Students

MMCC8026 – Data Journalism

2025 – Session 1, In person-scheduled-weekday, North Ryde

General Information

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Unit convenor and teaching staff Unit convenor and teaching staff
Mathias Felipe de Lima Santos
mathias.felipe@mq.edu.au
Credit points Credit points
10
Prerequisites Prerequisites
Admission to MMediaComm or MCrInd
Corequisites Corequisites
Co-badged status Co-badged status
Unit description Unit description

This unit focuses on innovative approaches to finding, reporting, producing and interacting with media stories through basic data analysis and data visualization. Students will critically analyse and gain practical experience in finding data-sets, using data-driven reporting techniques and producing effective and informative visualisations. The unit also covers user experience, interactivity and the rhetorical use of big and small data in media practice.

Important Academic Dates

Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates

Learning Outcomes

On successful completion of this unit, you will be able to:

  • ULO1: analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
  • ULO2: demonstrate an advanced knowledge of how to gather, analyse and interpret data as a journalist and within collaborative contexts
  • ULO3: apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
  • ULO4: evaluate and analyse new literacies in journalism.
  • ULO5: situate the focus on data and visualization within debates about journalism and its social function.

General Assessment Information

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day an assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a mark of‚ 0 (zero) will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11.55pm. A 1-hour grace period is provided to students who experience a technical issue.    

This late penalty will apply to all assessments (e.g., essays, reports, posters, portfolios, journals, recordings etc). Late submission of time sensitive tasks (such as tests/exams, quizzes, performance assessments/presentations, scheduled practical assessments/labs etc) will only be addressed by the unit convenor in a Special consideration application. Special Consideration outcome may result in a new task. These are serious penalties that will substantially alter your final grade and even determine whether you pass or fail this unit. Please make every effort to submit your assignment by the due date.

If you find you cannot submit your assignment on time, please apply for Special Consideration through AskMQ. Make sure you read Macquarie University's policy regarding Special Consideration requests before you apply: https://students.mq.edu.au/study/assessment-exams/special-consideration

Assessment Tasks

Name Weighting Hurdle Due
Writing Analysis 40% No 11/April/25, 11:55 PM
Quiz 30% No 1/May/25, 11:55 PM
Data Story 30% No 27/May/24, 11:55 PM

Writing Analysis

Assessment Type 1: Essay
Indicative Time on Task 2: 25 hours
Due: 11/April/25, 11:55 PM
Weighting: 40%

 

The essay identifies and critically analyses a recent example of data journalism in the context of key discussions and debates on how it can produce stories that inform, educate and entertain from a human perspective. Refer to iLearn for further information.

 
On successful completion you will be able to:
  • analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
  • evaluate and analyse new literacies in journalism.
  • situate the focus on data and visualization within debates about journalism and its social function.

Quiz

Assessment Type 1: Problem set
Indicative Time on Task 2: 25 hours
Due: 1/May/25, 11:55 PM
Weighting: 30%

 

This task involves the compilation and submission of skills demonstrated through quizzes and coding tasks. This task encompasses knowledge on data cleaning, visualization, and basic statistical calculations relevant to data journalism. Refer to iLearn for further information.

 
On successful completion you will be able to:
  • analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
  • demonstrate an advanced knowledge of how to gather, analyse and interpret data as a journalist and within collaborative contexts
  • apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
  • evaluate and analyse new literacies in journalism.
  • situate the focus on data and visualization within debates about journalism and its social function.

Data Story

Assessment Type 1: Project
Indicative Time on Task 2: 30 hours
Due: 27/May/24, 11:55 PM
Weighting: 30%

 

This project contains original data story and its input material. Grades are weighted by team evaluation. Refer to iLearn for further information.

 
On successful completion you will be able to:
  • demonstrate an advanced knowledge of how to gather, analyse and interpret data as a journalist and within collaborative contexts
  • apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.

1 If you need help with your assignment, please contact:

  • the academic teaching staff in your unit for guidance in understanding or completing this type of assessment
  • the Writing Centre for academic skills support.

2 Indicative time-on-task is an estimate of the time required for completion of the assessment task and is subject to individual variation

Delivery and Resources

The Data Journalism unit (MMCC8026) begins in Week 2. The course will be delivered through weekly two-hour seminars, combining lecture-style content with hands-on practical exercises. This unit requires the use of computer resources and online tools like GitHub and Google Colab.

Students will also have access to online resources via iLearn, including lecture slides, supplementary readings, seminar recordings, and links to relevant datasets. An iLearn discussion forum will facilitate Q&A and peer-to-peer learning outside of seminar time.

Policies and Procedures

Macquarie University policies and procedures are accessible from Policy Central (https://policies.mq.edu.au). Students should be aware of the following policies in particular with regard to Learning and Teaching:

Students seeking more policy resources can visit Student Policies (https://students.mq.edu.au/support/study/policies). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.

To find other policies relating to Teaching and Learning, visit Policy Central (https://policies.mq.edu.au) and use the search tool.

Student Code of Conduct

Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/admin/other-resources/student-conduct

Results

Results published on platform other than eStudent, (eg. iLearn, Coursera etc.) or released directly by your Unit Convenor, are not confirmed as they are subject to final approval by the University. Once approved, final results will be sent to your student email address and will be made available in eStudent. For more information visit connect.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au

Academic Integrity

At Macquarie, we believe academic integrity – honesty, respect, trust, responsibility, fairness and courage – is at the core of learning, teaching and research. We recognise that meeting the expectations required to complete your assessments can be challenging. So, we offer you a range of resources and services to help you reach your potential, including free online writing and maths support, academic skills development and wellbeing consultations.

Student Support

Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/

Academic Success

Academic Success provides resources to develop your English language proficiency, academic writing, and communication skills.

The Library provides online and face to face support to help you find and use relevant information resources. 

Student Services and Support

Macquarie University offers a range of Student Support Services including:

Student Enquiries

Got a question? Ask us via the Service Connect Portal, or contact Service Connect.

IT Help

For help with University computer systems and technology, visit http://www.mq.edu.au/about_us/offices_and_units/information_technology/help/. 

When using the University's IT, you must adhere to the Acceptable Use of IT Resources Policy. The policy applies to all who connect to the MQ network including students.

Unit information based on version 2025.05 of the Handbook