Table 3 Competencies and learning objectives, datathon phase.
From: Advancing data science research education in Africa through datathon-driven innovations
Competency | Bloom’s taxonomy level | Learning objectives | Signature assessment |
|---|---|---|---|
Develop research topics and hypotheses within multidisciplinary teams | Create | Perform collaborative hypothesis generation using large, multimodal health data sources | First project presentation on day 1 |
Choose appropriate comparison groups and methodological approaches for hypothesis testing | Evaluate | Define primary and secondary outcomes and design testable hypotheses | Second project presentation on day 2 |
Perform univariate, bivariate, and multivariable analyses for hypothesis testing | |||
Organize large, multimodal health data sources | Apply | Apply computer algorithms to curate, query, and organize operational data sets | Final computer algorithm files |
Prepare master data sets | Final master data sets | ||
Analyze large, multimodal health data sources | Analyze | Prepare descriptive statistics and apply statistical methods and modeling | Group project report |
Present scientific results in oral and written discourses | Understand | Develop and deliver a team project presentation | Final project presentation on day 5 |
Prepare a research study progress report | Final study report | ||
Disseminate findings with the broader scientific community | Remember | Prepare a research manuscript synthesizing the training activities | Research manuscript |
