Latest Module Specifications
Current Academic Year 2025 - 2026
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Description This module focuses on how data and IT tools can assist and support journalists in digital storytelling. The module aims to give students a solid basic understanding of the tools available and possibilities of data journalism. Besides learning about the basics of this increasingly vital discipline, students will learn how data is used in the media industry today, where to locate data, how to analyse it, and how to optimise the presentation of information for maximum readability and interactivity. The module also gives students a thorough grounding in the use of common tools including spreadsheets and presentation. The module focuses particularly on using visualisation to effectively communicate data. Students will apply these principles and tools in telling journalistic stories and the importance of a narrative remains crucial throughout. The module will be delivered as a series of lectures and workshops which will cover spreadsheets, document and presentation preparation and visualisation tools. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Learning Outcomes 1. Explain how data is used in journalism (Describe the fundamental concepts of Data Literacy and Analytics, the key steps in the analytics process, and the applications and implications of data analytics in one’s specialism.) 2. Understand where to source data for journalistic stories 3. Learn how to clean and utilise appropriate data, including FoI, open government and public datasets (Demonstrate the ability to source and import data and apply basic functions for cleaning and processing of this data in preparation for data analysis.) 4. Report and write complex, multi-source data driven journalism (Identify the relevant insights extracted from a dataset and effectively and appropriately communicate them.) 5. Solve analytical problem and learn how to view data critically (incl. spreadsheets). (Differentiate between the different data types in analytics and have the ability to explain basic database design concepts.) 6. Apply the basic principles in effectively communicating data visually. (Identify and use basic data analysis and visualisation tools to describe and interpret data.) 7. Utilize online tools to both collect and visualize data sets. (Demonstrate knowledge of the key statistical concepts underlying data analytics, including descriptive statistics and principles of effective visualisations.) | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
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Indicative Content and Learning Activities
Introduction and Context Ubiquity of computers, information and systems Data vs Information Where to Find Data and the Stories Open data FoI Publically funded datasets Social networks Data Sorting, Cleaning, Analytics, Pivot Tables, Basic Statistics How to Bring the Data to Life Principles Design, Animation, Interaction | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Indicative Reading List Books:
Articles: None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Other Resources None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||