In this section, you will learn about the importance of ethical considerations and implications of Generative Artificial Intelligence (GenAI), particularly Large Language Models (LLMs) like ChatGPT. This section highlights that LLMs are not inherently good or bad. Instead, the importance of user engagement in ethical practices is emphasized to ensure responsible use of these tools.

Ethical considerations for educators include attention to student privacy, expectations, and consequences—all of which should clearly be defined in syllabus statements, classroom policies, or institutional statements. Meanwhile, ethical implications exist involving varying ethical standards for how people approach LLMs differently, how human and machine bias influence GenAI, and how style guides differ on citing information garnered from ChatGPT.

After reading this section, you should be able to articulate your own ethical queries and concerns related to LLMs, such as ChatGPT, both as a general user and an educator.

Author: C. Anneke Snyder
Contributors: Gwendolyn Inocencio, Mary Landry, Jonahs Kneitly
Designers: Irene AI, Sweta Kailani
Supervisors: Terri Pantuso, Sarah LeMire

This assignment asks students to take bibliographic data and generate a properly formatted APA citation. After completing questions #1-8, they are then asked to create 3 properly formatted in-text citations in APA style. Finally, they are asked to take the first 8 citations and turn them into a properly formatted reference sheet, attached to the end of the worksheet. Depending on skill level, the instructor may choose to allow them to use an aid (like Purdue Owl) to construct the citations or do them from memory. This assignment is best used to assess students’ understanding of APA and provide them with low-stakes practice of these formatting skills. 

Grammar Bowl is a game designed to review important grammar rules with students in a group setting. The game can be played individually; however, small groups of 2-3 students collaborating often creates a competitive, albeit friendly, atmosphere that encourages students to think and work quickly.

Technical writing courses introduce you to some of the most important aspects of writing in the worlds of science, technology, and business—in other words, the kind of writing that scientists, nurses, doctors, computer specialists, government officials, engineers, and other professionals do as a part of their regular work. The skills learned in technical writing courses can be useful in other fields as well, including education and social sciences.

Technical writing courses introduce you to some of the most important aspects of writing in the worlds of science, technology, and business—in other words, the kind of writing that scientists, nurses, doctors, computer specialists, government officials, engineers, and other professionals do as a part of their regular work. The skills learned in technical writing courses can be useful in other fields as well, including education and social sciences.

In this section, we will examine how generative AI (GenAI) tools may assist with academic reading and research. Examples of content generated by ChatGPT will show how GenAI may be incorporated into a classroom setting. Each section offers suggestions for use and various strategies that could be incorporated for those who wish to allow the use of these tools for assignments. Included throughout are suggestions on how to promote students’ ethical and effective use of these tools and to possibly limit their use if desired. By the end of this section, you should be able to use GenAI to support reading practices.

Author: Jonahs Kneitly
Contributors: Gwendolyn Inocencio, Mary Landry, C. Anneke Snyder
Designers: Irene AI, Sweta Kailani
Supervisors: Terri Pantuso, Sarah LeMire

In this section, illustrative examples from ChatGPT show how to incorporate Large Language Models (LLMs) into the writing process while considering ethical concerns associated with such tools, namely avoiding plagiarism or exploitation of AI-generated content. The advent of public access to LLMs means they are now a critically important aspect of digital information literacy. As such, this technology must be addressed in the composition classroom with guided instruction. We recommend a strategy that models application of a modified version of stasis theory to all LLM-generated content.

After reading this section you should be prepared to teach stasis theory as a strategy for continual interrogation that helps rhetors discern whether generative-AI content exhibits appropriate depth, scope, and quality, along with the appropriate next steps in argumentation, writing, or research.

