In creative disciplines such as Media Arts and Production, GenAI offers potential for exploration and collaboration, as well as ways to save time and improve technical outcomes. However, it is still important to emphasise the value of authorial control or management of AI inputs and the fundamental skills students need to master so that they can judge the results from AI collaborations.
As presented at a ‘GenAI in the classroom’ panel at the recent Academic Forum, I have seen a mix of informal GenAI use by students as well as strategic integration of GenAI tools as part of overall subject design. This growing presence of GenAI in the classroom presents challenges for academic integrity that need to be balanced out with integrated assessment design strategies. The collection of sound and video media during field trips is one such strategy that we will be trialling.
Uncovering poor academic practice related to GenAI use often relies on monitoring work in progress and some detective work. The onus is on us as academics to keep up with the evolution and usage of GenAI tools being commonly used in our discipline. We have the responsibility to guide students effectively in class, but also set them up for how AI will be a key player in their post-university careers.
Informal use of GenAI in the classroom
In a class I’m teaching this session, I’ve seen an exponential growth in the informal use of GenAI. This has included:
- Students live-translating my speech and the slides (even though I provide them with a PDF before class)
- Students using GenAI tools during class to formulate responses to small group discussion tasks
According to the subject dashboard, my subject is made up of 100% international students. While some of these students still lack a degree of confidence in their spoken English, the standard of written expression in assessment submissions has significantly improved. This is to the point where assessment criteria around clarity of expression are less relevant. It is becoming more important to ensure that students can effectively engage with a brief, understand the conceptual framework of a subject and adhere to specific processes of creation.
Creative use of GenAI in the classroom
In the Media Arts and Production discipline, there are subjects where we actively encourage students to explore the creative potential of Gen AI.
- Experimental Media – in-class activities exploring the creative use of GenAI led by Justin Harvey whose area of research is focused in this area
- Screen Story – led by Matthew Dabner, students are given the option of using GenAI tools to generate pitch decks as an aide to presenting their screenplay concepts
- Experiential Media – in the subject I am coordinating, students can brainstorm options for project mood boards and rough UI designs using GenAI tools
Out in the field: Creative Practice
For the first core subject, of the proposed Bachelor of Creative Practice, assessments require students to make media projects across sound, animation and video. The assessments are themed around conveying a sense of place. The plan is for students to go on two field trips over the course of the session to gather sound and video material from which to make their assessment submissions.
There are fundamental skills associated with media gathering that will inform their future practice even if it is no longer lens- or microphone-based. We still want them to know what well recorded sound sounds like and the choices that result in producing well composed and communicative images. However, even with these designed-in controls, GenAI tools are available for the other parts of the production process. There are AI driven audio processors that can recover sound and give it a professional polish, as well as generative tools to adjust image content and fix technical issues such as focus and grading.
Trial and error = successful GenAI engagement
We need to become proficient in these tools ourselves and teach our students how to ethically use GenAI in their own professional practice. This is where the research–teaching nexus is so important for academics. We need to have the hands-on experience of applying and failing as well as succeeding with GenAI tools. We’ll only be able to identify what ethical use of these tools looks like in our areas of expertise through directly working with and then thinking through the implications of their application.
Our students will need to have an effective set of principals they can apply to using GenAI tools in their future careers. That will mean critical thinking frameworks so they can effectively respond to new developments, a level of mastery over what is currently available, and a flexible approach to imagining the jobs they’ll go into and the professional practices they’ll create.