How to build data literacy on campus

The data age is here, but is higher education prepared? With AI, algorithms and analytics now part of daily life, universities need to make sure their students are prepared for the future workplace, that researchers remain at the cutting edge of data strategy and that institutional leaders can make data-informed decisions. This collection of resources offers advice on integrating data literacy into the curriculum, how researchers can manage and present their data and how to get started with data visualisation.

The ability to interpret and analyse data is becoming an imperative for many employers. So, universities have a responsibility to equip students with foundational data literacy skills that will enable them to flourish in a wide array of careers. But how can data literacy be added or integrated into existing university curricula effectively? What does teaching data literacy entail in terms of technical know-how, data visualisation and critical thinking skills? And should this now be taught in tandem with AI literacy? These resources seek to answer some of these questions with useful advice. 

Researchers not only need the ability to manage and interpret data, they must also learn to present and explain it in clear and simple terms for different audiences. And as available datasets get larger, the challenge of identifying patterns and drawing conclusions also grows. Find advice on the data skills early career researchers need to succeed in academia, on open access data, evidence synthesis and understanding your own research metrics.

For data-informed decisions and institutional strategy, university leaders need to ensure effective data governance, storage and analysis. They need to champion for data literacy across their institutions to ensure students and staff can develop the skills they need. These resources look at how driving a better understanding of data benefits everyone on campus.