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A Fuzzy-Based Assessment Model for Faculty Performance Evaluation. Mohammed Onimisi Yahaya College of Computer Sciences and Engineering King Fahd University of Petroleum and Mineral Dhahran 31261, Saudi Arabia mdonimisi@kfupm.edu.sa. February, 2011. OUTLINE. Introduction
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A Fuzzy-Based Assessment Model for Faculty Performance Evaluation Mohammed OnimisiYahaya College of Computer Sciences and Engineering King Fahd University of Petroleum and Mineral Dhahran 31261, Saudi Arabia mdonimisi@kfupm.edu.sa February, 2011.
OUTLINE • Introduction • Existing assessment model • Background • The Evaluation Model • Results • Conclusions
Introduction (1) • What is Assessment? • -placement • -classification problem • Why is Assessment required? • -required for faculty appraisal • -school placement • -school comparison and ranking • -great role in monitoring and improving the performance of • educational systems
Introduction (2) • Fuzziness in Assessment • questionnaire often contains fuzzy statements such as • -strong • -competent • - unsatisfactory • - agree • - strongly agree etc • Question : How do you measure this ? • - These terms are vague. • Answer: Defuzzify
Background Zhu and Li (2009) presented a combination of fuzzy logic system and neural network model and applied it to teaching quality assessment, Nolan (1998) reported uses of scoring rubrics will help to standardize the grading. Kai et al (2005), investigated and presented the main properties of Fuzzy based assessment models as monotone output property
How Fuzzy Systems Work (1) Knowlegde base (rulebase) Defuzzification Fuzzification Decision making mechanism (Fuzzy reasoning) Figure 1. Fuzzy logic system
How Fuzzy Systems Work (2) Figure2 - The features of a membership function
How Fuzzy Systems Work (3) • What is Fuzzy logic ? • - simple way to arrive at a definite conclusion based upon • vague, ambiguous, imprecise • Fuzzification • - transforming crisp values into grades of membership • for linguistic terms • Fuzzy rule base (knowledge base) • -The rulebase contains the rules and forms • Fuzzy Rule Evaluation (inferencing) • -determine the firing strength of each rule • Defuzzification • -removing the vagueness
The evaluation model (1) Table 1 : Performance evaluation scale Table 2 : Teaching method and Presentation Evaluation Scale
The evaluation model(2) Table 3: Performance Evaluation Criteria
The evaluation model(3) The expected score versus the strength of attribute of an ogive function. Expected score Strength of attribute
The evaluation model(4) Figure 3: range and classes of Teaching Method
The evaluation model(5) Figure 4: range and classes of Presentation and Delivery
Discussion of Result(1) Figure 5: range and classes of Teaching Method
Discussion of Result(3) Figure 6: Three Dimensional Depiction of the inference rules
Discussion of Result(4) Figure 7: Plot to show the effect of Teaching Method and Presentation on performance
Conclusion • In summary, • -we reviewed and presented the following some existing assessment model • -Discussed the concept of fuzzy inference system • -Presented an evaluation model for faculty performance measure satisfying the monotone property of assessment model • Finally, we presented some experimental results and discussion