Outline

  • Theme: Natural Intelligence / Biological Learning
  • Due: 25 June 2025, 23:55
  • Mark weighting: 25% total
  • Submission: Text/PDF upload in Wattle with code in GitLab.
  • Policies: see the policies page
  • Learning Outcomes Assessed: Learning Outcomes 2 and 3. Learning Outcome 1 is expected to be applied in creating artistic output.

The first 3 assessment tasks this year are called “Portfolio Item 1”, “Portfolio Item 2” and “Portfolio Item 3”. The written works and artistic responses you create will form part of your portfolio of works for EXTN1019B, along with your Final Project. All of your works will be available to view at the end of year exhibition. For an example and for inspiration, you can view the 2024 cohorts works here.

TEMPLATE: Fork and clone the template for this portfolio item

Theme: Natural Intelligence / Biological Learning

Portfolio Item 3 requires you to create an interpretation to the theme “Natural Intelligence / Biological Learning”.

You will create up to 3 artistic responses related to this theme. You will need to explain how your responses align with the theme. In your portfolio submission, you should have one major response and up to two instances of lab work that reflects your exploration of the theme and/or ml5 model you have used in your major work.

Digital technologies are hyper-driven by the concepts of Artificial Intelligence and Machine Learning, but what is Artificial Intelligence without a reference to some form of Natural Intelligence. Similarly, Machine Learning only exists relative to Biological Learning systems. You may interpret Natural Intelligence / Biological Learning in any number of ways. You may wish to draw upon works we have previously encountered in this course, including “Ways of Being”1, “Other Minds”2, or “The Spell of the Sensuous”3. You may also approach your teacher for inspiration.

Description

The third assessment task requires you to:

  • implement machine learning as a component of your artistic response to the theme
  • explore new realms of human-computer interaction to drive the user experience of your artwork and enhance your interpretation of the theme.
  • explain how your artistic response aligns with the theme (artist_statement.md)
  • explain the rationale of your human computer interaction (hci.md)
  • explain how you have used machine learning (ml.md)
  • explain how to interact with your artwork(s) (README.md)

Specification

File(s) Word Limit Description
artist-statement.md 600 words explaining your overall interpretation of the theme and how your reponses embodies the chosen topic. You may also include what other aspects of art, or meaning, you have chosen to investigate. Where relevant, you may explore your development process
hci.md 500 words Explain the rationale which has informed your interaction design, and how your interactivity enhances your interpretation of the theme. References should be included in this file
ml.md 500 words Describe and explain the purpose of the machine learning system(s) you have implemented and how your use of ML aligns with your interpretation of the theme. References should be included in this file
README.md up to 100 words how to interact with your artwork
sketch.js
(multiples)		 N.A. Your artistic responses. You only need one index.html. Machine learning resources should be included in the assets folder

## Development Process {#how-to}

Each week’s lab will contribute work that should be present in the portfolio.

Here are the things you should do when completing this assessment task:

  • Choose an interpretation of the theme and explore possible artistic responses to the theme. Explore HCI. Research Machine Learning.
  • Develop a plan for your:
    • artistic responses
    • human-computer interaction
    • plan to integrate machine learning in a way which enhances your interpretation of the theme
  • For each sketch, develop an artistic response which conveys your interpretation of the theme
    • make it interactive
    • make it meaningful
  • Write an artist statement which explains how your artwork represents your interpretation of the theme
    • The artist statement should be called artist-statement.md
  • Complete your Machine Learning documentation: ml.md
    • write about the origin of your ML techniques(s) (where it came from or what inspired this design)
    • explain how machine learning contributes to your interpretation of the theme
    • explain the dynamism4 of your ML system (if any)
  • Complete your human-computer interaction design documentation: hci.md
    • what inspires your human-computer interaction design?
    • what modes of human-computer interaction have you used?
    • how does your human-computer interaction form feedback loops between human and machine?
    • how have you developed the affordances (see also “The Design of Everyday Things”)?
  • Write a README.md document which explains how to interact with your artwork (a how to document)
  • Check against the specification, and submit

All documentation should be:

  • written using markdown. (PDF is an acceptable alternative)
  • include comprehensive referencing.

