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Unit outline_

CMPN1220: Foundations of Digital Music and Media

Semester 1, 2024 [Normal day] - Sydney

Foundations of Digital Music will provide students with a broad understanding of the theoretical concepts of digital music. The unit includes a historical overview in the development of sound-based composition and creativity from its initial beginnings with the advent of sound recording through to the emergence of computer-based applications to create and organise sounds in time and space. The unit will focus on the approaches taken over the last century to record, transform and organise sound in a variety of creative contexts, ranging from early electroacoustic music experiments, through to contemporary electronic music production. Repertoire from the vast field of sonic arts will be covered to offer a new perspective on audio and sound production in today's contemporary music scene.

Unit details and rules

Academic unit Composition and Music Technology
Credit points 6
Prerequisites
? 
None
Corequisites
? 
None
Prohibitions
? 
None
Assumed knowledge
? 

None

Available to study abroad and exchange students

Yes

Teaching staff

Coordinator Benjamin Carey, benjamin.carey@sydney.edu.au
Lecturer(s) Benjamin Carey, benjamin.carey@sydney.edu.au
The census date for this unit availability is 2 April 2024
Type Description Weight Due Length
Online task Early Feedback Task - Canvas quiz
Canvas quiz based on content from unit outline + Week 1 #earlyfeedbacktask
0% Week 03
Due date: 05 Mar 2024 at 23:59
5 - 10mins
Outcomes assessed: LO3
Small test Listening test
Aural assessment
30% Week 05
Due date: 19 Mar 2024 at 13:00
1 hour
Outcomes assessed: LO1 LO4 LO3 LO2
Presentation Production Analysis Presentation
Production Analysis
30% Week 08
Due date: 16 Apr 2024 at 13:00
10 minute Presentation
Outcomes assessed: LO2 LO4 LO3
Assignment Essay and Q+A/Viva Voce
Written and Oral assessment
40% Week 13
Due date: 24 May 2024 at 23:59
2500 words + 5 minute Q+A/Viva Voce
Outcomes assessed: LO1 LO2 LO3 LO4

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: A mandatory, unweighted early feedback task based on content from the Unit of Study Outline, and Week 1 lecture

 

  • Listening test: The in-class listening test covers repertoire covered during previous classes, and in the online listening list linked to in the class Canvas site. This test is designed for students to display their developing knowledge of the range of styles, aesthetics and
    technological approaches present in the field of digital music and media.

 

  • Production Analysis Presentation: In this task, you are required to choose a piece of electronic music to analyse for its innovative production techniques. The piece of music must be of your own choosing, and can be historical or contemporary, however it may not be one that has been covered in class or in our online listening list. The presentation should break down the technical components of the work by any means necessary, but should include audio-visual examples as well as contextual/historical research on the techniques present in the work. You may choose to focus deeply on a subset of the techniques present in the work (e.g. a composer’s approach to spatialisation or use of synthesis techniques), or you may choose to look at the breadth of techniques present in the piece.

 

  • Essay and Q+A/Viva Voce Task: Choosing from a topic of interest from across the range of topics covered this semester, write an in-depth essay that investigates a particular musical style, compositional approach or technological development in the field of digital music and media. The essay should include substantial literature research of the topic in question, as well as musical analysis and historical context. You are allowed to use Generative AI (ChatGPT3.5) in preparation for this task, however, you are required to demonstrate your knowledge of your topic, as well as your use of Generative AI in a 5-minute Q+A Viva Voce in Week 13 of Semester. Use of ChatGPT is to be restricted to the free and publicly available GPT3.5 version of the software. The software should not be used to write your essay for you, but can be used to increase your knowledge of the topic area through in depth collaborative reflection, workshopping of your argument, and/or editing and revision of your essay topic. Your use of such software needs to be referenced, and justified in the Viva Voce portion of the assessment.

