弗莱堡医学院对学业成功的影响:毕业生调查结果。

GMS Zeitschrift fur Medizinische Ausbildung Pub Date : 2015-10-15 eCollection Date: 2015-01-01 DOI:10.3205/zma000986
Silke Biller, Martin Boeker, Götz Fabry, Marianne Giesler
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引用次数: 0

摘要

目的:本研究旨在利用毕业生调查数据,分析哪些与弗莱堡医学院教学相关的因素会影响学习成功:长期以来,学习成功与否及其影响因素一直是研究的主题,学习成功与否可以用易于量化的指标(期末成绩、学生满意度等)来衡量。近年来,也经常用毕业生的能力水平来评估学习成功与否。毕业生调查被认为是衡量学习成功与否的合适工具:方法:我们利用弗莱堡大学在毕业生毕业一年半后进行的三次毕业生调查数据进行分析。学习成功与否用四个指标来衡量:M2考试笔试成绩、医学专业知识和科学专业知识的自我评估以及学生满意度。通过多元回归分析,计算了所选变量对不同学习成功指标的预测能力,这些变量也通过毕业生调查进行测量:结果:可以确定对预测学习成功有轻微或适度帮助的模型。大学入学资格考试的分数是预测 M2 笔试的最强预测因子:三项调查的 R(2) 在 0.08 和 0.22 之间。学位课程结构和教学的不同变量有助于预测医学专业知识(R(2)=0.04-0.32)和学生满意度(R(2)=0.12-0.35)。学位课程的结构和课程顺序以及理论与实践的结合这两个变量本身是显著的、样本不变的预测因子(β-weight(Structure)=0.21-0.58, β-weight(Combination)=0.27-0.56)。结论:描述教学的因素很难对学生的学习产生影响:结论:在预测 M2 笔试分数时,描述教学的因素几乎没有任何帮助。科学专业知识缺乏可预测性的原因很可能是,这些知识很少被纳入课程,而且往往不明确。理论与实践的可变结合似乎对传授医学专业知识和培养学生的满意度具有重要意义。这些关系在多大程度上具有实际意义,还需要进一步研究探讨。一个具体的局限是,对专业知识和技能的衡量仅以自我评估为基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Impact of the Medical Faculty on Study Success in Freiburg: Results from Graduate Surveys.

Aim: Using the data from graduate surveys, this study aims to analyze which factors related to teaching and learning at the Freiburg Faculty of Medicine can influence study success.

Background: Study success and the factors influencing it have long been the subject of investigation, with study success being measured in terms of easily quantifiable indicators (final grades, student satisfaction, etc.). In recent years, it has also frequently been assessed in terms of graduate competency levels. Graduate surveys are considered suitable instruments for measuring these dimensions of study success.

Method: Data from three Freiburg graduate surveys conducted one and a half years after graduation were drawn upon for the analysis. Study success was operationalized using four indicators: results on the written section of the M2 exam, self-assessment of medical expertise and scientific expertise, and student satisfaction. Using multiple regression analyses, the predictive power was calculated for selected variables, also measured by the graduate surveys, for the different study success indicators.

Results: It was possible to identify models that contribute slightly or moderately to the prediction of study success. The score earned on the university entrance qualification demonstrated itself to be the strongest predictor for forecasting the M2 written exam: R(2) is between 0.08 and 0.22 for the three surveys. Different variables specific to degree program structure and teaching are helpful for predicting medical expertise (R(2)=0.04-0.32) and student satisfaction (R(2)=0.12-0.35). The two variables, structure and curricular sequencing of the degree program and combination of theory and practice, show themselves to be significant, sample-invariant predictors (β-weight(Structure)=0.21-0.58, β-weight(Combination)=0.27-0.56). For scientific expertise, no sample-independent predictors could be determined.

Conclusion: Factors describing teaching hardly provide any assistance when predicting the written M2 exam score, which makes sense to the extent that teaching goes far beyond the heavily knowledge-based content of the written M2 exam. The lack of predictability for scientific expertise is most likely explained in that these have been only rarely included in the curriculum and often inexplicitly so. The variable combination of theory and practice appears to be significant for imparting medical expertise and the development of student satisfaction. The extent to which these relationships are practically relevant needs to be explored in further studies. A specific limitation is that the measurement of expertise and skill is based solely on self-assessments.

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