Application of epidemiological principles, analyses & interpretation of public health data are fundamental skills for public health students. Troves of health data are available in public domain for free, and open-source tools are freely available for analysis.

While training programmes in epidemiology focus on theory, statistics, & a generic introduction to the use of digital tools, they rarely cover data handling, programming, and computational aspects of public data, such as cleaning health data sets or creating visualisations using free and open-source tools such as R and Python. This creates an unmet gap in the teaching programmes between theory and hands-on applications.

Software & Data Carpentry Workshops (“Carpentry”) provide a teaching model to prepare students in becoming proficient users of digital tools of epidemiology & evidence-based health. These consist of workshops that enable attendees learn about programming, task automation, version control, & skills in using free and open-source software. Instructors work alongside the attendees using live-session coding where they execute codes on screen in real-time that the attendees replicate on their machines; they also use repeated feedbacks from the attendees during the workshop. The curricula are maintained in a public repository.

We used this model to teach web-based evidence appraisal software GRADEPro for a class on grading of evidence for undergraduate health sciences course at the School of Health Sciences in 2017. The instructor presented a problem to the class; the students and the instructor worked real-time in solving the problem using GRADEPro. The instructor live-coded with the students. Students reported that they felt more engaged in this format of the class than in lecture-based classes on similar topics; on an average, the grades for this assessment were higher than in the previous years. While the cohort of the students may be different from the previous years, these results suggest that Carpentry can be a viable model for teaching epidemiology and evidence appraisal.