Students
MECO826 – Data Journalism
2019 – S2 Day
General Information
Download as PDF
| Unit convenor and teaching staff |
Unit convenor and teaching staff
Margie Borschke
10HA 254, 10 Hadenfeld Dr (formerly Y3A 254)
after class
|
|---|---|
| Credit points |
Credit points
4
|
| Prerequisites |
Prerequisites
Admission to MFJ or MCreIndMFJ or MMedia or MCreIndMMedia
|
| 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 the use of digital technologies and data structures. Students will critically analyse and gain practical experience in data-driven reporting techniques, the principles of information design and the production of data visualisations. The unit also covers user experience, gamification, collaboration and the potential uses and limitations of 'big' data for journalistic 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:
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
General Assessment Information
- All assessments must be submitted online via the appropriate ilearn Turnitin submission box
- Students will have access to the standards expected and examples of relevant and related assessment tasks. (The assessment criteria are stated in this unit guide. The standards expected are detailed in the rubric available on ilearn in the relevant Assessment section--there will also be many opportunities to discuss these standards and examples of relevant and related assessment tasks in class time.)
- SPECIAL CONSIDERATION Unless a Special Consideration request has been submitted and approved, (a) a penalty for lateness will apply – two (2) marks out of 100 will be deducted per day for assignments submitted after the due date – and (b) no assignment will be accepted more than seven (7) days (incl. weekends) after the original submission deadline. No late submissions will be accepted for timed assessments – e.g. quizzes, online tests.”
- This penalty does not apply for cases in which an application for Special Consideration was made and approved.
Assessment Tasks
| Name | Weighting | Hurdle | Due |
|---|---|---|---|
| Portfolio: Deconstructed Data | 40% | No | Thursday September 5, 2019 23:59 |
| Data Visualisation in context | 60% | No | November 4, 2019 9:00am |
Portfolio: Deconstructed Data
Due: Thursday September 5, 2019 23:59
Weighting: 40%
You will submit a Portfolio containing:
- Two blog posts (apx 500 words each + links and images), chosen from the weekly set exercises in weeks 1-5.
- A 500 word overview/introduction that summarises and reflects on the work completed and contextualises the work within key debates and discussions
Format: Submit your portfolio as a word doc or pdf via Turnitin box on iLearn.
Detailed instructions will be issued each week to guide your posts.
- Analysis: Demonstrate that you can identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history
- Case Studies: Your ability to choose appropriate examples to analyse and evaluate concepts and approaches to news gathering and storytelling
- Context: Your post will demonstrate that you can situate literacies in journalism within debates about journalism and its social function.
- Presentation: Clarity of expression and appropriate use of images, links and other media.
Assessment Style & Feedback:
This is a formative assessment. Your formal feedback will include a grade out of 100 and a qualitative rubric
On successful completion you will be able to:
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Data Visualisation in context
Due: November 4, 2019 9:00am
Weighting: 60%
Your data visualisation in context portfolio will include:
- Three original visualizations (see iLearn for more detail; learning activities in class will scaffold the production of these visualisations).
- Each visualisation should be accompanied by a caption that includes information on sources and tools used.
- A 1000 word essay that a) explains your process and decisions and b) critically assesses the benefits, challenges and limits of data driven storytelling and journalism.
More Detailed instructions will be given on iLearn.
Assessment Criteria:
- Visualizations: The success of your visualizations as a form of effective non-fiction storytelling
- Research: The quality of the research and/or reporting you conducted to develop your visualizations; your ability to identify suitable datasets or gather suitable data
- Practice: Show that you are able to identify and reflect upon good practice in the field and contextualise your work
- Context: Demonstrate understanding of key debates in the field of data journalism
This is a summative assessment: Feedback will include a grade out of 100 and a qualitative rubric
On successful completion you will be able to:
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Delivery and Resources
Seminars begin in week 1 as stated in timetables. Attendance at all seminars is expected.
Information about weekly readings and learning activities will be available via iLearn.
