Predictors of Student Productivity in Biomedical Graduate School Applications.
Predictors of Student Productivity in Biomedical Graduate School Applications.
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DOI：
10.1371/journal.pone.0169121
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发表时间：
2017
期刊：
影响因子：
3.7
通讯作者：
Cook JG
中科院分区：
文献类型：
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作者：
Hall JD;O'Connell AB;Cook JG
许多美国生物医学博士课程每年收到的入学申请比他们可以接受的更多，因此需要选择性录取过程。典型的选择标准包括标准化考试成绩，本科平均成绩，推荐信，简历和/或个人陈述，强调相关的研究或专业经验，以及培训教师的面试反馈。录取决定通常是建立在假设这些应用程序组件与研究生院的研究成功相关，但这些假设没有经过严格的测试。我们试图确定是否有任何应用程序组件可以预测通过第一作者学生出版物和完成学位的时间来衡量的学生生产力。我们收集了2008-2010年进入查佩尔山的北卡罗来纳州大学第一年生物医学博士课程的研究生的生产力指标，并分析了他们的入学申请的组成部分。我们发现，在那些被录取并选择在斯坦福大学入学的申请人中，考试成绩、成绩、以前的研究经验或教师面试评分与高或低的生产力之间没有相关性。相比之下，推荐信作者对在研究生院发表多篇第一作者论文的学生的评分明显高于那些在同一时间段内没有发表第一作者论文的学生。我们的结论是，最常用的标准化考试（一般GRE）是一个特别无效的预测工具，但定性评估由以前的导师更有可能确定学生谁将成功地在生物医学研究生的研究。基于这些结果，我们得出结论，招生委员会应避免过度依赖应用程序的任何单一组件，并不再强调对学生生产力预测最低的指标。我们建议持续跟踪所需的培训成果，并结合对招生实践的回顾性分析，以指导申请要求和整体申请审查。
Many US biomedical PhD programs receive more applications for admissions than they can accept each year, necessitating a selective admissions process. Typical selection criteria include standardized test scores, undergraduate grade point average, letters of recommendation, a resume and/or personal statement highlighting relevant research or professional experience, and feedback from interviews with training faculty. Admissions decisions are often founded on assumptions that these application components correlate with research success in graduate school, but these assumptions have not been rigorously tested. We sought to determine if any application components were predictive of student productivity measured by first-author student publications and time to degree completion. We collected productivity metrics for graduate students who entered the umbrella first-year biomedical PhD program at the University of North Carolina at Chapel Hill from 2008–2010 and analyzed components of their admissions applications. We found no correlations of test scores, grades, amount of previous research experience, or faculty interview ratings with high or low productivity among those applicants who were admitted and chose to matriculate at UNC. In contrast, ratings from recommendation letter writers were significantly stronger for students who published multiple first-author papers in graduate school than for those who published no first-author papers during the same timeframe. We conclude that the most commonly used standardized test (the general GRE) is a particularly ineffective predictive tool, but that qualitative assessments by previous mentors are more likely to identify students who will succeed in biomedical graduate research. Based on these results, we conclude that admissions committees should avoid over-reliance on any single component of the application and de-emphasize metrics that are minimally predictive of student productivity. We recommend continual tracking of desired training outcomes combined with retrospective analysis of admissions practices to guide both application requirements and holistic application review.