• Class Number 5380
  • Term Code 3260
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Charles Martin
    • Charles Martin
  • Class Dates
  • Class Start Date 25/07/2022
  • Class End Date 28/10/2022
  • Census Date 31/08/2022
  • Last Date to Enrol 01/08/2022
SELT Survey Results

This course introduces the fundamentals of coding and design required to create expressive interactive artworks. Students will learn how to conceptualise, realise, and evaluate an original interactive artwork using a high-level programming language. They will experiment with computer graphics, sound, and input devices and learn programming concepts required for accomplishing their creative objectives.

The course introduces the creative possibilities presented by the computer in the modern art world, fundamental concepts of visual and interactive design, and recent developments in art and interaction computing. Topics covered include interactive and new media art, interaction design, program organisation, variables, control structures, graphics, and audio.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Describe the qualities of computer-based artworks and recent developments in interactive computational art.
  2. Apply knowledge of visual and physical interaction with a computer interface including recent developments.
  3. Design and construct computer programs in a programming language for interactive art.
  4. Create and evaluate an original and creative work of interactive art.

Research-Led Teaching

This course introduces aspects of computer-based art related to current research in computer art and music taking place at ANU. For instance, current computer-based artworks created by ANU staff will be discussed as case-studies in aspects of interaction. New techniques, such as creative applications of machine learning and artificial intelligence will be considered as extension material. The course draws upon the rich practice-led research experiences of the ANU computer science, art and music staff in exploring this field.

There are several textbooks available online through the ANU Library on p5.js and creative coding, these three cover similar topics to this course and are a good resource:

  • Make: Getting Started with p5.js. Lauren McCarthy, Casey Reas, and Ben Fry. 2015. (link)
  • Learn JavaScript with p5.js: Coding for Visual Learners. Engin Arslan. 2018. (link)
  • Coding Art: The Four Steps to Creative Programming with the Processing Language. Mathias Funk and Yu Zhang. 2021. (link)

Staff Feedback

Students will be given feedback in the following forms in this course:

  • written comments
  • verbal comments
  • feedback to whole class, groups, individuals, focus group etc

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). Feedback can also be provided to Course Conveners and teachers via the Student Experience of Learning & Teaching (SELT) feedback program. SELT surveys are confidential and also provide the Colleges and ANU Executive with opportunities to recognise excellent teaching, and opportunities for improvement.

Other Information

Please see the course policy on this website for further information: https://comp.anu.edu.au/courses/comp1720/policies/

Class Schedule

Week/Session Summary of Activities Assessment
1 Intro to coding in p5; what is art? Lab: basics of p5 - put a circle on the internet
2 Types and variables; random chance Lab: basics of p5 - shapes, colours, and coordinates
3 Conditionals and iteration; How to think about colour Lab: generative art with algorithms
4 Functions and arrays; how do we judge art? Lab: interactive art with p5
5 Objects; interactive art Lab: kaleidoscopes with functions and arrays
6 Code concepts revision, artist's statements, and interaction recap Lab: create a pokegarden with objects
7 Sound and music computing Lab: making sounds with p5
8 storyboards and trajectories; affordances and interfaces Lab: collections and structures in p5
9 recent developments in art and interactive computing Lab: major project storyboard
10 working with data Lab: major project toolbox
11 simulations and dynamics Lab: a sketch for your major project
12 creative machine learning Lab: final touches on your major project

Tutorial Registration

For lab registration and information see this page: https://comp.anu.edu.au/courses/comp1720/labs/

Assessment Summary

Assessment task Value Due Date Return of assessment Learning Outcomes
Pre-Lab and In-Lab Tasks 5 % * * 1,2
Assignment 1 15 % 15/08/2022 29/08/2022 3,4
Assignment 2 15 % 05/09/2022 19/09/2022 3,4
Assignment 3 15 % 04/10/2022 18/10/2022 3,4
Major Project 50 % 31/10/2022 * 1,2,3,4

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines , which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Integrity Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the Academic Skills website. In rare cases where online submission using Turnitin software is not technically possible; or where not using Turnitin software has been justified by the Course Convener and approved by the Associate Dean (Education) on the basis of the teaching model being employed; students shall submit assessment online via ‘Wattle’ outside of Turnitin, or failing that in hard copy, or through a combination of submission methods as approved by the Associate Dean (Education). The submission method is detailed below.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.


There are two participation requirements for this course:

  • Students are expected to participate in all learning activities in order to complete collaborative elements and receive peer feedback.
  • Some pre-lab and in-lab tasks involve in-class assessment so participation is required in order to gain a mark and feedback.

Assessment Task 1

Value: 5 %
Learning Outcomes: 1,2

Pre-Lab and In-Lab Tasks

Pre-Lab and In-Lab tasks are due in each lab from week 2 to week 11.

The Pre-lab task includes a weekly post on the course forum (100-200 words) and comments on two other posts. The content of the post is related to each week's lab.

In-lab tasks are the main content of lab which includes conceptualising and discussing computer-based artworks, experimenting with p5 code and collaborating with other students to develop interactive creative artworks. Your pre-lab work is due each week by the start of your lab and your in-lab tasks are assessed during the lab.

