An Automatic Educational Quality Evaluation Fuzzy System (original) (raw)
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Using Fuzzy Techniques for Students' Evaluation
2010
The learning evaluation process tries to establish the degree of students' knowledge and competence assimilation. There are many learning evaluation methods from both pedagogical and system approach point of view. In this work we present a students' system evaluation based on fuzzy techniques. The proposed algorithm implementation is realized in Java. The importance and the role of fuzzy evaluation topics in the domain of evaluation of learning performance are discussed. Some connections and applications of these topics with the content of consecrated topics in a university environment examination are explored. A special emphasis is given to the applications of classical and fuzzy logic in the process of aggregation of specialist opinions.
Fuzzy Logic Based Students Performance Analysis Model for Educational Institutions
International Journal of Research IMSEC Ghaziabad, India, 2010
Students play a very important role in the growth of any institute. Basically the rating or ranking of any institute fully depends upon the performance of its students. The performance of a student includes two major factors: one is the marks obtained and other is the number of classes that he/she attended i.e. attendance. It's very necessary to monitor these two factors for a good result and a smooth growth of any institute. This paper presents a methodology to improve these two factors by analyzing the performance of individual student. For this purpose, the whole data i.e. obtained marks and attendance is divided into various ranges. This can be easily done by fuzzy logic system. A fuzzy system is a mathematical model that analyzes input values in terms of logical values. While variables in mathematics take numerical values, in fuzzy logic applications, the non-numeric linguistic variables are often used to facilitate the expression of rules and facts. This paper includes the role of fuzzy logic, fuzzy system, various characteristics of fuzzy logic system, linguistic variables, rules and membership functions and the implementation of performance analysis methodology with the help of fuzzy logic system.
Fuzzy Logic Theory and Applications in Uncertainty Management of Linguistic Evaluations for Students
Cases on Technologies in Education from Classroom 2.0 to Society 5.0, 2021
Fuzzy logic can deal with information arising from perception and cognition that is uncertain, imprecise, vague, partially true, or without sharp boundaries. Fuzzy logic can be used for assigning linguistic grades and for decision making and data mining with those linguistic grades by teachers, instructors, and professors. Many aspects of fuzzy logic including fuzzy sets, linguistic variables, fuzzy rules, fuzzy math, fuzzy database queries, computational theory of perceptions, and computing with words are useful in uncertainty management of linguistic evaluations for students. This chapter provides many examples of this after describing the theory of fuzzy logic.
Fuzzy Logic Performance Analysis Model for Students
International Conference on Operations and Management Sciences – 2010 (ICOMS – 10), IMT Nagpur, 2010
The role of students in developing a country is huge. Research has demonstrated that college outcomes are tied to the effort that students put into their work and the degree to which they are involved with their studies and campus life. Students play a very important role in the growth of any institute. Basically the rating or rank of any institute fully depends upon the performance of the students. The performance of the student includes certain major factors like Communication skill, knowledge of student, presentation skill, notebook/documents preparation skill and the basic skill(one is the marks obtained and other is the number of classes that he/she attended i.e. attendance). It's very necessary to monitor these factors for good result and a smooth growth of any institute. In this paper we present a methodology to improve these factors by analyzing the performance of individual student. For this purpose, we divided the whole data into various ranges. This can be easily done by fuzzy logic system. A fuzzy system is a mathematical model that analyzes input values in terms of logical values. While variables in mathematics take numerical values, in fuzzy logic applications, the non-numeric linguistic variables are often used to facilitate the expression of rules and facts. This paper includes the role of fuzzy logic, fuzzy system, various characteristics of fuzzy logic system, linguistic variables, rules and membership function and the implementation of performance improvement methodology with the help of fuzzy logic system.
Evaluating Students' Performance using Fuzzy Logic
2012
results give motivation and encouragement to the students. So reforms in education are must not only in curriculum development but also in students" performance assessment. Proposed method is useful when questions in the examination are of subjective or objective type and total time duration is given to attempt all questions rather than individual question. This method considers importance and complexity of question into account. It makes use of fuzzy inference system (FIS) and fuzzy logic.
PROCEEDINGS OF THE 45TH INTERNATIONAL CONFERENCE ON APPLICATION OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE’19), 2019
The main goal of this research is to introduce and justify the use of fuzzy logic in the process of evaluation of test results in English of university students majoring in Computer Science. More specifically, the authors aim at implementing a fairer assessment of students' knowledge and skills for borderline cases between two grades without that changing the overall group score.
A NEW FUZZY APPROACH FOR TEACHER'S PERFORMANCE EVALUATION
International Research Journal of Modernization in Engineering Technology and Science, 2020
Teacher evaluation by students is done in most educational systems to improve the quality of education as well as the teacher's own awareness of strengths and weaknesses. The summative assessment is performed at the end of the semester by asking students to evaluate aspects of the teacher and the course. Although these scores are generally linguistic, they are converted into crisp numbers that cannot completely cover the ambiguity of the words. In this paper, a new fuzzy approach is proposed that considers the vagueness and uncertainty of words throughout the evaluation process. Instead of a crisp number, linguistic words are used in the evaluation process. The proposed approach uses the Perceptual Computer (Per-C) and the Linguistic Weighted Average (LWA). To show the effectiveness of the proposed methodology, a case study with real data in Jahrom University was conducted. The results demonstrate that the proposed approach provides an effective teacher evaluation.
A fuzzy system for evaluating students’ learning achievement
The proper system for evaluating the learning achievement of students is the key to realizing the purpose of education. In recent years, several methods have been presented for applying the fuzzy set theory in the educational grading systems. In this paper, we propose a method for the evaluation of students’ answerscripts using a fuzzy system. The proposed system applies fuzzification, fuzzy inference, and defuzzification in considering the difficulty, the importance and the complexity of questions. The transparency, objectivity, and easy implementation of the proposed fuzzy system provide a useful way to automatically evaluate students’ achievement in a more reasonable and fairer manner. 2008 Elsevier Ltd. All rights reserved.
Fuzzy Approach For Students Performance Evaluation
The common, traditional practice in most higher learning institutions is to evaluate students' performances based on their academic achievements. Recently, the need to combine other factors to enhance the evaluation of students has been recognized and were implemented in many academic institutions. Student's achievement evaluation is important in fulfilling the recruitment requirements in many organizations. Organizations in various industries are not only looking for graduates with excellent academic grades but also those graduates whom are equipped with other criteria such as holding soft-skills ability, are pro-active and independent, and having leadership capability. Thus, evaluating students' performances has become a challenge for universities to ensure that students are rewarded accordingly. In general, the evaluations of student's academic achievement usually involve a number of judgments and are based on imprecise data. However, the major limitation in the current academic evaluation include the lack of information behind the evaluation method used and the criteria considered in classifying the student's grade. Therefore, this research investigates the implementation of fuzzy logic in student's achievement evaluation. Fuzzy terms can be used to represent academic performance evaluation that involves the measurement of capability, know-how and skill. Hierarchical fuzzy approach was used to evaluate student's achievement and further classified into certain group of classes. In this case, reasoning based on fuzzy approach is likely to offer an alternative way of handling imprecise data, especially in making decisions and judgments.
Fuzzy Logic Based Evaluation of Performance of Students in Colleges
Performance of students in colleges is difficult to assess before the final results are declared. The performance depends on many factors such as student attendance, teaching effectiveness, facilities etc. Generally, when one is interested in assessing these dependency factors, a physical inventory of the items involved is done and a decision is recommended to the management. But its impact on performance of students is not carried out. This paper aims at presenting the idea of evaluating this performance using fuzzy logic. The paper describes the procedure that can be used to assess the performance of students. The process is based entirely on the principle of taking non-precise inputs on the factors affecting the performance: student attendance, teaching effectiveness and infrastructure facilities and subjecting them to fuzzy arithmetic and obtaining a crisp value of the performance. It is quite clear from the paper itself that this method can be used in practice to analyse further with more additional factors affecting the performance.