Students
MECO826 – Data Journalism
2015 – S2 Day
General Information
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| Unit convenor and teaching staff |
Unit convenor and teaching staff
Margie Borschke
Y3A 159
by appointment
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|---|---|
| Credit points |
Credit points
4
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| Prerequisites |
Prerequisites
Admission to MFJ
|
| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| 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.
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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.
Assessment Tasks
| Name | Weighting | Due | Groupwork/Individual | Short Extension | AI Approach |
|---|---|---|---|---|---|
| Portfolio1: Deconstructed Data | 20% | August 26, 2015 | No | ||
| Portfolio 2 | 30% | October 28, 2015 | No | ||
| Data Story Pitch and Plan | 10% | Week 9 | No | ||
| Data Journalism Project | 40% | November 16, 2015 | No |
Portfolio1: Deconstructed Data
Due: August 26, 2015
Weighting: 20%
Groupwork/Individual:
Short extension 3: No
AI Approach:
Each student will submit a Portfolio that is made up of three blog posts from the Community of Inquiry Blog (apx 500 words each; weeks 1-4) and a 250 word overview/introduction that reflects on the work completed
Detailed descriptions of the research and learning activities that you will document in your blog posts will be issued in class and via email. A reference copy of instructions will be posted to iLearn.
Individual Posts are to be completed before class each week and published to Meco826.ltc.mq.edu.au.
You should follow the blog's style guide.
You will be expected to present and discuss your posts in class.
Due: Submission of selected posts via iLearn turnitin box on August 26, 2015
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.
Portfolio 2
Due: October 28, 2015
Weighting: 30%
Groupwork/Individual:
Short extension 3: No
AI Approach:
Each student will submit a Portfolio that is made up of four-five blog posts (apx 250-500 words each from weeks 5-11) and a 250 word overview/reflective introduction
Detailed descriptions of the research and learning activities that you will document in posts your will be issued in class and via email. A reference copy of instructions will be posted to iLearn.
Individual Posts are to be completed before class each week and published on Meco826.ltc.mq.edu.au
You should follow the blog's style guide.
You will be expected to present and discuss your posts in class.
Due: Submission of selected posts via iLearn turnitin box on October 28, 2015
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 Story Pitch and Plan
Due: Week 9
Weighting: 10%
Groupwork/Individual:
Short extension 3: No
AI Approach:
Each Student will pitch their data-driven story idea to the class in week 9.
Students should post all relevant materials to the group discussion area on the Blog prior to class including links to relevant data sets, tools and back up research. You will use this post to talk the class through your idea and plan.
You should also acknowledge and discuss any existing pieces of Data Journalism or Visualizations that inspired your approach.
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.
Data Journalism Project
Due: November 16, 2015
Weighting: 40%
Groupwork/Individual:
Short extension 3: No
AI Approach:
A data driven feature or series of stories that should include a headline, an introduction and three-four original visualizations* including links to all relevant data sets and sources. (*You may storyboard any ideas that you are unable to produce due to technical limitations but please discuss this approach with your lecturer ahead of time.) (apx 1500 words)
You will write a short social media strategy for promotion of your work. (apx. 500 words)
A Research report and reflection that explains your process and decisions and critically assesses the benefits, challenges and limits of data driven journalism (apx. 1000words)
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
A collaborative learning space can be found at meco826.ltc.mq.edu.au. Students will need their oneID to login. Information about weekly readings and learning activities will be available via both the collaborative learning space and iLearn.
You will also receive an email each week summarizing the activity on the site and reminding you about the week's schedule.
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of 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/support/student_conduct/
Results
Results shown in iLearn, 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.
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
IT Help
For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/.
When using the University's IT, you must adhere to the Acceptable Use 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
- 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
- Portfolio1: Deconstructed Data
- Portfolio 2
- Data Story Pitch and Plan
- Data Journalism Project
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
- 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
- Portfolio1: Deconstructed Data
- Portfolio 2
- Data Story Pitch and Plan
- Data Journalism Project
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
- 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
- Portfolio1: Deconstructed Data
- Portfolio 2
- Data Story Pitch and Plan
- Data Journalism Project
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
- 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
- Portfolio1: Deconstructed Data
- Portfolio 2
- Data Story Pitch and Plan
- Data Journalism Project
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
- 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
- Portfolio1: Deconstructed Data
- Portfolio 2
- Data Story Pitch and Plan
- Data Journalism Project
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
- 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
- Portfolio1: Deconstructed Data
- Portfolio 2
- Data Story Pitch and Plan
- Data Journalism Project