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Introduction <p>The era of big data necessitates a digital transformation in higher education, yet current biomedical curricula in China often fail to meet the interdisciplinary demands of the field.</p> Methods <p>To identify critical bottlenecks, this study conducted a validated questionnaire survey (Cronbach’s α = 0.73) among 108 graduate program applicants from diverse Chinese universities. Data were analyzed using descriptive statistics, Spearman correlation, and multivariable logistic regression to quantify the impact of research experiences on student anxiety.</p> Results <p>It has been identified that domestic universities exhibit significant shortcomings in several areas, including the curriculum system, practical resources, and mentoring models. The findings revealed that a significant structural deficiency exists, with 70.37% of students lacking systematic big data training. Furthermore, while 62.04% possess only basic experimental skills, only 37.96% demonstrate proficiency in data analysis. Furthermore, 84.26% reported a critical lack of access to experimental equipment, and 81.48% rely heavily on traditional one-on-one mentorship. Notably, students with prior research experience exhibited significantly higher anxiety regarding competitive pressure (<i>P</i> = 0.039).</p> Discussion and conclusion <p>Addressing these disparities, we propose a “Curriculum-Platform-Evaluation” (CPE) integrated reform model. This framework leverages big data to restructure tiered curricula, establish virtual-physical fusion platforms, and implement dynamic evaluation, offering a scalable pathway for cultivating innovative biomedical talent.</p>

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Big data driven integration of curriculum platform and evaluation for reforming biomedical education in China

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年8月4日

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  • Lin Ye,
  • Ming Liu,
  • Taiwen Li,
  • Yu Zhou,
  • Xikun Zhou,
  • Jing Li

摘要

Introduction

The era of big data necessitates a digital transformation in higher education, yet current biomedical curricula in China often fail to meet the interdisciplinary demands of the field.

Methods

To identify critical bottlenecks, this study conducted a validated questionnaire survey (Cronbach’s α = 0.73) among 108 graduate program applicants from diverse Chinese universities. Data were analyzed using descriptive statistics, Spearman correlation, and multivariable logistic regression to quantify the impact of research experiences on student anxiety.

Results

It has been identified that domestic universities exhibit significant shortcomings in several areas, including the curriculum system, practical resources, and mentoring models. The findings revealed that a significant structural deficiency exists, with 70.37% of students lacking systematic big data training. Furthermore, while 62.04% possess only basic experimental skills, only 37.96% demonstrate proficiency in data analysis. Furthermore, 84.26% reported a critical lack of access to experimental equipment, and 81.48% rely heavily on traditional one-on-one mentorship. Notably, students with prior research experience exhibited significantly higher anxiety regarding competitive pressure (P = 0.039).

Discussion and conclusion

Addressing these disparities, we propose a “Curriculum-Platform-Evaluation” (CPE) integrated reform model. This framework leverages big data to restructure tiered curricula, establish virtual-physical fusion platforms, and implement dynamic evaluation, offering a scalable pathway for cultivating innovative biomedical talent.