A faculty performance evaluation model based on MACBETH and fuzzy filter ranking methods

Area of Science:

• Higher Education Management
• Educational Assessment
• Decision Support Systems

Background:

• Faculty performance evaluation is vital for higher education institutions.
• Existing tools lack usability and do not account for diverse professional tracks in Chinese application-oriented universities.
• There is an unmet need for tailored faculty evaluation management systems.

Purpose of the Study:

• To develop and validate a novel faculty performance evaluation framework for application-oriented universities in China.
• To address the limitations of current evaluation methods by incorporating professional tracks.
• To provide an easy-to-use tool for measuring, ranking, and awarding faculty.

Main Methods:

• A hybrid multi-criteria decision making (MCDM) approach was applied in three steps.
• Development of measurement indicators through literature review and practical assessment forms.
• Utilization of the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) method for criterion weighting based on faculty tracks.
• Application of the Fuzzy Filter Ranking (FFR) approach for faculty performance ranking.

Main Results:

• A validated framework for faculty performance evaluation in application-oriented universities.
• Successful demonstration of the methodology's applicability and utility in a Chinese university case study.
• The system effectively streamlines weight assignment and faculty ranking processes.

Conclusions:

• The proposed framework offers an intuitive and practical solution for faculty performance assessment.
• It serves as an effective evaluation tool and decision-aiding reference for university stakeholders.
• The methodology can be extended to other academic evaluation problems, enhancing educational quality.