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Higher education evaluation system based on AHP & EWM

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DOI: 10.23977/aetp.2022.061012 | Downloads: 15 | Views: 731

Author(s)

Xinyue Yang 1, Junqi Yang 1, Yiwei Lu 1

Affiliation(s)

1 Northwest A&F University, Yangling, 712100, China

Corresponding Author

Xinyue Yang

ABSTRACT

As the scope of mental work continues to expand and technology continues to develop, people are more and more concerned about the issue of higher education. In order to measure the health status of the higher education system and evaluate the effectiveness of the policy, we establish the Health Evaluation System of Higher Education and the Prediction Model. task 1 In order to better quantify the criteria of health evaluation, we divide the model into four layers through AHP algorithm, select and define 13 fourth-layer indicators, and use Entropy Weight Method (EWM) to objectively calculate the fourth-layer indicators. The Analytic Hierarchy Process (AHP) is used to calculate the third-level weight. According to the population of different countries, we use the complex method of AHP and EWM and scale the indicator to create a scoring mechanism. In task 2 We firstly apply the model to a number of countries to test its suitability, and the results are in good agreement with the education assessment lists published by the United Nations. And we find that India is a country where there is still room for improvement in the education system. task 3 We propose an attainable and reasonable vison for India’s system that supports a healthy and sustainable system of higher education. task 4 According to the scores of India in various indicators and the total score obtained in task 2, we judge that the score of India is unqualified. task 5 We select three of the lowest scores in India’s higher education system out of 13 indicators, and propose targeted policies and a implementation timeline that will support the migration from current state to your proposed state. task 6 We establish a prediction model based on ARIMA, and substitute time series data into the prediction model to obtain the prediction results. Then, we use AHP and EWM algorithms to calculate the first-level targets for comparison, so as to evaluate the effectiveness of the policies. task 7 We reference and analyze the various situations in India and the real world impact of the implementation plan, find that the change is very difficult, and analyze the feasibility of the policy.

KEYWORDS

Higher education, Health, Sustainability, AHP, EWM, ARIMA

CITE THIS PAPER

Xinyue Yang, Junqi Yang, Yiwei Lu, Higher education evaluation system based on AHP & EWM. Advances in Educational Technology and Psychology (2022) Vol. 6: 75-93. DOI: http://dx.doi.org/10.23977/aetp.2022.061012.

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