Assessment criteria

The following assessment criteria are used for written work in this unit of study:

Result name

Mark range

Description

High distinction

85 - 100

Demonstrates high level of initiative in research and reading; sophisticated critical analysis of evidence; high level engagement with theoretical issues, innovative use of reading/research material and impressive command of underlying debates and assumptions; properly documented and written with style, originality and precision.

Distinction

75 - 84

Demonstrates initiative in research and wide, appropriate reading; complex understanding of question and ability to critically review material in relation to underlying assumptions and values; analyses material in relation to empirical and theoretical contexts; properly documented; clear, well-developed structure and argument with some signs of literary style.

Credit

65 - 74

Evidence of broader understanding than pass level; offers synthesis with some critical evaluation of material; coherent argument using a range of relevant evidence; some evidence of independent thought, good referencing. A high credit (70-74) shows some evidence of ability to problematise and think conceptually.

Pass

50 - 64

Written work meets basic requirements in terms of reading/research; relevant material; tendency to descriptive summary rather than critical argument; makes a reasonable attempt to avoid paraphrasing; reasonably coherent structure; often has weaknesses in particular areas, especially in terms of narrow or underdeveloped treatment of question; acceptable documentation.

Fail

0 - 49

Work may fail for any or all of the following reasons: Unacceptable paraphrasing; irrelevance of content; poor spelling; poor presentation; grammar or structure so sloppy it cannot be understood; failure to demonstrate understanding of content; insufficient or overlong word length.

For more information see guide to grades.

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.

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

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

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 2023 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 2023. 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

WK Topic Learning activity Learning outcomes
Week 01 Introduction: what is digital music? Global trends in digital music and media. From compositional aesthetics to contemporary digital cultures. Lecture and tutorial (3 hr)  
Week 02 Dreaming of the future - early electronic musical instruments: Intonarumori, Theremin, Ondes Martenot, Trautonium etc. Lecture and tutorial (3 hr)  
Week 03 Sampling in the wild - the significance of sampling in contemporary music culture. History, techniques, aesthetics and ethics of sampling Lecture and tutorial (3 hr)  
Week 04 Sound synthesis - history, methods, and techniques Lecture and tutorial (3 hr)  
Week 05 Listening Test 1. In class listening and practical activities. Lecture and tutorial (3 hr)  
Week 06 Sound processing and electronic production - audio effects and sound processing, history and techniques Lecture and tutorial (3 hr)  
Week 07 Mapping the digital - historical overview and theoretical concepts of digital audio (sampling theorem, bit depth, buffer sizes, non-real-time vs real-time audio) Lecture and tutorial (3 hr)  
Week 08 Production Analysis Presentations. Practical Activities. Lecture and tutorial (3 hr)  
Week 09 Shortcuts to Digital Sound - examining the role of presets in digital music production. Practical synthesis and sound design session Lecture and tutorial (3 hr)  
Week 11 DJ Culture and live electronic performance - development of performance practices, historical and contemporary tools and techniques Lecture and tutorial (3 hr)  
Week 12 Visualisation and sonification - synergies between sound, image, and data. Introduction to music and sound analysis and representation methods Lecture and tutorial (3 hr)  
Week 13 Essay Q+A/Viva Voce Assessment Lecture and tutorial (3 hr)  

Attendance and class requirements

Attendance: Students are expected to attend a minimum of 90% of timetabled activities for a unit of study, unless granted exemption by the Dean, Head of School or professor most concerned. The Dean, Head of School or professor most concerned may determine that a student fails a unit of study because of inadequate attendance. Alternatively, at their discretion, they may set additional assessment items where attendance is lower than 90%.

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.

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.

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

  • LO1. recognise repertoire from various periods in the development of electronic and digital music
  • LO2. demonstrate analytical skills and methodologies to describe sounds and non-traditional musical outputs
  • LO3. demonstrate a clear understanding of the techniques used to create music in the digital domain
  • LO4. demonstrate cultural competence to access available resources to explore new avenues in digital music production.

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
GQ1 GQ2 GQ3 GQ4 GQ5 GQ6 GQ7 GQ8 GQ9

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

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

More information can be found on Canvas.

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.