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central). Students should be aware of the following policies in particular with regard to Learning and Teaching:
- Academic Appeals Policy
- Academic Integrity Policy
- Academic Progression Policy
- Assessment Policy
- Fitness to Practice Procedure
- Grade Appeal Policy
- Complaint Management Procedure for Students and Members of the Public
- Special Consideration Policy (Note: The Special Consideration Policy is effective from 4 December 2017 and replaces the Disruption to Studies Policy.)
Undergraduate students seeking more policy resources can visit the Student Policy Gateway (https://students.mq.edu.au/support/study/student-policy-gateway). It is your one-stop-shop for the key policies you need to know about throughout your undergraduate student journey.
If you would like to see all the policies relevant to Learning and Teaching visit Policy Central (https://staff.mq.edu.au/work/strategy-planning-and-governance/university-policies-and-procedures/policy-central).
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/study/getting-started/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 ask.mq.edu.au or if you are a Global MBA student contact globalmba.support@mq.edu.au
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
If you are a Global MBA student contact globalmba.support@mq.edu.au
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.
MMCCS Session Re-mark Application http://www.mq.edu.au/pubstatic/public/download/?id=167914
Information is correct at the time of publication
Graduate Capabilities
PG - Capable of Professional and Personal Judgment and Initiative
Our postgraduates will demonstrate a high standard of discernment and common sense in their professional and personal judgment. They will have the ability to make informed choices and decisions that reflect both the nature of their professional work and their personal perspectives.
This graduate capability is supported by:
Learning outcomes
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Assessment tasks
- Portfolio: Deconstructed Data
- Data Visualisation in context
PG - Discipline Knowledge and Skills
Our postgraduates will be able to demonstrate a significantly enhanced depth and breadth of knowledge, scholarly understanding, and specific subject content knowledge in their chosen fields.
This graduate capability is supported by:
Learning outcomes
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Assessment tasks
- Portfolio: Deconstructed Data
- Data Visualisation in context
PG - Critical, Analytical and Integrative Thinking
Our postgraduates will be capable of utilising and reflecting on prior knowledge and experience, of applying higher level critical thinking skills, and of integrating and synthesising learning and knowledge from a range of sources and environments. A characteristic of this form of thinking is the generation of new, professionally oriented knowledge through personal or group-based critique of practice and theory.
This graduate capability is supported by:
Learning outcomes
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Assessment tasks
- Portfolio: Deconstructed Data
- Data Visualisation in context
PG - Research and Problem Solving Capability
Our postgraduates will be capable of systematic enquiry; able to use research skills to create new knowledge that can be applied to real world issues, or contribute to a field of study or practice to enhance society. They will be capable of creative questioning, problem finding and problem solving.
This graduate capability is supported by:
Learning outcomes
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Assessment tasks
- Portfolio: Deconstructed Data
- Data Visualisation in context
PG - Effective Communication
Our postgraduates will be able to communicate effectively and convey their views to different social, cultural, and professional audiences. They will be able to use a variety of technologically supported media to communicate with empathy using a range of written, spoken or visual formats.
This graduate capability is supported by:
Learning outcomes
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Assessment tasks
- Portfolio: Deconstructed Data
- Data Visualisation in context
PG - Engaged and Responsible, Active and Ethical Citizens
Our postgraduates will be ethically aware and capable of confident transformative action in relation to their professional responsibilities and the wider community. They will have a sense of connectedness with others and country and have a sense of mutual obligation. They will be able to appreciate the impact of their professional roles for social justice and inclusion related to national and global issues
This graduate capability is supported by:
Learning outcomes
- Identify and critically analyse the practice of data journalism, its products (including visualizations and interactive reporting) and its history.
- Demonstrate an understanding of how to gather, analyse and interpret data as a journalist.
- Apply advanced reporting and storytelling techniques to find and produce stories that inform, educate and entertain.
- Identify and analyse new literacies in journalism.
- Situate the focus on data and visualization within debates about journalism and its social function.
Assessment tasks
- Portfolio: Deconstructed Data
- Data Visualisation in context