By Carly Schnitzler, Annette Vee, and Tim Laquintano
A little over four months after the publication of TextGenEd: Teaching with Text Generation Technologies, we're thrilled to highlight another 16 open-access assignments that enable teachers to integrate text generation technologies into their courses and respond to this crucial moment. TextGenEd was perhaps the first pedagogical collection explicitly focused on teaching writing with text generation technologies, but Continuing Experiments joins a rich ecosystem of open access collections including Harvard MetaLab's AI Pedagogy Project and the MLA-CCCC Joint Task Force's Exploring AI Pedagogy. Here, we publish the first of our planned semi-annual addendums: Continuing Experiments is a sustained response to the constant change that is built into teaching writing with text generation technologies. Amid the breakneck speed of AI developments, teachers are finding their footing in their classrooms by practicing, experimenting, and even resisting the tech in innovative ways.
One striking difference in the submissions for Continuing Experiments was the number of assignments incorporating prompt engineering. The call for the TextGenEd came out prior to the release of ChatGPT and the assignments reflect a range of work with text generation technologies from Markov chains to RNNs to LLMs. But almost all of the submissions for Continuing Experiments focused on LLMs, in particular ChatGPT or other openly accessible chat-based LLM interfaces. And we saw a new category emerge in prompt engineering: assignments that support students learning to iterate on their interactions with chatbots, honing the output towards particular goals. From logs that record their learning processes (Gogan) to reprogramming outputs to better reflect world Englishes (Gupta), this new category of assignments help students collaborate with the models in their current dominant interface.
Other assignments continue the work of TextGenEd in developing students' AI literacy, with a renewed focus on the ethical and cultural impacts of AI as a critical in understanding these tools (Gallagher). In the creative explorations category, resources like AI Dungeon (Eldin) and Midjourney (Hutchinson and Jensen) expand the repertoire of crafting and analyzing creative narratives with text and image generation tools. The reflections the assignment in our ethical considerations category makes are philosophical (Proulx), examining the question “How can we use Generative AI as a writing tool and still speak for ourselves?” through a specific disciplinary lens. Professional writing assignments demonstrate and probe the utility of LLMs in applications from transcription (Horton) to resume creation (Large). Students consider how computational machines have already and will become enmeshed in communicative acts (Gillo) and how we work with them to produce symbolic meaning (Gordon) in the rhetorical explorations category.
As in TextGenEd, each assignment is licensed CC-BY-NC and includes an abstract that provides a brief introduction and outcomes plus an "assignment in brief" table that includes Learning Goals; Original Assignment Context; Materials Needed; and Time Frame. These brief summaries and the generous licensing are meant to facilitate ease of use for teachers across diverse curricular contexts. Please make these assignments your own!
While there's good reason to resist the speed of AI development on the technological side, we believe in rapid publication of pedagogical responses. These assignments have undergone an accelerated editorial review and drafting process to showcase some of the thoughtful, of-the-moment experimentation happening in writing-intensive classrooms across disciplines.
As the name implies, we will continue to publish and share Continuing Experiments as text generation technologies and teaching evolve and inform one another. As you experiment and adapt these assignments and others in your own classrooms, please consider submitting to future editions! More information on our submission and publication processes can be found here. For now, we are so excited to share this latest collection of assignments with you.
The AI literacy grouping helps students to develop a crucial suite of critical thinking skills needed to work with emerging technologies: functional awareness, skepticism about claims, and critical evaluation of outputs.
Fact-Checking Auto-Generated AI Hype, by Anna Mills
Variation in the Writing Outputs of First-year Writing Students and Generative AI, Kayode Victor Amusan
AI Literacy: Real-World Cautionary Tales, by Maureen Gallagher
Creative explorations play around the edges of text generation technologies, asking students to consider the technical, ethical, and creative opportunities as well as limitations of using these technologies to create art and literature. Many of these assignments look beyond our contemporary scene of LLM text generation and lend valuable context to our current moment, drawing from earlier technologies or historicizing connections.
Narrative and Text Generation AI, by Addison Eldin
Writing Imagery: Multimodal AIs in History and Digital Art, by Daniel Hutchinson and Erin Jensen
From Consumer to Creator: Analyzing and Producing Machine-Made Stories, by Marc Watkins
In the ethical considerations category, assignments are split between two primary foci—the first engages students in the institutional ethics of using LLMs in undergraduate classrooms and the second attends to the ethical implications of LLMs and their outputs.
Speaking and Thinking for Ourselves, by Jeremy Proulx
This section presents assignments that enable students to understand how computational writing technologies might be integrated into workplace contexts. Unlike academic discourse, professional writing is not grounded in an ethos of truth-seeking and critical inquiry; it tends to be grounded in an ethos of efficacy as well as constraints of legality and workplace ethics.
The "First Pass, Second Pass" Strategy of AI and Traditional Methods of Data Transcription in Qualitative Research, by Analeigh E. Horton
Writing for Career Readiness: Engaging ChatGPT to Develop Resume Bullet Points, by Sara Large
In Continuing Experiments, we added a new subcategory—prompt engineering—to reflect the continued importance of iterating prompts and platforms to achieve writing goals with generative AI.
Rhetorical Prompt Engineering, by Bryan Kopp, Christopher McCracken, Lindsay Steiner, and Louise Zamparutti
Introductory Activity for Generative AI, by Josh Anthony
Applying Advanced Generative AI Prompting Techniques, by Emily Dux Speltz and Abram Anders
The Gen/ReGen Log: Refining the Rhetoric of Structured Prompts, by Brian Gogan
Translinguo: Critically Making Chatbot Prototypes by Learning How to Write Generative AI prompts, by Anuj Gupta
These assignments ask students to consider how computational machines have already and will become enmeshed in communicative acts and how we work with them to produce symbolic meaning.
Collaborative Research with ChatGPT, by John Gordon
GenAI Platform Privacy Impact Assessment & Remediation, by Emily Gillo