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Module Code - Title:

JM4062 - DATA JOURNALISM

Year Last Offered:

2025/6

Hours Per Week:

Lecture

0

Lab

3

Tutorial

0

Other

0

Private

7

Credits

6

Grading Type:

N

Prerequisite Modules:

Rationale and Purpose of the Module:

The Data Journalism module will teach students to understand the landscape of the use of data in news media and the degree of knowledge and skills required for various 'beats'. It will enable students to engage with statistics and scientific research confidently in their journalism, from reporting on it to producing data driven reports. The module will provide students with the basic conceptual tools to assess and develop suitable research design and methodologies for data driven journalism projects. The module will introduce students to the range of data available, how it can be used Introduce basic tools used in data analysis and produce basic charts.

Syllabus:

The Data Journalism module will teach students key theory and practice in data journalism. The module will teach students mathematical tools for journalists alongside basic statistics. The module will teach students where to find data including public access, FOI, CSO, and International resources. The module will include data analysis and advanced data visualisations and the principles of data visualisation and communicating data to the public. The module will include mapping regional or geographic data. Overall, the module will teach students how to develop data into coherent news stories.

Learning Outcomes:

Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)

On successful completion of this module, students will be able to demonstrate an ability to communicate basic mathematics and statistics to general audiences. Students will be able to demonstrate an ability to find and generate data for news stories and suitably process and analyse data to inform stories. Students will demonstrate an understanding of an introductory knowledge of tools used for data gathering, analysis and visualisation. Students will be able to demonstrate an ability to evaluate and apply principles of data visualisation. Students will be able to demonstrate an ability to design and conduct a small-scale data driven investigation.

Affective (Attitudes and Values)

On successful completion of this module, students will be able to: Demonstrate an understanding of and ability of values, motivations, and attitudes around the application of data in journalism, for example how data may be used to attempt to manipulate an audience.

Psychomotor (Physical Skills)

On successful completion of this module, students will be able to: NA

How the Module will be Taught and what will be the Learning Experiences of the Students:

This module will be taught via labs over a twelve week period. The module is based on recent innovations in journalism practice which has seen data being used to develop and complement stories. For example in fact checking practices via geolocation technologies. The methods taught here has also been used in conflict situations such as Syria and Ukraine to provide evidence for war crimes.

Research Findings Incorporated in to the Syllabus (If Relevant):

Prime Texts:

Britten, Bob. (2014) "Data-driven Journalism." In Convergent Journalism: An Introduction, pp. 157-180. , Routledge
Hermida, Alfred, and Mary Lynn Young (2019) Data journalism and the regeneration of news. , Routledge
Gray, Jonathan, Lucy Chambers, and Liliana Bounegru. (2014) The data journalism handbook: How journalists can use data to improve the news. , O'Reilly Media

Other Relevant Texts:

Programme(s) in which this Module is Offered:

BAJDCOUFA - JOURNALISM AND DIGITAL COMMUNICATION

Semester(s) Module is Offered:

Spring

Module Leader:

niamh.kirk@ul.ie