9:00 Keynote: Dr. Stuart Selber
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