Agenda for CCCC business meeting
Kim Gainer
The Intellectual Property in Composition Studies Standing Group invites conference attendees to its open annual meeting to discuss intellectual property and writing topics such as copyright, fair use, text ownership and authorship, remixing, open sharing, appropriation, and generative AI. During this meeting, the Standing Group will consider how recent developments in intellectual property conversations and policies intersect with composition, rhetoric, and writing studies. Participants will talk about how generative AI could influence IP policies related to instruction and assessment, student intellectual property, and how to teach IP in the classroom. Instructors, administrators, graduate students, and librarians are encouraged to join in.
The Standing Group would like to request the same Special Interest Group Thursday evening time slot that it was assigned in 2024. We request a room that can accommodate approximately30 to 40 people with round tables set up for discussion and an overhead projector.
Date Requested: Thursday SIG Business Meeting Slot
Remixing with AI: Pedagogical and Rhetorical Implications
Annotation
GAI both contributes to and complicates composition. It can be part of the remixing process in a course approaching Plato’s dialogues as texts to be theatrically transformed. Process-based reflective approaches to teaching writing can be augmented by incorporating multimodal activities with GAI. On the other hand, LLM output is patchwriting-adjacent, with implications for teaching research.
Proposal Description
ChatGPT became available in November 2023. Over a year later, similar AI bots, grounded in LLMs, have proliferated; sufficient time has passed to gauge how GAI both contributes to and complicates the educational enterprise. In “’What? A Flippin’ Skit?’ Remixing and Performing Plato’s Dialogues,” Speaker 1 demonstrates how LLMs become part of the remixing process in a cross-listed undergraduate/graduate survey course in ancient rhetoric that approached Plato’s dialogues as texts to be theatrically transformed. In academia, Plato’s dialogues have been elevated as foundational philosophical treatises, though scholars in ancient rhetoric and classics know them as pieces of creative writing, essentially plays. The class used LLMs as tools to begin the transformation, radically adapting the dialogues, translating the text into contemporary conversational language, writing additional lines, gender- and race-swapping characters, integrating music and movement, and creating original costumes. Speaker 2, in “Re-reading the Limits of Linguistic Abstraction: Naïve and Visionary Multimodal Composition with Generative AI,” explores how process-based reflective approaches to teaching writing can be augmented by incorporating multimodal and GAI activities. Forms of GAI available for language (LLMs) and images (GANs) offer important approaches for teaching the interconnectedness of different textual modes. LLM-generated linguistic descriptions of visual texts and parallel visual texts from GAI applications can permit the interrogation of Mariolina Salvatori's characterization of "writers as visionary shapers of meaning." Such interrogations challenge common views of GAI-produced texts as one-shot instances of frozen intellectual capital, instead allowing for a process-based perspective on the back-and-forth writerly labor negotiating between GAI-produced linguistic representations of visual texts and GAI-produced visual representations of linguistic texts. Speaker 3, in “GAI as Patchwriting: Online Sources, Training Data, and the Research Writing Course,” discusses how LLM output is patchwriting-adjacent and the resulting implications for teaching research. GAI output is not identical to patchwriting, however, because the training data, while drawn from online sources, is not the same as those online sources. GAI generates purported information through identification of word patterns rather than via links to information contained in the training data. As writing teachers, especially when teaching research writing, we need to understand how GAI constructs its output so that we can help our students grasp how LLMs work, including how they can mislead users. While some major media outlets are suing GAI companies for their use of texts for training data, others are licensing their texts to the GAI companies for use in future training. These media companies host the sources that we would like our students to use and document. However current technology does not allow users to access these publications as sources but only as traces within summations, sometimes inaccurate, of sources. For students to understand the limitations of GAI in conducting research, they need to understand this important distinction between traditional research and GAI output. Following the presentations by the three panelists, attendees will be invited to participate in the discussion, including consideration of how they can integrate GAI into their own classes while simultaneously helping students to recognize both the potential and the limitations of GAI and LLMs.
Stedman, Kyle D
Hi Kim,
When I lead a “table” (yes, in quotation marks), it’s typically on the pedagogical side—but I don’t have anything particularly on my mind beyond simply asking everyone how IP issues are affecting their teaching these days.
With our business meeting on Thursday morning and the sponsored panel (which partly includes pedagogy, right?) not until Saturday morning, perhaps Kim, Laurie, Clancy, and/or Mike could briefly preview us on the implications of AI they’ll be focusing on there?
(I’m aware of how empty this response is of actual content…maybe as I think more about it I’ll get more ideas?)
Thanks for starting the conversation,
Kyle
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Jim Purdy
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BRADLEY BLECK
Bradley Bleck
Spokane Falls CC
Spokane, WA
509.533.3572