Analyzing the Difficulty of China's National College Entrance Examination (NCEE) Mathematics Papers: An AHP Approach with Expert Judgment Matrices and Data-Driven Validation ——Evidence from 2024 National Papers A, New Curriculum Standards I & II

Yin Hui(School of Mathematical Sciences, Guizhou Normal University, China)
Yunfei Lu(School of Mathematical Sciences, Guizhou Normal University, China)

Abstract

This study examines the 2024 National College Entrance Examination (NCEE) Mathematics Papers (National Paper A, New Curriculum Standard I and II ) through an integrated methodology combining Analytic Hierarchy Process (AHP) theory, analysis of variance (ANOVA), and Python-based computational analysis. We developed an enhanced difficulty assessment framework featuring an AHP-derived integrated difficulty coefficient model that utilizes expert-constructed judgment matrices for precise factor weighting, overcoming limitations of conventional evaluation approaches. Our Python-powered analytical pipeline enabled comprehensive data processing, visualization of difficulty factor distributions, and rigorous statistical testing. ANOVA results demonstrated no statistically significant differences among the three exam versions across seven core difficulty dimensions: contextual factors, parameter factors, operational proficiency, reasoning ability, knowledge coverage, thinking orientation, and cognitive levels, indicating remarkable stability in overall test difficulty.

Keywords

AHP difficulty model; Comparative study; Analysis of variance; NCEE mathematics assessment; Educational measurement

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DOI: http://dx.doi.org/10.12345/jetm.v9i2.24764