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Correlation of online assessment parameters with summative exam performance in undergraduate medical education of pharmacology: a prospective cohort study.


ABSTRACT: BACKGROUND: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. METHODS: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. RESULTS: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 

SUBMITTER: Kuhbeck F 

PROVIDER: S-EPMC6842254 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Correlation of online assessment parameters with summative exam performance in undergraduate medical education of pharmacology: a prospective cohort study.

Kühbeck Felizian F   Berberat Pascal O PO   Engelhardt Stefan S   Sarikas Antonio A  

BMC medical education 20191108 1


<h4>Background</h4>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.<h4>Methods</h4>A prospective study was conducted with a coho  ...[more]

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