Study on evaluation method of online education reform effect based on analytic hierarchy process
Minglun Wu
Abstract
Minglun Wu
Abstract
In order to overcome the problems of low accuracy and long time-consuming of the effect evaluation method, this paper proposes an evaluation method of the effect of education reform based on AHP. First, the reform effect evaluation system was established to obtain 22 evaluation indicators such as the number of login platforms and the time of watching videos; Secondly, the factor set is determined by analytic hierarchy process (AHP), and the evaluation judgement matrix is constructed. The rationality of the matrix is verified by consistency test. Finally, the index weight and membership vector are calculated by AHP, and the comprehensive score of the reform effect of the membership vector is obtained by grade assignment method. The results show that the evaluation accuracy of the proposed method can reach 100%, and the evaluation time is only 7.59 s, indicating that the proposed method can improve the evaluation effect.
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In order to overcome the problems of low accuracy and long time-consuming of the effect evaluation method, this paper proposes an evaluation method of the effect of education reform based on AHP. First, the reform effect evaluation system was established to obtain 22 evaluation indicators such as the number of login platforms and the time of watching videos; Secondly, the factor set is determined by analytic hierarchy process (AHP), and the evaluation judgement matrix is constructed. The rationality of the matrix is verified by consistency test. Finally, the index weight and membership vector are calculated by AHP, and the comprehensive score of the reform effect of the membership vector is obtained by grade assignment method. The results show that the evaluation accuracy of the proposed method can reach 100%, and the evaluation time is only 7.59 s, indicating that the proposed method can improve the evaluation effect.
Key concepts: Analytic hierarchy process, Set (abstract data type), Judgement, Weight, Evaluation methods, Computer science, Consistency (knowledge bases), Matrix (chemical analysis)