MECO6902: Semester 2, 2025

Units MECO6902 Semester 2 2025 [Normal day]

Unit outline_

MECO6902: Legal and Ethical Issues in Media Practice

Semester 2, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

MECO6902 will introduce students to key legal and ethical issues relevant to journalism and the professional fields of public communication. Students will be given an introductory survey of the main ethical theories in Western thought to establish a framework within which to examine specific ethical issues that relate to media systems. They will also be introduced to the structure of Australia's legal system in comparison with other legal systems, and explore selected law, regulation and policy issues.

Unit details and rules

Academic unit	Media and Communications
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Tiania Stevens, tiania.stevens@sydney.edu.au
Lecturer(s)	Holly Raiche, holly.raiche@sydney.edu.au
	Manan Luthra, manan.luthra@sydney.edu.au
	Uzma Aleem, uzma.aleem@sydney.edu.au
	Ruby Hamad, ruby.hamad@sydney.edu.au
	Mark Mulligan, mark.mulligan@sydney.edu.au

Assessment

The census date for this unit availability is 1 September 2025

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Portfolio or journal	Online comment piece n/a	30%	Multiple weeks	1500 words	AI allowed
Outcomes assessed:
Presentation	Presentation n/a	20%	Multiple weeks	1500 words	AI allowed
Outcomes assessed:
Contribution	Participation n/a	10%	Multiple weeks	n/a	AI allowed
Outcomes assessed:
Written work	Essay n/a	40%	Week 12 Due date: 31 Oct 2025 at 23:59	3000 words	AI allowed
Outcomes assessed:

Assessment summary

Detailed information for each assessment can be found on Canvas.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a High distinction indicates work of an exceptional standard, a Distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name	Mark range	Description
High distinction	85 - 100
Distinction	75 - 84
Credit	65 - 74
Pass	50 - 64
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see sydney.edu.au/students/guide-to-grades.

For more information see guide to grades.

Use of generative artificial intelligence (AI)

You can use generative AI tools for open assessments. Restrictions on AI use apply to secure, supervised assessments used to confirm if students have met specific learning outcomes.

Refer to the assessment table above to see if AI is allowed, for assessments in this unit and check Canvas for full instructions on assessment tasks and AI use.

If you use AI, you must always acknowledge it. Misusing AI may lead to a breach of the Academic Integrity Policy.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

Academic integrity

The University expects students to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

Our website provides information on academic integrity and the resources available to all students. This includes advice on how to avoid common breaches of academic integrity. Ensure that you have completed the Academic Honesty Education Module (AHEM) which is mandatory for all commencing coursework students

Penalties for serious breaches can significantly impact your studies and your career after graduation. It is important that you speak with your unit coordinator if you need help with completing assessments.

Visit the Current Students website for more information on AI in assessments, including details on how to acknowledge its use.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Support for students

The Support for Students Policy reflects the University’s commitment to supporting students in their academic journey and making the University safe for students. It is important that you read and understand this policy so that you are familiar with the range of support services available to you and understand how to engage with them.

The University uses email as its primary source of communication with students who need support under the Support for Students Policy. Make sure you check your University email regularly and respond to any communications received from the University.

Learning resources and detailed information about weekly assessment and learning activities can be accessed via Canvas. It is essential that you visit your unit of study Canvas site to ensure you are up to date with all of your tasks.

If you are having difficulties completing your studies, or are feeling unsure about your progress, we are here to help. You can access the support services offered by the University at any time:

Support and Services (including health and wellbeing services, financial support and learning support)
Course planning and administration
Meet with an Academic Adviser

