Using Gaussian membership functions for improving the reliability and robustness of students' evaluation systems
Using Gaussian membership functions for improving the reliability and robustness of students' evaluation systems
复制标题
DOI：
10.1016/j.eswa.2010.12.048
复制
发表时间：
2011-06-01
影响因子：
8.5
通讯作者：
Hameed, Ibrahim A.
中科院分区：
文献类型：
--
作者：
Hameed, Ibrahim A.
本文将介绍一种更可靠的基于高斯隶属函数的学生评价系统。该方法被建模为一个三节点模糊系统。三个节点中的每一个都应用模糊化、模糊推理和去模糊化来考虑问题的难度、重要性和复杂性。第一个节点计算问题的难度，作为问题的模糊化平均准确率和平均时间率的函数。第二个节点计算回答问题的成本，作为其难度和复杂性的函数。第三个节点计算问题所需的调整程度，作为其答案成本和重要性的函数。问题的准确率和回答时间率是从学生的答案脚本中获得的，而问题的复杂性和重要性是由领域专家获得的，即，教师和/或考官。为了提高系统的可靠性和鲁棒性，提出了高斯隶属函数（MF）作为传统三角形MF的替代。(C)2010爱思唯尔有限公司版权所有。
In this paper, a more reliable system of student evaluation based on gaussian membership functions will be introduced. The proposed method is modeled as a three fuzzy nodes system. Each of the three nodes applies fuzzification, fuzzy inference, and defuzzification in considering the difficulty, importance and complexity of questions. The first node computes the difficulty of questions as a function of the fuzzified average accuracy and average time rates of questions. The second node computes the cost of answering questions as a function of its difficulty and complexity. The third node computes the degree of adjustment required by questions as a function of its answer-cost and importance. The accuracy and answer-time rates of questions are obtained from students' answerscripts while the complexity and importance of questions are obtained by a domain expert, i.e., teachers and/or examiners. In order to improve the reliability and robustness of the system, Gaussian membership functions (MFs) are proposed as an alternative to the traditional triangular MFs. (C) 2010 Elsevier Ltd. All rights reserved.