Design of Autonomous Learning Ability Evaluation System Based on Maximum Subordination Principle and Weight Strategy
ZHAO Weizhou
WANG Huizhen
ZHANG Hui
JING Huili
Abstract：Aiming at the problems such as too many influence factors and evaluation data in autonomous learning abili-ty ,self-evaluation model is researched and self-evaluation system is designed based on weight strategy and maximum subordi-nation principle .Firstly ,considering that excellent ,medium and poor are fuzzy concepts ,the membership functions of these three standard modes are defined .Secondly ,by analyzing main factors and sub factors ,an indictor system is built for autono-mous learning evaluation .Finally ,an autonomous learning ability self-evaluation model and a system are given .Experiment show that ,this system need not too much experts' intervention ,moreover ,it can rapidly and accurately present autonomous learning ability evaluation results according to the self-evaluation indictor information .
Keywords：autonomous learning abilitymaximum subordination principleweight
Publication Date：2015-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 1981-1984 )