Departamento de Matemáticas, Estadística e Investigación Operativa, Universidad de La Laguna, Tenerife, Spain.
Departamento de Análisis Matemático, Universidad de La Laguna, Tenerife, Spain.
FEBS Open Bio. 2019 Sep;9(9):1493-1502. doi: 10.1002/2211-5463.12707. Epub 2019 Aug 15.
Academic performance during the first year of university is correlated with future academic success, and is considered to be a determining factor in the reduction of dropouts. In the present study, we describe a new academic performance indicator for the first term of first-year science degrees students at La Laguna University in Spain. We are interested in identifying the most important previous academic factors for predicting the success of first-year students at university. Specifically, multiple linear regression models were used to identify such predictors of academic success. We report that, for all of the analyzed science degrees, the best predictor of academic success is high school grade point average. In addition, we obtained predictive models for estimating the value of the new academic performance indicator. Using these models, we can predict future academic success, which may help identify students at risk of failure at the beginning of the course. This in turn would ensure early implementation of educational interventions or strategies to increase academic achievement of such students.
大学第一年的学业成绩与未来的学业成功相关,被认为是减少辍学率的决定因素。在本研究中,我们描述了西班牙拉古纳大学第一年理科学生第一学期的一项新学业成绩指标。我们感兴趣的是确定哪些最重要的先前学业因素可以预测大学生第一年的成功。具体而言,我们使用多元线性回归模型来确定学业成功的这些预测因素。我们报告说,对于所有分析的理科专业,学业成功的最佳预测因素是高中平均绩点。此外,我们还获得了预测模型来估计新学业成绩指标的值。使用这些模型,我们可以预测未来的学业成功,这有助于识别课程开始时失败风险较高的学生。这反过来又可以确保及早实施教育干预措施或策略,以提高这些学生的学业成绩。