MCGY1030: Semester 1, 2026

Units MCGY1030 Semester 1 2026 [Normal day]

Unit outline_

MCGY1030: This Is Music

Semester 1, 2026 [Normal day] - Sydney

Overview

This course introduces students to the different ways of thinking about music that bind together our Conservatorium culture. It is a course concerned with 'big' questions: What exactly is a musical work? What do we hear when music is played? How do we go about making new music and how do we make old music new again? In grappling with these questions, students learn how to formulate persuasive arguments about the nature of music in general and the significance of musical works and artists in particular. The course is broken into four three-week episodes: Talking about Music, Making Music, Listening to Music and Learning about Music. Lectures from performers, composers, music educators and musicologists comprise each of these episodes and cover the wide variety of music genres and approaches to music making taught at the Conservatorium. As students hone their philosophical positions in relation to the course's 'big' questions, they are therefore simultaneously introduced to the constellation of ideas that constitute our musical world.

Unit details and rules

Academic unit	Analysis, History and Cultural Studies
Credit points	6
Prerequisites ?	None
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Shin Kang Lee, shinkang.lee@sydney.edu.au
Lecturer(s)	David Larkin, david.larkin@sydney.edu.au
Lecturer(s)	Shin Kang Lee, shinkang.lee@sydney.edu.au
Tutor(s)	Jeremy Rose, jeremy.rose@sydney.edu.au

Assessment

The census date for this unit availability is 31 March 2026

Details
Criteria

Type	Description	Weight	Due	Length	Use of AI
Contribution	In Class Contribution In class contribution of students to discussion, assessed by quality and quantity. This is not an assessment of attendance and does not require marking after class.	20%	Ongoing	n/a	AI allowed
Outcomes assessed:
Out-of-class quiz	Early feedback task Canvas quiz #earlyfeedbacktask	0%	Week 02 Due date: 08 Mar 2026 at 23:59	15-20 minutes	AI allowed
Outcomes assessed:
Presentation	Lecture response Response to 1 lecture (multi-format options)	10%	Week 03 Due date: 15 Mar 2026 at 23:59	3 min	AI allowed
Outcomes assessed:
Written work	Article analysis Article analysis	10%	Week 06 Due date: 05 Apr 2026 at 23:59	600 words	AI allowed
Outcomes assessed:
Q&A following presentation, submission or placement	Q&A (Group Presentation) Q&A	10%	Week 07 Due date: 14 Apr 2026 at 23:59	5 min	AI prohibited
Outcomes assessed:
Presentation	Group presentation Group presentation on article analysis (followed by secure Q&A)	10%	Week 07 Due date: 14 Apr 2026 at 23:59	5 min	AI allowed
Outcomes assessed:
Written work	Sound-based analysis Sound-based analysis	10%	Week 09 Due date: 03 May 2026 at 23:59	400 words	AI allowed
Outcomes assessed:
Written work	Final essay Research topic exploration	30%	Week 13 Due date: 31 May 2026 at 23:59	1000 words	AI allowed
Outcomes assessed:
= hurdle task ? = group assignment ? = early feedback task ?

Early feedback task

This unit includes an early feedback task, designed to give you feedback prior to the census date for this unit. Details are provided in the Canvas site and your result will be recorded in your Marks page. It is important that you actively engage with this task so that the University can support you to be successful in this unit.

Assessment summary

Early Feedback Task
Participation
Lecture response
Group presentation
Q&A (immediately following group presentation)
Article analysis
Sound based analysis
Final assignment

Detailed information for each assessment can be found on Canvas.

Assessment criteria

See rubrics posted on the Canvas site.

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	This is My Music	Lecture (2 hr)
Week 01	This is My Music	Tutorial (1 hr)
Week 02	This is Good Music?	Lecture (2 hr)
Week 02	This is Good Music?	Tutorial (1 hr)
Week 03	This is Music on Country	Lecture (2 hr)
Week 03	This is Music on Country	Tutorial (1 hr)
Week 04	This is a Score	Lecture (2 hr)
Week 04	This is a Score	Tutorial (1 hr)
Week 05	This is a Performance	Lecture (2 hr)
Week 05	This is a Performance	Tutorial (1 hr)
Week 06	This is a Musical Work	Lecture (2 hr)
Week 06	This is a Musical Work	Tutorial (1 hr)
Week 07	Music and the Body	Lecture (2 hr)
Week 07	Music and the Body	Tutorial (1 hr)
Week 08	Music and the Supernatural	Lecture (2 hr)
Week 08	Music and the Supernatural	Tutorial (1 hr)
Week 09	Music and Nature	Lecture (2 hr)
Week 09	Music and Nature	Tutorial (1 hr)
Week 11	Music and Conflict	Lecture (2 hr)
Week 11	Music and Conflict	Tutorial (1 hr)
Week 12	Music and Peace	Lecture (2 hr)
Week 12	Music and Peace	Tutorial (1 hr)

Attendance and class requirements

Lecture recording: Lectures for this unit of study will be recorded and made available to students via Canvas.

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

Readings are self-selected by students in this course and form part of the assessment structure of their assignments.

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. Identify appropriate primary resources for a project
LO2. Evaluate secondary resources in terms of quality of argumentation, including the impact of sociohistorical context on music across genres
LO3. Analyze the structure of music and sound, and evaluate its sociohistorical significance
LO4. Develop appropriate approaches to individual and collaborative projects, with consideration of appropriate methodology, including cultural difference where relevant

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.

Assignments have been revised on the basis of USS feedback.

Additional information

Disability Services

The University is committed to supporting students to achieve their best possible results. The University’s Disability Services offer a range of services and adjustments to minimise the impact of any disability on your learning experience and to optimise your academic success.

Please see: http://sydney.edu.au/study/academic-support/disability-support.html for more information and to register for relevant support.

Learning analytics

Participation in this unit of study permits the University to use your learning analytics for the purpose of improving your learning. This includes data from the Canvas website, and the results of the Unit of Study Survey conducted at the end of the semester.

Students should complete the Unit of Study Survey at the end of this unit of study. Comments and survey results are confidential. Only the Unit of Study coordinator, the Associate Dean (Education), and the Head of School and the Dean can view student comments made in this survey.

It is essential that you complete this survey so that we can maintain the highest standards of teaching at the SCM and the University.

Disclaimer

Important: the University of Sydney regularly reviews units of study and reserves the right to change the units of study available annually. To stay up to date on available study options, including unit of study details and availability, refer to the relevant handbook.

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

Early feedback task

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