Data Journalism and Digital Investigations
module description
From the module description (2026–2027):
What is data journalism? What are digital investigations? What kinds of techniques and approaches are journalists using to create, use and tell stories with data? What kinds of data sources and methods do investigators, artists and activists use to produce facts based on information in the public domain?
In the last few years, journalists, investigators, artists and activist groups have been experimenting with different techniques for investigation, analysis, storytelling and interactivity with public data. These developments have been referred to as data journalism and digital investigations. This module will explore these dynamic fields, including how digital data is being put to work to enable different forms of making sense, telling stories and involving publics.
Students will learn how to develop a “critical data practice” for understanding and working with data and digital methods. This will include critically reflecting on the data sources, tools, techniques and methods of data journalism and digital investigations through a series of readings, as well as learning how to assemble, clean, analyse, visualise data and develop stories and investigations through their own projects.
Building on tools and pedagogical innovations from leading centres for data journalism and digital investigations education, the module will adopt a ‘flipped classroom’ approach supporting collaborative student projects through engaging digital resources and workshops.
This module uses a flipped classroom model. This model enables active student learning by working on projects with instructor support and a carefully designed package of materials. This package includes bespoke worksheets, video tutorials, “how-to” articles, datasets, tools, shared working spaces and forums for learning outside the classroom. The lion’s share of classroom time is for deep, collaborative work on project development with instructor support in a workshop format. Prior to class students are expected to watch video lectures, do readings, learn how to use software tools and implement research protocols with the help of software tool tutorials and worksheets, as well as to progress with their research projects. Time in class is dedicated to hands-on work on group projects with support from module convenors and other guest experts. The individual learning activities prior to each class are essential for students to be able to make progress on their projects during class and for student success on this module. In the final seminars students present the preliminary outcomes of their projects. These presentations offer an opportunity for formative feedback from module convenors and other experts ahead of finalising and submitting the projects for summative assessment at the end of the module.