E3S Web of Conferences (Jan 2021)

Research on the Fairness of MPACC Selection Based on Examiner Heterogeneity

  • Wang Yan,
  • He Zhuqian,
  • Zheng Jingjie

DOI
https://doi.org/10.1051/e3sconf/202123503010
Journal volume & issue
Vol. 235
p. 03010

Abstract

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The selection of MPACC (Master of Professional Accountant) is a key step in the training of senior accounting personnel. This paper examines the relationship between examiner heterogeneity and MPACC second test scores. We try to clarify the reason for the unfair phenomenon because of the heterogeneity of examiners in MPACC second test results and seek ways to solve this problem. The study found that the MPACC second test results are unfair. This unfairness is caused by the heterogeneity of the examiner. However, standardized algorithms balance the differences in MPACC examiner heterogeneity. The regression model was constructed by using the MPACC second test scores before and after standardization, which verified the existence of examiner heterogeneity and the effect of the standardized algorithm on the examiner heterogeneity. This article is based on the differences of MPACC second test scores due to examiner’s heterogeneity. We propose the application of standardized algorithm, which will play an important role in improving the quality of MPACC enrollment and promoting the training of senior accounting personnel.