Outline

Overview

Discourse analysis is concerned with analysing how people create meaning(s) in a given social context. In this unit students will learn to apply linguistic methods to the analysis of discourse. Discourse includes both spoken and written language as well as images. Students will learn to apply a range of advanced linguistic methods to explore different discourse varieties and to study their organisation above the sentence level. A particular focus will be on the kinds of insights provided by different analytical techniques.

Unit details and rules

Academic unit	Linguistics
Credit points	6
Prerequisites ?	(LNGS2601 and LNGS2624) or 12 credit points at 2000 level in Linguistics
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	No

Teaching staff

Coordinator	James Martin, james.martin@sydney.edu.au
Lecturer(s)	James Martin, james.martin@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2025

Details
Criteria

Type	Description	Weight	Due	Length
Assignment	Assingment 2 Text analysis and interpretation	65%	Formal exam period Due date: 10 Jun 2025 at 23:59 Closing date: 16 Jun 2025	3000 words
Outcomes assessed:
Assignment	Assignment 1 text analysis and interpretation	35%	Week 09 Due date: 28 Apr 2025 at 23:59 Closing date: 05 May 2025	1500 words
Outcomes assessed:
= hurdle task ? = AI allowed ?

Assessment summary

This assignment will require you to integrate information from lectures and practicals to create a concise written argument.

Assessment criteria

Result code	Result name	Mark range	Description
HD	High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
DI	Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
CR	Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
PS	Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
FA	Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.
AF	Absent fail	0 - 49	When you haven’t completed all assessment tasks or met the attendance requirements.

For more information see guide to grades.

Use of generative artificial intelligence (AI) and automated writing tools

Except for supervised exams or in-semester tests, you may use generative AI and automated writing tools in assessments unless expressly prohibited by your unit coordinator.

For exams and in-semester tests, the use of AI and automated writing tools is not allowed unless expressly permitted in the assessment instructions.

The icons in the assessment table above indicate whether AI is allowed – whether full AI, or only some AI (the latter is referred to as “AI restricted”). If no icon is shown, AI use is not permitted at all for the task. Refer to Canvas for full instructions on assessment tasks for this unit.

Your final submission must be your own, original work. You must acknowledge any use of automated writing tools or generative AI, and any material generated that you include in your final submission must be properly referenced. You may be required to submit generative AI inputs and outputs that you used during your assessment process, or drafts of your original work. Inappropriate use of generative AI is considered a breach of the Academic Integrity Policy and penalties may apply.

The Current Students website provides information on artificial intelligence in assessments. For help on how to correctly acknowledge the use of AI, please refer to the  AI in Education Canvas site.

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.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

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 Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

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 to discourse analysis	Lecture (2 hr)
Week 02	Appraisal (attitude)	Lecture and tutorial (3 hr)
Week 03	Appraisal (engagement, graduation)	Lecture and tutorial (3 hr)
Week 04	Identification (participant identification)	Lecture and tutorial (3 hr)
Week 05	Identification (reference chains)	Lecture and tutorial (3 hr)
Week 06	Ideation (taxonomy and lexical relations)	Lecture and tutorial (3 hr)
Week 07	Ideation (further lexical resources)	Lecture and tutorial (3 hr)
Week 08	Periodicity (scaffolding discorrse)	Lecture and tutorial (3 hr)
Week 09	Conjunction (external)	Lecture and tutorial (3 hr)
Week 10	Conjunction (internal)	Lecture and tutorial (3 hr)
Week 11	Negotiation (speech function)	Lecture and tutorial (3 hr)
Week 12	Negotiation (exchange structure)	Lecture and tutorial (3 hr)
Week 13	Genre and register	Lecture and tutorial (3 hr)

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

The textbook for this course is:

Martin, J. R. and Rose, D. (2007) Working with Discourse: Meaning beyond the clause. London: Continuum. (WWD)

This should be available at the Coop Bookshop.

The readings each week are:

1 Introduction WWD Chapter 1

2 Appraisal (attitude) WWD Chapter 2 - Appraisal

3 Appraisal (engagement & graduation) WWD Chapter 2 - Appraisal

4 Negotiation (speech function and exchange structure) WWD Chapter 7 – Negotiation

5 Negotiation (speech function and exchange structure) WWD Chapter 7 – Negotiation

6 Identification (participant identification) WWD Chapter 5 - Identification

7 Identification (reference chains) WWD Chapter 5 - Identification

8 Ideation (taxonomy and lexical relations) WWD Chapter 3 - Ideation

9 Ideation (activity, figures, grammatical metaphor) – Reading to be supplied.

10 Conjunction (external) WWD Chapter 4 – Conjunction

11 Conjunction (internal) WWD Chapter 4 - Conjunction

12 Periodicity (scaffolding discourse) WWD Chapter 6 – Periodicity

13 Genre & register (modelling social context) WWD Chapter 8 – Tackling a Text, 9 – Connections

Other optional readings for deeper analysis:

Martin (1992) English Text: System and Structure. Amsterdam: John Benjamins.
A more in depth look at discourse semantics that Working With Discourse is derived from.

Martin and Rose (2008) Genre Relations: Mapping Culture. London: Equinox.
A detailed discussion of genre, for your final assignment.

Other optional readings will be suggested from time to time in the lectures.

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. By the end of this unit a student will be able to: - demonstrate an understanding of the fundamental principles of discourse anlaysis analysis
LO2. demonstrate an understanding of the dependencies between various discourse systems and their role in realising context
LO3. understand and deploy argumentation to motivate descriptions and choose among competing options
LO4. read and understand academic articles in the field of discourse analysis
LO5. apply advanced technical and conceptual skills to measure and analyse similarities and differences between texts from the perspective of discourse anlaysis
LO6. begin working independently to research and analyze texts in innovative ways; begin to able to undertake discourse analysis projects independently and in collaboration with mentors and peers
LO7. appreciate potential applications of discourse analysis in educational, clinical and forensic contexts

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.

This course is developed in response to feedback.

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) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

LNGS3609: Text and Context

Semester 1, 2025 [Normal day] - Camperdown/Darlington, Sydney

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Use of generative artificial intelligence (AI) and automated writing tools

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Support for students

Weekly schedule

Weekly schedule

Study commitment

Required readings

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links