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Impact of contextual factors on the evaluation outcomes of national virtual simulation experimental teaching projects in biology and medicine

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  • Zhou, Zhengmei
  • Zhao, Shidi
  • Lin, Ye
  • Li, Yan

Abstract

The number of applications for National Virtual Simulation Experimental Teaching Projects (NVSETPs) in China has seen a significant increase. Consequently, the influence of contextual factors and their potential personal connections on the evaluation results, whether for national or non-national NVSETPs, has become a prominent concern. In this study, we employed a modified back-chaining method using logistic regression to examine whether contextual factors in NVSETP applications could explain the evaluation outcomes. Our analysis was based on data available on the open platform of China's Ministry of Education (MOE). We identified several significant influencing factors, including the score on a five-point rating system, the number of clicks on the application page, school quality, school region, and the gender, title, and position of the applicants. Our results shed light on the impact of contextual factors on the evaluation results of NVSETPs in the fields of biology and medicine, using a modified back-chaining method. We conclude that enhancing the transparency of the assessment process and implementing standardized, detailed scoring guidelines for NVSETPs would mitigate the negative influence of contextual factors.

Suggested Citation

  • Zhou, Zhengmei & Zhao, Shidi & Lin, Ye & Li, Yan, 2024. "Impact of contextual factors on the evaluation outcomes of national virtual simulation experimental teaching projects in biology and medicine," Evaluation and Program Planning, Elsevier, vol. 106(C).
    • Handle: RePEc:eee:epplan:v:106:y:2024:i:c:s0149718924000727
    DOI: 10.1016/j.evalprogplan.2024.102470
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    References listed on IDEAS

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    1. Yin, Zhifeng & Liang, Zheng & Zhi, Qiang, 2018. "Does the concentration of scientific research funding in institutions promote knowledge output?," Journal of Informetrics, Elsevier, vol. 12(4), pages 1146-1159.
    2. Ying Ma & Yandong Zhao & Xu Gong & Li Sun & Yonghe Zheng, 2018. "Close the gender gap in Chinese science," Nature, Nature, vol. 557(7703), pages 25-27, May.
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