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MODULE DESCRIPTOR
Module Title
Data Journalism And Storytelling
Reference CB3101 Version 2
Created February 2024 SCQF Level SCQF 9
Approved January 2024 SCQF Points 15
Amended April 2024 ECTS Points 7.5

Aims of Module
The module is designed to help the student find, prepare, analyse data and communicate appropriately with those data to a broad media audience. It will cover both using data to support a story as well as finding stories within data.

Learning Outcomes for Module
On completion of this module, students are expected to be able to:
1 Evaluate data from multiple sources.
2 Analyse data for use.
3 Communicate data in the context of a journalistic story.
4 Demonstrate awareness of the dynamics, whether cultural, economic, ethical, legal, political, social or affective, which shape the interpretation of data.
5 Demonstrate practical ability to find a story within data.

Indicative Module Content
Topics covered include, but are not limited to, the followwing: Data Understanding; Identifying and Evaluating Data Sources; Data Preparation; Using Data to Support a Story; Finding Stories in Data; Data Storytelling; Basic Statistics; Data Visualisation; Data Ethics; Data Platforms for Journalism. The module engages students with UNESCO's Education for Sustainable Development Normative, Strategic, and Collaborative competencies in terms of recognising and understanding the ethics and principles that underly the use of data in journalism as well as the needs and persepective of others in developing appropriate and sustainable strategies to address the challenges for proper data journalism.

Module Delivery
The module is delivered via lectures, online exercises, workshops, industry speakers, case studies and lab tutorials.

Indicative Student Workload Full Time Part Time
Contact Hours 36 N/A
Non-Contact Hours 114 N/A
Placement/Work-Based Learning Experience [Notional] Hours N/A N/A
TOTAL 150 N/A
Actual Placement hours for professional, statutory or regulatory body    

ASSESSMENT PLAN
If a major/minor model is used and box is ticked, % weightings below are indicative only.
Component 1
Type: Coursework Weighting: 100% Outcomes Assessed: 1, 2, 3, 4, 5
Description: Individual Portfolio Assessment

MODULE PERFORMANCE DESCRIPTOR
Explanatory Text
The calculation of the overall grade for this module is based on 100% weighting of C1. An overall minimum grade D is required to pass the module.
Module Grade Minimum Requirements to achieve Module Grade:
A The student needs to achieve an A in C1.
B The student needs to achieve a B in C1.
C The student needs to achieve a C in C1.
D The student needs to achieve a D in C1.
E The student needs to achieve an E in C1.
F The student needs to achieve an F in C1.
NS Non-submission of work by published deadline or non-attendance for examination

Module Requirements
Prerequisites for Module None.
Corequisites for module None.
Precluded Modules None.

INDICATIVE BIBLIOGRAPHY
1 BOUNEGRU, L. and GRAY, J., 2021. The Data Journalism Handbook: Towards a Critical Data Practice. Amsterdam University Press
2 CAIRO, A., 2019. How charts lie: Getting smarter about visual information. WW Norton & Company.
3 DYKES, B., 2019. Effective data storytelling: how to drive change with data, narrative and visuals. John Wiley & Sons.
4 RICHE, N.H., HURTER, C., DIAKOPOULOS, N. and CARPENDALE, S. eds., 2018. Data-driven storytelling. CRC Press.
5 ROGERS, S., 2013. Facts are Sacred: Text only ebook. Faber & Faber.
6 WONG, D.M., 2013. The Wall Street Journal guide to information graphics: The dos and don'ts of presenting data, facts, and figures. WW Norton & Company.

Robert Gordon University, Garthdee House, Aberdeen, AB10 7QB, Scotland, UK: a Scottish charity, registration No. SC013781