For each portfolio item this year, we either want you to create your own sketch, or extend some starter code we provide in class.
In either case, we want you to submit at least 2 non-trivial variations 5 of your sketch. This is an opportunity for you to experiment and explore different ways of implementing or expressing the same idea.

Submission Process

  1. Fork and clone the template repository.
  2. Include all files (program and documentation) in your repository
  3. Regularly push and commit to gitlab.
    We are expecting a history of commits.
  4. Zip your folder and submit to Wattle —
    this will timestamp your submission, and enable marking using the rubric.

Marking criteria

As discussed at the top of this page, Portfolio Item 3 makes up 25% of your overall mark for this course.

The marking criteria are:

  • critical engagement with the theme (20%) (LO #1)
  • human-computer interaction design (20%) (LO #2)
  • use of Machine Learning (20%) (LO #3)
  • creativity in coding, artistic output (20%) (LO #1 and #2)
  • addressing the specification (5%)
  • breadth of experimentation (submit 2-3 non-trivial variations) (5%) (LO #2)
  • use of version control (gitlab commit history) (5%)
  • referencing (5%) (LO #3)

Year 12 Portfolio Item 3 Assessment Rubric

  A Grade
(9-10)		 B Grade
(7-8)		 C Grade
(5-6)		 D Grade
(3-4)		 E Grade
(0-2)
Critical Engagement
LO #1
20%
artist-statement.md and sketches		 deep and critical engagement with the theme engages effectively with the theme engages appropriately with the theme engagement includes some references to the theme very limited engagement with the theme
Human-Computer Interaction
LO #2
20%
hci.md and sketches		 deeply explores and implements new ideas, theories, concepts or constructs in their development of human-computer interaction. Uses feedback loops between computer and humans to design an engaging experience for the user/audience. HCI strongly contributes to the interpretation of the theme explores several alternative concepts of human-computer interaction/modes of evolution over time, includes critical reflection of design (selection of appropriate interaction/responsiveness). HCI enhances the interpretation of the theme explores several interactions/modes of evolution over time. Limited critical reflection / alignment with the theme minimal exploration of human-computer interaction and/or evolution over time (only explores one interaction type). Describes modes of HCI used. HCI does not enhance the theme. no exploration of interaction or responsiveness or evolution over time. Names modes of HCI used. HCI detracts from the theme.
Use of Machine Learning
LO #3
20%
ml.md and sketches		 your use of ML connects deeply with your interpretation of the theme and/or you have developed and trained new ML systems using your own data and models. You have clearly explained the origins, operation, purpose and limitations of your ML models your use of ML connects effectively with your interpretation of the theme. You have effectively trained and used an existing ML system using your own data. You have explained the operation, purpose and limitations of your ML models your use of ML shows some connection to the theme. You have successfully adapted and applied pre-trained ML models. You have explained the operation and purpose of your ML model your use of ML shows limited connection to your interpretation of the theme. ML models have been applied in a limited manner. ML models are described. very limited use of inappropriate ML models which distract from your interpretation of the theme. Very limited ML model documentation
Creativity
LO #1 and #2
20%
sketches		 always employs creative thinking, drawing on a wide range of sources/influences, to develop surprising and innovative responses uses creative thinking, drawing on a range of sources/influences, to develop innovative responses uses critical thinking, drawing on a range of sources, to develop design solutions uses a limited range of sources to develop basic solutions develops very limited responses
Specification Satisfaction
5%
all files		 All elements present and comprehensively complete (artist-statement.md, ml.md, hci.md, README.md All elements present and completed to a good standard All elements present and complete Most elements present Significant elements (artistic statement.md, hci.md, ml.md, README.md) missing
Breadth of Experimentation
LO #3
5%
sketches		 3 or more significant variations of artistic responses (sketch.js, ML models) 2 or more non-trivial variations of artistic responses (sketch.js, ML models) 2 basic variations of artistic responses (sketch.js, ML models) 2 or fewer variations which demonstrate trivial variations a single code solution which demonstrates a trivial change to the provided code, or the use of generative AI to develop the code variation
Use of Version Control
5%
gitlab commit history		 significant use of gitlab throughout the project. Including early fork, and frequent commits strong use of gitlab throughout the project. Including early fork, and regular commits good use of gitlab throughout the project. a number of commits aligned with key development moments basic use of gitlab showing few commits no use of gitlab or other verifiable version control, or loss of code through negligence
Referencing
LO #3
5%
hci.md, ml.md		 comprehensive referencing using ANU School of Computing approved referencing style and only using key academic sources a good breadth of research references using ANU style using reputable academic sources satisfactory referencing using a well-known academic style using only academic sources basic references which are not comprehensive or using an unknown or unsupported referencing style or using non-academic sources very limited referencing using an unsupported style, or hallucinated references, or untrustworthy sources

