Learning the skills required to analyse data is crucial in science. Unfortunately however, the necessary underlying maths and statistics are typically regarded as difficult and abstract by students, who as a consequence may struggle to maintain motivation and engagement. This issue is made worse by traditional teaching, where lectures on theory, in which students are mostly passive, are followed by tutorials on exercises that may not be particularly inspiring or authentic (such as typical made up textbook questions).

The OpenDataStat website promotes an alternative problem-based approach where teaching and learning are built around the use of real, current, and openly available data. The availability of real-world “open” data has increased substantially in recent times, through the proliferation of public databases as well as the global push for open access to research.  Such abundant sources of real data can be exploited in the classroom to develop more authentic and relevant teaching and learning activities.

Moreover, the large scale and variety of open data can provide students with the freedom to shape their own assessment tasks, also according to personal interest and identity. For example, students can be given the opportunity to demonstrate their learning by applying relevant statistical methods to data sets of their choice. This is expected to be engaging and motivating.

Furthermore, open data can be exploited to develop critical thinking as well as to “demystify” science. In particular, activities can be conducted to revisit published findings using new data; this builds students’ confidence as they work directly through the process of recreating published research. Importantly, previous findings are sometimes not reproduced with new data, thus providing learners with first-hand experience of the provisional nature of science.

A key advantage of open data is that they are quick and free to access, so their use has the potential to drastically reduce the time and resources needed to conduct science projects. As a practical consequence, it becomes possible to offer additional opportunities to students that may otherwise be restricted to literature review projects.

The OpenDataStat project is led by Dr Mario Orsi with support from the Faculty of Health and Applied Sciences at the University of the West of England (UWE), Bristol, UK.