Late submission is not permitted.

Assessment Task 2

Value: 15 %
Due Date: 15/08/2022
Return of Assessment: 29/08/2022
Learning Outcomes: 3,4

Assignment 1

Assignment 1 involves creating a dynamic artwork in p5.js (see course website for required design specifications).

The artwork will be submitted as a GitLab repository consisting of p5.js code, assets and resources, an artist's statement, and a statement of originality.

Late submission is not permitted.

Assessment Task 3

Value: 15 %
Due Date: 05/09/2022
Return of Assessment: 19/09/2022
Learning Outcomes: 3,4

Assignment 2

Assignment 2 involves creating an interactive artwork in p5.js (see course website for required design specifications). The artwork needs to communicate a scene and include creative interactive features.

The artwork will be submitted as a GitLab repository consisting of p5.js code, assets and resources, an artist's statement, and a statement of originality.

Late submission is not permitted.

Assessment Task 4

Value: 15 %
Due Date: 04/10/2022
Return of Assessment: 18/10/2022
Learning Outcomes: 3,4

Assignment 3

Assignment 3 involves creating an interactive artwork with a flow of events in p5.js with multiple modes of input and output (see course website for required design specifications). The artwork needs to have a hook, last roughly 30 seconds, and leave an impression on the viewer.

The artwork will be submitted as a GitLab repository consisting of p5.js code, assets and resources, an artist's statement, and a statement of originality.

Late submission is not permitted.

Assessment Task 5

Value: 50 %
Due Date: 31/10/2022
Learning Outcomes: 1,2,3,4

Major Project

The Major Project involves creating a complete interactive artwork in p5.js that explores a given theme (see course website for the required thematic specification). Your goal is to provide an engaging user experience of roughly three minutes, but the exact nature of that experience is up to you.

The artwork will be submitted as a GitLab repository consisting of p5.js code, assets and resources, an artist's statement, an interaction statement, and a statement of originality.

Late submission is not permitted.

Academic Integrity

Academic integrity is a core part of the ANU culture as a community of scholars. The University’s students are an integral part of that community. The academic integrity principle commits all students to engage in academic work in ways that are consistent with, and actively support, academic integrity, and to uphold this commitment by behaving honestly, responsibly and ethically, and with respect and fairness, in scholarly practice.

The University expects all staff and students to be familiar with the academic integrity principle, the Academic Integrity Rule 2021, the Policy: Student Academic Integrity and Procedure: Student Academic Integrity, and to uphold high standards of academic integrity to ensure the quality and value of our qualifications.

The Academic Integrity Rule 2021 is a legal document that the University uses to promote academic integrity, and manage breaches of the academic integrity principle. The Policy and Procedure support the Rule by outlining overarching principles, responsibilities and processes. The Academic Integrity Rule 2021 commences on 1 December 2021 and applies to courses commencing on or after that date, as well as to research conduct occurring on or after that date. Prior to this, the Academic Misconduct Rule 2015 applies.


The University commits to assisting all students to understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. All coursework students must complete the online Academic Integrity Module (Epigeum), and Higher Degree Research (HDR) students are required to complete research integrity training. The Academic Integrity website provides information about services available to assist students with their assignments, examinations and other learning activities, as well as understanding and upholding academic integrity.

Online Submission

You will be required to electronically sign a declaration as part of the submission of your assignment. Please keep a copy of the assignment for your records. Unless an exemption has been approved by the Associate Dean (Education) submission must be through Turnitin.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Individual assessment tasks may or may not allow for late submission. Policy regarding late submission is detailed below:

  • Late submission not permitted. If submission of assessment tasks without an extension after the due date is not permitted, a mark of 0 will be awarded.

Please see our policy on late submission: https://comp.anu.edu.au/courses/comp1720/policies/#late-penalties

Referencing Requirements

The Academic Skills website has information to assist you with your writing and assessments. The website includes information about Academic Integrity including referencing requirements for different disciplines. There is also information on Plagiarism and different ways to use source material.

Returning Assignments

Assignments will be returned 10 working days after the submission date with feedback provided through GitLab. Pre- and in-lab assessment will have marks returned through Gradebook and feedback provided by tutors. Marks for the major project will be available when grades are released at the end of the semester.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure. Extensions may be granted for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Resubmission of Assignments

Please see our policy on appeals of assignment marks: https://comp.anu.edu.au/courses/comp1720/policies/#appeals

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information.
In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service – including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy.
If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes.

Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Charles Martin
(+612) 61253139

Research Interests

My research work is at the nexus of music technology, human-computer interaction and machine learning. I'm convinced that we can use computing systems to unlock new ways for people to be creative and enrich our everyday lives with new kinds of music and art. To do this, we need to imagine new kinds of computers, including embedding computers into new physical settings and to exploit machine learning to allow these computer systems to understand and interact with our complex creative activities.

My work involves:

  • new interfaces for musical performance
  • computational creativity
  • smartphone/tablet musical instruments
  • collaborative performance
  • co-creative interfaces
  • improvisation
  • percussive approaches to computer music

Charles Martin

By Appointment
Charles Martin
(+612) 61253139

Research Interests

Charles Martin

By Appointment

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