Ordering, distance and closeness of fuzzy sets
Fuzzy Sets and Systems - Special issue on fuzzy data analysis
An application of fuzzy sets in students' evaluation
Fuzzy Sets and Systems
Guaranteed accurate fuzzy controllers for monotone functions
Fuzzy Sets and Systems
New methods for students' evaluation using fuzzy sets
Fuzzy Sets and Systems
Parameter conditions for monotonic Takagi-Sugeno-Kang fuzzy system
Fuzzy Sets and Systems - Fuzzy systems
Criterion Based Assessment Using the Support of a Computer
HICSS '02 Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS'02)-Volume
Automatically constructing grade membership functions of fuzzy rules for students' evaluation
Expert Systems with Applications: An International Journal
On the use of fuzzy inference techniques in assessment models: part I--theoretical properties
Fuzzy Optimization and Decision Making
On the use of fuzzy inference techniques in assessment models: part II: industrial applications
Fuzzy Optimization and Decision Making
Expert Systems with Applications: An International Journal
On the monotonicity of hierarchical sum--product fuzzy systems
Fuzzy Sets and Systems
IEEE Transactions on Fuzzy Systems
Fuzzy interpolative reasoning via scale and move transformations
IEEE Transactions on Fuzzy Systems
Fuzzy Interpolation and Extrapolation: A Practical Approach
IEEE Transactions on Fuzzy Systems
Fuzzy set approach to the assessment of student-centered learning
IEEE Transactions on Education
An approach to automatic learning assessment based on the computational theory of perceptions
Expert Systems with Applications: An International Journal
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Hybrid approaches for approximate reasoning
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Computational intelligence models for image processing and information reasoning
Hi-index | 12.05 |
The main aim of criterion-referenced assessment (CRA) is to report students' achievements in accordance with a set of references. In practice, a score is given to each test item (or task). The scores from different test items are added together and then projected or aggregated, usually linearly, to produce a total score. Each component score can be weighted before being added together in order to reflect the relative importance of each test item. In this paper, the use of a fuzzy inference system (FIS) as an alternative to the conventional addition or weighted addition in CRA is investigated. A novel FIS-based CRA model is presented, and two important properties, i.e., the monotonicity and sub-additivity properties, of the FIS-based CRA model are investigated. A case study relating to assessment of laboratory projects in a university is conducted. The results indicate the usefulness of the FIS-based CRA model in comparing and assessing students' performances with human linguistic terms. Implications of the importance of the monotonicity and sub-additivity properties of the FIS-based CRA model in undertaking general assessment problems are discussed.