Developing new online resources on statistics and data handling for medical science students

Statistics and data handling are essential skills in medical sciences which students often find challenging. Similarly, there is a growing need for coding skills as we move more towards “big data”. Employers are increasingly seeking experience of open access programming languages including R and Python over proprietary data analysis software such as SPSS. However, our recent Internal Teaching Review highlighted that our undergraduates wanted more teaching on statistics and data analysis. Here we share our experiences of developing new optional online resources.

We developed two resources called “A Practical Guide to Data Analysis” and “Introduction to R”. The format was short lecture recordings including demos in Excel and RStudio. A key focus of our content was to provide context to aid understanding. In particular, when discussing how to choose appropriate statistical tests and graph types we worked through multiple examples of experiments. To allow students to conduct analysis in their own time, we also included simulated datasets, cheat sheets and an R notebook containing code with the expected outputs. We targeted the resources at years 3 and 4 but all medical science undergraduates had access through a shared virtual learning environment. Additionally, we ran a live online session specifically for year 4 students completing their honours projects called “Kickstarting your data analysis and visualisation”. Students were invited to complete anonymous surveys for the resources which included both 10-point Likert scales and free text questions.

Overall, the feedback across all the resources was very positive. The median rating of “A Practical Guide to Data Analysis” was 10 (IQR: 8.5, 10). Students particularly liked the use of examples to explain complex concepts. However, we acknowledge that engagement was relatively low which could be due to lack of awareness of the resources or difficulty in finding them. One student commented that they wish they had known about the resources before finishing the analysis for their lab project. Our future work will consider how we can increase the visibility of these resources and with the easing of restrictions, we are also planning to develop some face-to-face workshops such as an R taster session.