Technical University of Munich, Institute of Pharmacology and Toxicology, Biedersteiner Str. 29, 80802, Munich, Germany.
Technical University of Munich, School of Medicine, Center of Medical Education, Ismaninger Str. 22, 81675, Munich, Germany.
BMC Med Educ. 2019 Nov 8;19(1):412. doi: 10.1186/s12909-019-1814-5.
Learning analytics aims to improve learning outcomes through the systematic measurement and analysis of learning-related data. However, which parameters have the highest predictive power for academic performance remains to be elucidated. The aim of this study was to investigate the correlation of different online assessment parameters with summative exam performance in undergraduate medical education of pharmacology.
A prospective study was conducted with a cohort of undergraduate medical students enrolled in a pharmacology course at Technical University of Munich, Germany. After a four-week teaching and learning period, students were given access to an online assessment platform consisting of 440 multiple choice (MC) questions. After 12 days, a final written summative exam was performed. Bivariate correlation and multiple regression analyses were performed for different online assessment parameters as predictors and summative exam performance as dependent variable. Self-perceived pharmacology competence was measured by questionnaires pre- and postintervention.
A total of 224 out of 393 (57%) students participated in the study and were included in the analysis. There was no significant correlation for the parameters "number of logins" (r = 0.01, p = 0.893), "number of MC-questions answered" (r = 0.02, p = 0.813) and "time spent on the assessment platform" (r = - 0.05, p = 0.459) with exam performance. The variable "time per question" was statistically significant (p = 0.006), but correlated negatively (r = - 0.18) with academic performance of study participants. Only "total score" (r = 0.71, p < 0.001) and the "score of first attempt" (r = 0.72, p < 0.001) were significantly correlated with final grades. In a multiple regression analysis, "score first attempt" accounted for 52% of the variation of "score final exam", and "time per question" and "total score" for additional 5 and 1.4%, respectively. No gender-specific differences were observed. Finally, online assessments resulted in improved self-perceived pharmacology competence of students.
In this prospective cohort study, we systematically assessed the correlation of different online assessments parameters with exam performance and their gender-neutrality. Our findings may help to improve predictive models of academic performance in undergraduate medical education of pharmacology.
学习分析旨在通过对与学习相关的数据进行系统测量和分析来提高学习成果。然而,哪些参数对学业成绩具有最高的预测能力仍有待阐明。本研究的目的是调查不同在线评估参数与德国慕尼黑工业大学药理学本科医学教育中总结性考试成绩的相关性。
对德国慕尼黑工业大学药理学课程的一组本科医学生进行前瞻性研究。经过四周的教学和学习,学生可以访问由 440 个多项选择题(MC)组成的在线评估平台。12 天后,进行了最终的书面总结性考试。对不同的在线评估参数作为预测因子和总结性考试成绩作为因变量进行了双变量相关性和多元回归分析。通过干预前后的问卷调查来测量自我感知的药理学能力。
共有 393 名学生中的 224 名(57%)参与了这项研究并被纳入分析。参数“登录次数”(r=0.01,p=0.893)、“回答的 MC 问题数”(r=0.02,p=0.813)和“在评估平台上花费的时间”(r=−0.05,p=0.459)与考试成绩之间没有显著相关性。“每个问题的时间”变量具有统计学意义(p=0.006),但与研究参与者的学业成绩呈负相关(r=−0.18)。只有“总分”(r=0.71,p<0.001)和“首次尝试的分数”(r=0.72,p<0.001)与最终成绩显著相关。在多元回归分析中,“首次尝试的分数”占“期末考试分数”变化的 52%,“每个问题的时间”和“总分”分别占另外的 5%和 1.4%。没有观察到性别特异性差异。最后,在线评估提高了学生自我感知的药理学能力。
在这项前瞻性队列研究中,我们系统地评估了不同在线评估参数与考试成绩及其性别中立性的相关性。我们的研究结果可能有助于改善药理学本科医学教育中学业成绩的预测模型。