IUPUI. Twelve sections of the same course were offered and taught by the three instructors for the academic year 2014-15. The course was run under the supervision of a course coordinator, and instructors used the same standard PowerPoint lecture notes and followed the same evaluation criteria. Due to the variations among the scores under each evaluation criteria, we obtained entropy weights of these criteria and then incorporated into the TOPSIS technique to calculate an overall 'composite index' for the instructors to arrive at their individual rankings.
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