Author(s)

ZiYuan Guo^*, Yue Wang, XinRu Yin

Affiliation(s)

Department of Economics, Shanxi Engineering Science and Technology Vocational University, Jinzhong 030600, Shanxi, China.

Corresponding Author

ZiYuan Guo

ABSTRACT

With the rapid development of artificial intelligence, the application of intelligent marking system in exam marking has become the core direction of education. As this intelligent marking system involves the influence of a variety of human, machine and other subjective and objective factors, its evaluation accuracy may be subject to certain limitations, which brings certain challenges to the diversity and complexity of the implementation steps. In response to this problem, this study selects the method of hierarchical analysis (AHP). Firstly, it establishes a systematic a multilevel evaluation framework, and then establishes a systematic and multilevel evaluation framework, and then establishes a scientific multidimensional index system that a data-driven algorithm fusion strategy is proposed. Experimental results show the diversity and complexity of the implementation steps in response to this problem based on the in-depth analysis of the scoring rules by machine learning algorithms, the system can automate the evaluation of open-ended questions, and combine the manual review and data analysis to construct a new evaluation system of "intelligence-led- artificial gatekeeper". The study proves that the AHP algorithm proposed in effectively enhances the accuracy and feedback effect of intelligent assessment, which is a substantial achievement in this field.

KEYWORDS

Multi-level; Data-driven; AHP; Intelligent reviewing

CITE THIS PAPER

ZiYuan Guo, Yue Wang, XinRu Yin. Multidimensional evaluation of an intelligent reviewing system using the Analytic Hierarchy Process (AHP). World Journal of Educational Studies. 2025, 3(6): 13-19. DOI: https://doi.org/10.61784/wjes3084.

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