Weekly schedule

WK	Topic	Learning activity
Week 01	Introduction and overview	Lecture and tutorial (2 hr)
Week 02	Survey of ethical approaches 1: Aristotle and virtue ethics; Kant and deontological ethics	Lecture and tutorial (2 hr)
Week 03	Survey of ethical approaches 2: Mills and Utilitarianism; public journalism; Michel Foucault	Lecture and tutorial (2 hr)
Week 04	Media law, policy, the public interest and ethical conduct	Lecture and tutorial (2 hr)
Week 05	Media law, ethics and media systems and media regulation	Lecture and tutorial (2 hr)
Week 06	Codes of ethics and practice in media regulation	Lecture and tutorial (2 hr)
Week 07	Guest lecture	Online class (2 hr)
Week 08	Confidential information, privacy and surveillance	Lecture and tutorial (2 hr)
Week 09	Defamation and the protection of reputations	Lecture and tutorial (2 hr)
Week 10	Ethics, community, representation and vilification laws	Lecture and tutorial (2 hr)
Week 11	Copyright, creative rights, satire and parody	Lecture and tutorial (2 hr)
Week 12	Legal and ethical issues in commercial media cultures	Lecture and tutorial (2 hr)
Week 13	Media law and regulation (the future of media law and ethics: diversity, convergent)	Lecture and tutorial (2 hr)

Attendance and class requirements

Attendance: According to Faculty Board Resolutions, students in the Faculty of Arts and Social Sciences are expected to attend 90% of their classes. If you attend less than 50% of classes, regardless of the reasons, you may be referred to the Examiner’s Board. The Examiner’s Board will decide whether you should pass or fail the unit of study if your attendance falls below this threshold.
Lecture recording: Most lectures (in recording-equipped venues) will be recorded and may be made available to students on the LMS. However, you should not rely on lecture recording to substitute your classroom learning experience.
Preparation: Students should commit to spend approximately three hours’ preparation time (reading, studying, homework, essays, etc.) for every hour of scheduled instruction.
Restricted AI use is allowed for all assessments. AI can only be used for editing work already written in full by students. AI is not to be used to write assessments.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

Dwyer, T. (2012) Legal and Ethical Issues in the Media. Basingstoke, Hampshire, Palgrave Macmillan.

Further up to date readings and research material will be provided online in each week's module (see Canvas).

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. recognise and identify situations in media practice in which ethics might be a specific issue
LO2. possess relevant legal literacy, sufficiently to know when to identify risks and seek further advice
LO3. draw on ethical theories to think through ethical dilemmas and issues
LO4. understand legal and ethical issues facing reflective, responsible and professional public communicators
LO5. develop skills to continue own learning in this discipline and assist the learning of the group.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Additional information

Limited Use of AI tools_Academic Integrity

In the written assessments for this unit, you are allowed to use automated writing tools and artificial intelligence (AI) for the following purposes:

Editing assistance

You may use automated writing or AI tools such as Grammarly, Notion AI, ChatGPT, etc to provide feedback on your work and suggest readability improvements to your text in terms of grammar and expression. You cannot use generative AI tools to generate content.

Generating ideas for assessment

You may use AI tools such as ChatGPT, MS Co-Pilot, Ernie Bot and other generative AI to brainstorm initial ideas and approaches for completing your assignment.

However, you must develop or edit those ideas to a substantial degree to ensure your submission is your own, original work.

Suggesting a structure or outline

You may use AI tools such as ChatGPT, MS Co-Pilot, Ernie Bot and other generative AI to help you draft an outline for your work. But be very careful not to use AI tools to generate actual assignment content.

Writing a draft for later improvement

You may use AI tools such as ChatGPT, MS Co-Pilot, Ernie Bot and other generative AI to generate a draft artefact. You then need to take steps and save any documentation required in order to demonstrate that you were aware of the unit’s learning outcomes.

Your final submitted work must be your own, original work. You must acknowledge any use of AI tools that have been used in the assessment, and any material that forms part of your submission, must be appropriately referenced.

Be aware that generative AI tools often produce incorrect information.

You remain responsible for your work. This means you must independently verify and edit AI-generated content to ensure the integrity, accuracy, and suitability of the output.

Generative AI tools use probabilistic models that are trained on enormous datasets to generate plausible new content; they use existing, uncorroborated content from many sources and can produce inaccurate, biased or creatively fictitious content. Repeated use of a generative AI tool can create different content each time it is run.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI)

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Attendance and class requirements

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Additional information

Additional information

Disclaimer

On this page

Useful links