Author: Gwendolyn Inocencio
Contributors: C. Anneke Snyder, Mary Landry, Jonahs Kneitly
Designers: Irene AI, Shweta Kailani
Supervisors: Terri Pantuso, Sarah LeMire

From the OER Commons Description: Welcome to composition and rhetoric! While most of you are taking this course because it is required, we hope that all of you will leave with more confidence in your reading, writing, researching, and speaking abilities as these are all elements of freshman composition. Many times, these elements are presented in excellent textbooks written by top scholars. While the collaborators of this particular textbook respect and value those textbooks available from publishers, we have been concerned with disenfranchising students who do not have the resources to purchase textbooks. Therefore, we decided to put together this Open Educational Resource (OER) explicitly for use in freshman composition courses at Texas A&M University. Thanks to a generous grant from Dean David Carlson of the Texas A&M University Libraries, this project became a reality. It is a collaborative endeavor undertaken by faculty in the libraries and English Department as part of the Provost’s Student Success Initiatives at Texas A&M and continues to be a work in progress. Combined, Dr. Terri Pantuso, Dr. Kathy Anders, and Prof. Sarah LeMire have over 30 years of experience in writing and research instruction. Our goal is for students to leave this course as critical thinkers, polished writers, and informed citizens who can engage in civil public discourse.

Welcome to composition and rhetoric! While most of you are taking this course because it is required, we hope that all of you will leave with more confidence in your reading, writing, researching, and speaking abilities as these are all elements of freshman composition. Many times, these elements are presented in excellent textbooks written by top scholars. While the collaborators of this particular textbook respect and value those textbooks available from publishers, we have been concerned with disenfranchising students who do not have the resources to purchase textbooks. Therefore, we decided to put together this Open Educational Resource (OER) explicitly for use in freshman composition courses at Texas A&M University. Thanks to a generous grant from Dean David Carlson of the Texas A&M University Libraries, this project became a reality. It is a collaborative endeavor undertaken by faculty in the libraries and English Department as part of the Provost’s Student Success Initiatives at Texas A&M and continues to be a work in progress. Combined, Dr. Terri Pantuso, Dr. Kathy Anders, and Prof. Sarah LeMire have over 30 years of experience in writing and research instruction. Our goal is for students to leave this course as critical thinkers, polished writers, and informed citizens who can engage in civil public discourse. Gig ‘em, Ags!

This section is designed to build confidence about what Generative Artificial Intelligence (GenAI) means for the future of education by closely studying the operations, limitations, and theoretical value of a Large Language Model (LLM) like ChatGPT. To this end, this section seeks to explain what language modeling is and how this process contributes to an LLM’s tendency to generate inaccurate information. Additionally, this section considers how the design of an LLM—specifically, the collective knowledge it is trained upon—can contribute to the perpetuation of biases. Lastly, this section encourages critical thinking about the value of an LLM from a theoretical standpoint regarding the writing process and collaborative learning. By the end of this section, you should be able to articulate how an LLM like ChatGPT operates, as well as the value and limitations of this design within the evolution of learning.

Author: Mary Landry
Contributors: Gwendolyn Inocencio, C. Anneke Snyder, Jonahs Kneitly
Designers: Irene AI, Shweta Kailani
Supervisors: Terri Pantuso, Sarah LeMire

In this section, you will gain insights about privacy and confidentiality concerns related to a form of Generative Artificial Intelligence (GenAI) known as Large Language Models (LLMs) and, specifically, OpenAI’s policies about ChatGPT.

The full extent of privacy and confidentiality risks in relation to ChatGPT, which relies on collective intelligence for information gathering and dissemination, has not been fully realized. Users should be mindful of OpenAI’s terms of use, particularly as those terms are subject to change. Though OpenAI claims to not share private user information, the language around such statements is vague and contradictory, and there is a strong possibility that personal information may be monitored by human proctors. Moreover, educators who are bound to the legal obligations outlined in FERPA should be particularly concerned about how student privacy could be potentially violated by using ChatGPT and other GenAI technologies.

After reading this section, you should be able to articulate and discuss OpenAI’s significant terms of use and privacy policy, consider the potential privacy and intellectual property violations contained within the collective intelligence paradigm, and communicate your own concerns about privacy and confidentiality in relation to GenAI technologies.

Author: C. Anneke Snyder
Contributors: Gwendolyn Inocencio, Mary Landry, Jonahs Kneitly
Designers: Irene AI, Sweta Kailani
Supervisors: Terri Pantuso, Sarah LeMire