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Today, the editor brings you the part of the MULTIMOORA multi-attribute decision-making method of "Multi-attribute Decision-making Methods and Application Research Considering Decision-Maker Behavior in Probabilistic Language Environment".
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Today, the editor brings the MULTIMOORA method of the article "Research on multi-attribute decision making method and its application considering decision makers' behavior in probabilistic linguistic environment".
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1 内容摘要（Content summary）
Today, the editor will interpret and share the MULTIMOORA multi-attribute decision-making method part of "Multi-attribute Decision-making Methods and Application Research Considering Decision-Maker Behavior in Probabilistic Language Environment" from the three sections of "Mind Map, Intensive Reading Content, and Knowledge Supplement".
Today, the editor will interpret and share the MULTIMOORA method of the article "Research on multi-attribute decision making method and its application considering decision makers' behavior in probabilistic linguistic environment" from the three sections of "mind map, intensive reading content, and knowledge supplement".
2 思维导图（Mind mapping）
3 精读内容（Intensive reading content）
The last part of the method introduction is the practical application of the method, and the author uses a case study of the evaluation of the teaching quality of college education as an example to verify the feasibility of the method.
The last section of the method introduces the practical application of the method, using a case study of higher education teaching quality assessment to validate its feasibility.
The author begins with a description of the problem, and the author elaborates on the problem in detail, starting from the research background of the problem. Due to the rapid development of higher education in mainland China in the 21st century, the quality of education and teaching in colleges and universities has become a focus of general attention, and the evaluation of the quality of education and teaching in colleges and universities has also become the focus of many experts and scholars.
The author begins by describing the problem, starting from the research background and elaborating on the issues being studied. With the rapid development of higher education in China in the 21st century, the quality of education and teaching in universities has become a focal point of public attention. Consequently, the assessment of higher education teaching quality has become a key focus of research for many experts and scholars.
At present, the evaluation of the teaching quality of higher education mainly relies on the supervision and evaluation of relevant political and legal departments, school supervision departments and student teachers, which is far from meeting the needs of the complex and dynamic development of higher education, and needs to be further improved.
Currently, the assessment of higher education teaching quality mainly relies on supervision and evaluation by relevant governmental departments, school supervision departments, and feedback from students and teachers. However, this approach still falls short of meeting the complex and dynamic needs of higher education, necessitating further improvement.
According to the author, the current evaluation of the teaching quality of college education is divided into macro level and micro level, the macro level involves the education system, education policy and other aspects, which is related to the national education policy, while the micro level is closer to students, student-centered, and promotes the enthusiasm of teachers in teaching and students' learning.
According to the author, the assessment of higher education teaching quality is divided into macro and micro levels. The macro level involves aspects such as educational systems and policies, which are related to national educational policies. The micro level is more student-centric, aiming to promote the enthusiasm of teachers' teaching and students' learning.
At present, the scoring and evaluation method used by most schools is not good enough, and the evaluators have a vague impression of the evaluation indicators they use, so the use of language variables to evaluate the quality of education and teaching is more in line with realistic decision-making. The improved MULTIMOORA multi-attribute decision-making method based on probabilistic language terminology is student-centered, and the evaluation index system is constructed from four evaluation indicators, emphasizing the subjective position of students.
The conventional scoring evaluation method used by most schools is deemed inadequate, as evaluators often have vague perceptions of the evaluation criteria. Therefore, using linguistic variables to evaluate the quality of education and teaching is deemed more suitable for real-world decision-making. The improved MULTIMOORA method based on probability language terms, used in this instance, places students at the center and constructs an evaluation index system from four evaluation criteria, emphasizing the primacy of students.
Some of the indicators are shown in the table, and each indicator has its own unique and reasonable interpretation of the indicators, covering all aspects of education and teaching.
Some indicators, as shown in the table, each have their unique and reasonable interpretations, covering various aspects of education and teaching.
The first step in the evaluation is to assume the required parameters and let the decision-maker evaluate the different evaluation indicators to construct an initial probabilistic linguistic decision matrix.
The first step in the assessment is to assume the required parameters and allow decision-makers to evaluate different evaluation criteria to construct the initial probability language decision matrix.
The second step is to standardize the evaluation results, firstly, calculate the value matrix and probability weight matrix of the teaching quality of each discipline in the three states, construct the cumulative prospect decision matrix, and then standardize it.
The second step involves standardizing the evaluation results. Initially, the value matrix and probability weight matrix of teaching quality in various subjects under three states are calculated, followed by the construction of the cumulative prospect decision matrix, which is then standardized.
The third and fourth steps are to determine the attribute weights and use the selected method to rank the alternatives, respectively, and it is necessary to use the concept of dominant theory to calculate the numerical result matrix and the normalization matrix, so as to construct the ranking result matrix to determine the final ranking of the teaching quality of each subject.
The third and fourth steps involve determining attribute weights and using the selected method to rank alternative schemes. Here, concepts from dominance theory are used to calculate the numerical results matrix and standardized matrix, constructing the ranking results matrix to determine the final ranking of teaching quality in various subjects.
Chapter 5 also concludes, and this chapter introduces in detail a new multi-attribute decision-making method, that is, the MULTIMOORA method based on the improvement of cumulative prospect theory and probabilistic language terminology, and applies it to the evaluation of the teaching quality of university education, providing new ideas for it.
With this, the fifth chapter concludes, providing a detailed introduction to a new multi-attribute decision-making method, the improved MULTIMOORA method based on cumulative prospect theory and probability language terms, and applying it to the assessment of higher education teaching quality, offering new insights.
4 知识补充（Knowledge supplement）
What is multi-property decision-making?
What is multi-attribute decision-making?
Multi-attribute decision-making, also known as multi-objective decision-making of finite schemes, refers to the decision-making problem of selecting the optimal alternative or ranking the scheme under the condition of considering multiple attributes, which is an important part of modern decision science. Its theories and methods have a wide range of applications in many fields such as engineering, technology, economics, management, and military. The main problem of multi-attribute decision-making is in the evaluation and selection aspects.
Multi-attribute decision-making, also known as multi-objective decision-making, refers to the process of selecting the optimal alternative or ranking alternatives considering multiple attributes. It is an important part of modern decision science and finds wide applications in various fields such as engineering, technology, economics, management, and military. Multi-attribute decision-making mainly addresses the evaluation and selection of alternatives.
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翻译:ChatChat 3.5
Text: Multi-attribute decision_Baidu Encyclopedia (baidu.com)
Reference: Yang Yaxu. Research on multi-attribute decision-making methods considering decision-makers' behaviors in probabilistic language environment and their applications[D]. Baoding: Hebei University, 2023.
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