Generative AI (GenAI) brings new challenges and opportunities at an exponential speed. The explosive appearance of AI tools and materials in higher education is transforming the ways of teaching, learning, and assessing (Attewell, 2025).
I look at the field of Creative Computing, where students use GenAI not just for writing, but to engage in a range of programming practices: writing code, debugging, explaining the code, setting up workspaces, writing code descriptions, and more. In programming, AI literacy often refers to a set of technical and practical skills closely related to computer science. Dincă et al. (2023) highlight that the benefits of AI coding tools rely on the human programmers’ safeguard:
“The use of specialized AI tools in software development has the potential to increase productivity when utilized by experienced users, particularly for repetitive coding tasks. The implementations, however, must be subjected to meticulous scrutiny.”
This highlights that the barriers for students to be AI-literate: The ability to review, curate, and safeguard AI’s outputs assumes one to have strong technical skills. These skills can include being able to understand and correct programming concepts, and to accurately articulate tasks and goals when prompting the AI, and etc. Therefore, the challenge here is that, in order for one to become AI-literate in AI coding tools, one need to have a programming or computer science background in the first place.
Therefore, the problem of the use of AI coding tools in the pedagogy in creative computing is twofold: (a) the ability to use AI coding tools can be desired in future workspaces in the industry, we would therefore like to encourage the equal use and integration of these tools in students’ programming workflow, and (b) the misuse of AI coding tools (e.g., shortcut learning, misconduct) need to be avoid, and ensuring that those learning outcomes regarding technical programming skills can be accurately assessed.
My positionality
I’m an associate lecturer in the BSc Data Science and AI and MSc Creative Computing courses at CCI. During the ARP cycle, I’ll be teaching BSc year 1 students at the Mathematics and Statistics for Data Science unit. Apart from being a lecturer at the Creative Computing Institute, I am also a researcher and software engineer in a techno-scientific field of AI and music technology. In my teaching, I often consider the demystifying aspect of technologies – to share the technical know-how.
I started using AI coding tools about a year ago, and now I use them extensively in my technical practice for productivity.
Next step
To figure out what would the “actions” be in this action research project, I started by looking at relevant existing documents/guidelines on using AI in higher education, as well as reflecting on my teaching practices. Next step: 2. Relevant Documents and Contextual Challenges.
Reference list at: https://jaspersz.myblog.arts.ac.uk/2025/11/20/arp-references/