FAQ

Can I work on it during the weekly labs/workshops?

Yes! So if you create something during the workshop which you want to include in your portfolio, then by all means include it. You’re also welcome to use time outside of class to work on the portfolio item.

How long should I spend on this every week?

Between 1 and 3 hours outside class time should be sufficient. The BSSS expects that you complete 1 hour outside class for each hour spent in class.

Can I use open-source code for my artistic response?

Yes, for sure – as long as you provide links to any code that you used and you make some interesting changes/additions of your own to the code. Ensure you reference the open-source code in your artist-statement.md

Can I use other artists’ work as inspiration for my sketches?

I don’t see why not :) You can absolutely still look for sources of inspiration and reference them in your artistic response (name of inspiration/artist, name of work, link to work). However it’s not part of the marking criteria and therefore isn’t mandatory.

When will I get my marks & feedback?

I will endeavour to complete marking within 2 weeks of submission.

Can I use generative AI to write my report, artist statement or code?

We will be exploring the development, creation and appropriate application of generative AI in generating text, image and audio this year. This is NOT an open-license to use generative AI to write code or your written responses.

So: how can you use it?

  1. Be explicit about your use: explain how and why you want/need to use generative AI to generate code or text.
  2. Write your own ideas: you must generate ideas from your own brain and not outsource the generation of ideas.
  3. Read! You must read your sources and understand them yourself. It is no good asking ChatGPT to understand for you. Reach out if you need help.
  4. Polish: Write your ideas down and once you have a draft you might use generative AI to help finesse your work.
  5. Be explicit: This course is all about creativity. Tell us how you completed this process and how this made you feel. Have you learned more, or learned less? Does it help reduce pressure? Does it make you feel unethical?
  6. Opt Out: Shout it from the rooftops: You do not have to use generative AI! To quote from The Incredibles: “No school like the old school”.

Bibliography and Footnotes

Oxford dictionary says that dynamism is ‘the quality of being characterized by vigorous activity and progress’ i.e the quality of being dynamic. Dynamic machine learning refers to an ML system that learns and changes over time. Thus in this context, dynamism is the ability for the ML system to learn and adapt over time.

  1. Bridle, James. (2022). Ways of being: Beyond human intelligence. Allen Lane, an imprint of Penguin Books. EAN/UPC: 9780241469651 ↩

  2. Godfrey-Smith, Peter. (2018). Other Minds: The Octopus, the Sea, and the Deep Origins of Consciousness. Harper Collins GB. ISBN: 9780008226299 ↩

  3. Abram, D. (1996). The Spell of the Sensuous: Perception and Language in a More-Than-Human World. Vintage Books. eISBN: 978-0-307-83055-5 ↩

  4. ↩

  5. We just want you to implement an idea and play around with your code to generate some interesting changes in the visuals/audio. Think of it like doodling – see where your mind takes you and then, when you see an output that you like, take a screenshot/screen recording of it. The non-trivial part just means your changes can’t be too simple (e.g. if the only variation you make is changing the background colour from grey to pink, that’s too simple) ↩

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