Fabiola Hanna
Generative AI in Teaching, for Media Practices: Programming
As the fellowship supported integrating Generative AI into an existing course,students explored critical approaches in the context of a graduate-level studio course that introduces programming to artists, scholars, and filmmakers at the School of Media Studies. Students were familiarized on how artists currently use Generative AI, providing hands-on experience developing their own approaches, and moved beyond both the hype and fear surrounding these tools toward critical engagement. Students engaged with AI tools to pay attention to three possible roles: teacher, coding co-author, and troubleshooting companion.
Faculty Reflection
Students demonstrated three distinct approaches to using Claude in their coding projects: full reliance (where some admitted they “would not know where to start” without it), hybrid supplementation (using Claude for specific challenges while maintaining project control), and strategic selection (reserving Claude for tedious tasks while tackling interesting problems independently). All students were surprised by Claude’s capabilities, particularly its comprehensive responses, ability to provide visual examples, proactive suggestion of improvements, and contextual understanding of projects. However, this sophistication came with complexity that some found difficult to fully comprehend or customize.
The ethical concerns raised by students clustered around three main areas: professional impact (worries about AI replacing programmers and job displacement), educational impact (concerns about reduced learning opportunities and understanding fundamentals), and responsibility (questions about using code without full comprehension and the ethics of submitting AI-assisted work). While students universally agreed on Claude’s efficiency and indicated they would use it again, they diverged significantly on whether this represented a positive or problematic development. Some felt grateful for the creative freedom it provided, while others felt intimidated by their dependency and worried about “robbing themselves of the experience to learn.” Individual perspectives ranged from concerns about environmental costs and cultural literacy to observations about inconsistent coding styles, revealing a sophisticated and nuanced understanding of AI’s complex role in education and
professional development.
Curriculum
Experiment 0: Setup and Decode + Experiment 1: Unfriendly Interfaces
Students covered HTML/CSS/JavaScript basics, variables, arrays, functions, and working with libraries like jQuery UI, using primarily hand-coding techniques and conventional programming methods.
Experiment 2: Browser Extension
For Experiment 2, I held a technical workshop on “Coding with AI as a collaborator,” teaching students to work with, debug, and refine AI-generated code. After Experiment 2, I asked the students in my class to fill out a questionnaire to reflect on their experience using Claude, covering their usage approach, any ethical or philosophical concerns that arose, surprising aspects of the tool, their emotional/mental responses to using it, and whether they would use it again for future assignments.
Student Feedback
The course evaluations reveal a complex response to AI-integrated programming education, with overall positive feedback but notable tensions around pedagogy. While students appreciated using Claude to learn JavaScript while class time was used for open dialogues and critique, some felt the balance tipped too heavily toward self-directed AI-assisted learning at the expense of foundational instruction. Although the course was well-received, I want to note that several students expressed worry and uncertainty about educational standards, which remind me of similar concerns when Wikipedia came out and the worries surrounding that. It took some time for universities to learn how to approach Wikipedia in the 2000s and this strikes me as a similar issue. Finally, I would like to insist on the major issue that needs to be contended with: the environmental costs and continued post- and de-colonial struggles with land and water grabs with unethical Big Tech. Universities should decide where they stand on these and support work that wrestles with these issues and finds approaches that students, faculty and staff would be happier to support.