Mountain Daylight Time GMT-6
Register here: https://forms.gle/8n79cWyN4ShChEeK9
We have a Discord server, but honestly aren’t using it much: https://discord.gg/a79DHf8E
All times are Mountain Daylight Time. Click on times to open Microsoft Teams meeting
9:00 Keynote: Dr. Stuart Selber–An AI Manifesto for Technical Communication Programs
10:00 A1: Innovating Technical Communication Education with AI: Experiences from Mercer University
Hannah Nabi, Lecturer, Department of Technical Communication, Mercer University
Bremen Vance, Assistant Professor, Department of Technical Communication, Mercer University
Pam Estes Brewer, Chair and Professor, Department of Technical Communication, Mercer University
A discussion of the department’s current initiatives in integrating AI into its teaching methods and strategic plan. The workshop is intended for educators, researchers, and practitioners in technical communication and education technology interested in AI’s role in education. The goals of this panel discussion are to:
- Present specific examples of AI use in technical communication education.
- Share outcomes and observations from these AI-integrated teaching methods.
- Discuss the effectiveness of AI tools in student learning and skill development.
- Consider the future role of AI in technical communication education.
11:30 B1: Teaching Authorship in the Age of AI
Yunus Doğan Telliel and Kevin Lewis
In this presentation, we discuss our findings from an ongoing research study examining students’ perceptions of authorship when working with generative AI tools in their writing projects. This research focuses on Worcester Polytechnic Institute’s Professional Writing Program, consisting of a student survey, a faculty survey, and a qualitative study of AI-related assignments in technical communication courses.
Beyond Perceptions: Surveying Student Experiences with Responsible AI Use in Writing Courses
John Sherrill and Michael Salvo
This 20-minute presentation will provide instructor and student experiences working with AI in professional writing courses, including an experience report of teaching a collaborative report about AI, and preliminary findings from a mixed-methods survey of student experiences using AI. Rather than focusing exclusively on student and instructor perceptions about AI use in the classroom, our presentation challenges common instructor perceptions about how students may be using generative AI and LLMs in the classroom by providing experiential and quantitative data about how AI is shaping professional writing.
Technical Writing and Generative AI: Some takeaways for ethical reflection
Manushri Pandya and Arthur Berger
How are technical writers actually using generative AI?
At times, technical writers report using generative AI in ways that run counter to prevailing narratives. We hope to use our survey along with continuous feedback to think more critically about what the core concerns of the field are to its practitioners, in order to achieve its mission of “advanc[ing] technical communication as the discipline of transforming complex information into usable content for products, processes, and services.” [1] To that end, this presentation seeks to explore and provide insight into the intersections between AI, its potential impact on the practice of technical communication, its ethical implications, as well as its pedagogical applications and/or challenges in technical writing. [1] – STC mission from https://www.stc.org/about-stc/mission-a-vision/ Note: This is a collaborative project between Arthur Berger, President STC-Carolina; Manushri Pandya, PhD Student at NC State.
1:00 C1: A Model for Levels of Autonomy in Technical Communication
Michael J. Klein and Philip L. Frana
Department of Interdisciplinary LIberal Studies
James Madison University
The authors propose a pathway for understanding levels of autonomy in technical communication, presenting a four-quadrant contextual model for AI in technical communication: (1) Human beings sharing technical information with other human beings; (2) Human beings sharing technical information with artificial intelligences; (3) Artificial intelligences sharing technical information with human beings; and (4) Artificial intelligences sharing technical information with other artificial intelligences. The authors will share examples of humans and machines operating in each quadrant as well as analyzing the benefits and challenges that surface in the various relationships.
AI Ethics and (In)Authenticity: Preliminary Investigations of GPTs’ Affordances for Routine Production and Their Shortcomings for Symbolic Analytic Labor
Paul Hunter and A. Deptula
This presentation builds on findings from our forthcoming article (Deptula et al., 2024) on AI and authenticity. In that article, we detail how generative pre-trained transformer (GPT) large language models handle commonplace TPC concerns: genres, plain language, and grammatical/mechanical correctness. Our initial analyses reveal that ChatGPT 3.5, as of August 2023, can produce reasonable outlines for standard TPC genres (e.g., scientific articles, business proposals, and feasibility reports), transform sentences according to plain language conventions (evidenced by Flesch-Kincaid grade level scoring), and help writers ensure mechanical and grammatical correctness.
2:30 D1: Rhetorical prompt engineering in an era of AI expedience
Bryan Kopp, bkopp@uwlax.edu
Chris McCracken, cmccracken@uwlax.edu
Lindsay Steiner, lsteiner@uwlax.edu
Louise Zamparutti, lzamparutti@uwlax.edu
We designed a multi-week case study for technical writing students that incorporates AI into a complex risk-communication scenario. This case study introduces students to generative text technology through a scaffolded set of tasks in which they intervene in a classic professional and technical writing case study—the risk communication surrounding the Three Mile Island nuclear disaster. Students used ChatGPT to understand the case, to analyze and revise one of the memos implicated in the meltdown, to document and reflect on their revision strategies, and to develop a set of best practices for working with generative AI in technical communication.
4:00 E1: AI for Empathy? AI-Generated Personas and Teaching Design Thinking
Emma Kostopolus
I will discuss how I use AI-generated personas in my Technical Writing and Editing class, typically populated by students in Engineering Technologies and Interdisciplinary Studies, two very disparate contexts. I’ll work through the differences seen when students work with AI personas versus personas that they themselves generate, and report on how students appear to use the personas in crafting their midterm project, a recommendation report specifically intended for university stakeholders.
Artificial Interfaces, Artificial Ideologies: A Visual Rhetorical Analysis of ChatGPT
Eric York
This presentation reports on a visual rhetorical analysis of ChatGPT’s user interface (UI) and user experience (UX), including main interface elements and primary user flows, to reveal and trace the ideologies constructed and perpetuated in the product design. I explain how the UI and UX of ChatGPT relies on technical communication concepts of clarity and simplicity (Kostelnick and Roberts, 1998) to create and perpetuate a corrosive design philosophy, the most extreme example of extreme usability (Dilger, 2006) that undermines both literacy and design, and I discuss the pedagogical and programmatic implications of this finding, arguing for embodied rhetorics that can provide means of resistance and a both/and way to accommodate the rapid changes AI will usher in.
5:30 Keynote: Dr. Patrick Corbett–A Humanistic Perspective on AI Adoption Bridging the Global North/South Divide
Note: Vivian Garcia at Macmillan/Bedford St. Martin asked if I could share a link to their AI resources: