TextGenEd: Teaching with Text Generation Technologies

Edited by Annette Vee, Tim Laquintano, and Carly Schnitzler

WAC Clearinghouse, Aug 2023


Abstract

Generative AI is the most influential technology in writing in decades—nothing since the word processor has promised as much impact. Publicly-accessible Large Language Models (LLMs) such as ChatGPT have enabled students, teachers, and professional writers to generate writing indirectly, via prompts, and this writing can be calibrated for different audiences, contexts and genres. At the cusp of this moment defined by AI, TextGenEd collects early experiments in pedagogy with generative text technology, including but not limited to AI. The fully open access and peer-reviewed collection features 34 undergraduate-level assignments to support students' AI literacy, rhetorical and ethical engagements, creative exploration, and professional writing text gen technology, along with an Introduction to guide instructors' understanding and their selection of what to emphasize in their courses. TextGenEd enables teachers to integrate text generation technologies into their courses and respond to this crucial moment.


Introduction

by Tim Laquintano, Carly Schnitzler, and Annette Vee

AI Literacy

  1. Testing ChatGPT Response Variety to Introduce Natural Language Processing, Elisa Beshero-Bondar [View]
    DOI: 10.37514/TWR-J.2023.2982.2.01
  2. Understanding Markov Chains, Gabriel Egan [View]
    DOI: 10.37514/TWR-J.2023.2982.2.02
  3. Neuroqueering AI: The Text Generator as Emergent Collaborator, Natalie Goodman [View]
    DOI: 10.37514/TWR-J.2023.2982.2.03
  4. Transforming Writing Assignments with AI: Approaches for Using Artificial Intelligence for Fostering Student Engagement and Comprehension, Daniel Hutchinson and Erin Jensen [View]
    DOI: 10.37514/TWR-J.2023.2982.2.04
  5. Rhetorical Analysis of Predictive LLMs, Alan Knowles [View]
    DOI: 10.37514/TWR-J.2023.2982.2.05
  6. Learning about Text Technology through the LLM Generation of Papers, Nick Montfort [View]
    DOI: 10.37514/TWR-J.2023.2982.2.06
  7. Critical Assessment and Analysis Exercise, Nathan Murray and Elisa Tersigni [View]
    DOI: 10.37514/TWR-J.2023.2982.2.06

Creative Explorations

  1. Cyborg Texts: A Procedural Creativity Assignment, Jason Boyd [View]
    DOI: 10.37514/TWR-J.2023.2982.2.08
  2. Spellcraft & Translation: Conjuring with AI, Dana LeTriece Calhoun [View]
    DOI: 10.37514/TWR-J.2023.2982.2.09
  3. Made Not Only By Me: Coauthoring a Children’s Book with Text and Image Generation, Brandee Easter [View]
    DOI: 10.37514/TWR-J.2023.2982.2.10
  4. cmpttnl cnstrnt: An Exercise in Constraint and Prompt Engineering, Douglas Luman [View]
    DOI: 10.37514/TWR-J.2023.2982.2.11
  5. The Grand Exhibition of Prompts, Mark C. Marino and Rob Wittig [View]
    DOI: 10.37514/TWR-J.2023.2982.2.12
  6. Different Ways of Narrating with Curveship-js, Nick Montfort [View]
    DOI: 10.37514/TWR-J.2023.2982.2.13
  7. Deconstructing and Reconstructing Genre and Form with Tracery, Mark Sample [View]
    DOI: 10.37514/TWR-J.2023.2982.2.14
  8. Who's Talking: Dada, Machine Writing, and the Found: RiTa.js for Visual Artists and Writers, kathy wu [View]
    DOI: 10.37514/TWR-J.2023.2982.2.15

Ethical Considerations

  1. Promoting Ethical Artificial Intelligence Literacy with Generative AI Tools Like ChatGPT on an Undergraduate Course Project, Mike Frazier and Lauren Hensley [View]
    DOI: 10.37514/TWR-J.2023.2982.2.16
  2. The Term Paper Turing Test: “Cheating” for AI Literacy, Paul Fyfe [View]
    DOI: 10.37514/TWR-J.2023.2982.2.17
  3. Teaching Social Identity and Cultural Bias Using AI Text Generation, Christopher D. Jimenez [View]
    DOI: 10.37514/TWR-J.2023.2982.2.18
  4. Professor Bot: An Exercise in Algorithmic Accountability, Jentery Sayers [View]
    DOI: 10.37514/TWR-J.2023.2982.2.19
  5. AI In First Year Writing Courses, Marc Watkins [View]
    DOI: 10.37514/TWR-J.2023.2982.2.20
  6. Repetition, Zach Whalen [View]
    DOI: 10.37514/TWR-J.2023.2982.2.21

Professional Writing

  1. The Paranoid Memorandum: A Generative AI Exercise for Professional Communication, Jason Crider [View]
    DOI: 10.37514/TWR-J.2023.2982.2.22
  2. Analysis of iterations of responses to human prompts: ChatGPT and automated writing, Huiling Ding [View]
    DOI: 10.37514/TWR-J.2023.2982.2.23
  3. Text Generators in Technical Communication: Summarizing Technical Documents, Douglas Eyman [View]
    DOI: 10.37514/TWR-J.2023.2982.2.24
  4. Translating a Policy Document into Plain English, Timothy Laquintano [View]
    DOI: 10.37514/TWR-J.2023.2982.2.25
  5. Professional Writing for Healthcare: Writing & Revising Research Summaries with Artificial Intelligence, Heidi A. McKee [View]
    DOI: 10.37514/TWR-J.2023.2982.2.26
  6. AI for Editing, Nupoor Ranade [View]
    DOI: 10.37514/TWR-J.2023.2982.2.27

Rhetorical Engagements

  1. Decoding an AI Bot’s Chatting Pattern: Text Generating Technology Analysis Assignment, Bhushan Aryal & Ordner W. Taylor [View]
    DOI: 10.37514/TWR-J.2023.2982.2.28
  2. Synthetic Metacognition: Iterating Prompts with GPTs, Kyle Booten [View]
    DOI: 10.37514/TWR-J.2023.2982.2.29
  3. Using LLMs as Peer Reviewers for Revising Essays, Antonio Byrd [View]
    DOI: 10.37514/TWR-J.2023.2982.2.30
  4. Genre Generators, Addison Eldin [View]
    DOI: 10.37514/TWR-J.2023.2982.2.31
  5. Writing Against the Machine: Debating with ChatGPT, Justin Lewis and Ted Wayland [View]
    DOI: 10.37514/TWR-J.2023.2982.2.32
  6. Using AI Text as Prompts for Critical Analysis, Juan Pablo Pardo-Guerra [View]
    DOI: 10.37514/TWR-J.2023.2982.2.33
  7. Generate and Enact a Writing Style: Examining Writing Style Though Generative AI, John Silvestro [View]
    DOI: 10.37514/TWR-J.2023.2982.2.34
Front Matter

Read the collection's CFP and meet the editors. 

AI Literacy

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.

Creative Explorations

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. 

Ethical Considerations

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.

Professional Writing

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.

Rhetorical Engagements

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.