What key terms should I know within artificial intelligence (AI) discourse?

Artificial Intelligence (AI)

Artificial Intelligence, often referred to as AI, encompasses computational systems created to imitate human behaviors and cognitive processes. In essence, computer scientists strive to design AI that can augment or replicate specific human cognitive functions, such as problem solving, experiential learning, pattern recognition, and decision making.

Generative AI (GenAI)

Generative AI is a branch of artificial intelligence trained on vast datasets (text, images, audio, code, etc.) in order to generate contextually relevant outputs. ChatGPT is a well-known formation of GenAI designed to generate human-like language in response to a prompt; in fact, the “G” in ChatGPT stands for “generative” to reflect this nature. However, GenAI covers a great variety of generators, such as image generators like Midjourney and DALL-E 2, or voice generators like Eleven Labs. Amid these various formations, ChatGPT belongs to a specific subcategory of GenAI called Large Language Models.

Large Language Models (LLMs)

Large Language Models are a specific subset of GenAI designed to process and generate human language. These models, trained on extensive textual data, can understand, generate, and manipulate text in ways that resemble human communication. LLMs include popular chatbots like OpenAI’s ChatGPT, Microsoft’s Bing, Google’s Bard, and more.

What should I know about composing a research paper before I begin this tutorial?

A Brief Overview

In many ways, pursuing a college degree is synonymous with doing research. Indeed, writing a research paper mirrors the practices of intellectual exploration in places like the Library of Alexandria of ancient Egypt. While the modern research paper looks much different than its ancient predecessors, its value remains the same: Research is a means for finding clarity amid a world of complexity.

With the latest GenAI, such as ChatGPT, students and researchers alike now have a powerful tool at their disposal to enrich the research process. As an illustration, this tutorial will explore three specific strategies where collaborating with ChatGPT can augment traditional research methods. For further information on research papers in general, see table 1.

Table 1

Open-Access Resources Related to Composing a Research Paper

What are three ways ChatGPT can support research paper composition?

Surveying the Ongoing Discourse of Research on a Given Topic

No research paper is composed in a vacuum; instead, scholarly work is built upon existing knowledge, theories, and previous research findings. As such, the research process has often been likened to joining an “ongoing conversation,” as Kenneth Burke famously illustrates with his parlor metaphor.^[4] This illustration can help you think critically about how your research fits into the ongoing discourse on a topic. How will you build upon what has already been said? Do you agree or disagree with others’ viewpoints? What new perspectives can you add to the dialogue? Such questions can help you lean into the scholarly exchange of ideas and position your research to be a more meaningful contribution to the collective understanding of a subject.

When researching a topic, understanding the academic conversation surrounding it can be challenging, especially for popular topics like climate change or gun control. This is where the design of tools like ChatGPT can be uniquely helpful. As an LLM, ChatGPT has been trained on vast arrays of internet text, making it well-versed in the ongoing discourse of research across various subjects. Consequently, ChatGPT can serve as a valuable entry point for surveying the most relevant language related to a research question.

For an example, see Strategy in Action #1, in which a user puts in their research question on internet privacy and ChatGPT responds with an overview of the different perspectives involved.

Strategy in Action #1

View the following example prompt and response with ChatGPT focused on surveying the ongoing discourse of research on a given topic.

If you’d like to interact directly with ChatGPT in the above conversation, access the original chat through this link^[5] and click the ‘Continue the conversation’ button in the opened dialogue window.

Check out table 2 for additional tips and suggestions related to surveying the ongoing discourse of research on a given topic.

Table 2

Tips and Suggestions: Know the Limitations of ChatGPT’s Training

Drafting with Different Reasoning Strategies

Most research paper assignments tend to feature larger page requirements to accommodate an in-depth exploration of a topic. However, the longer length can also present the challenge of sustaining a well-developed argument throughout the paper. To tackle this challenge, it is important to think critically about the most effective and persuasive way to approach a topic.

For this purpose, writers and speakers employ various reasoning strategies to build and structure an argument, such as analogy, cause-and-effect, classification and division, compare and contrast, problem-and-solution, definition, and more. Consider, for instance, how these various reasoning strategies can generate a number of ways to approach the topic of mental health, as demonstrated in Table 3:

Table 3

Various Reasoning Strategies for Approaching the Topic of Mental Health

If you’re feeling stuck with how any of these reasoning strategies might apply to your research, ChatGPT can be a linguistic lifeline. As an LLM, the chatbot has been extensively trained in each one of these reasoning strategies, enabling it to model how these various modes might work with your topic. See Strategy in Action #2 for an example, in which a user explores several approaches for the topic of eating disorders. Collaborating with ChatGPT in this way can help you determine what to include in your writing as well as which strategy (or mix of strategies) is the best for organizing your thinking.

Strategy in Action #2

View the following example prompt and response with ChatGPT focused on drafting with different reasoning strategies.

If you’d like to interact directly with ChatGPT in the above conversation, access the original chat through this link^[8] and click the ‘Continue the conversation’ button in the opened dialogue window.

Integrating Sources and Quotes

In any research paper, the integration of sources is not just an assignment requirement to check off—it adds essential depth and credibility to your work. When you integrate sources into your paper, you are both showcasing the close reading of the research you’ve done and inviting yourself into the academic conversation. As such, the art of smoothly embedding quotes within the flow of your writing should be a key focus because it enables readers to follow your ideas seamlessly and grasp the relevance of the quotations instantly. However, this task can present a number of challenges, such as the struggle to balance your voice with the source’s voice, the fear of misinterpretation, and the need for proper contextual understanding.

To improve the integration of quotes, students can seek personalized feedback from ChatGPT, which has been extensively trained in various quoting strategies within its design as an LLM. See Strategy in Action #3 for an example, where ChatGPT generates guidance for integrating a quote from The Odyssey into the user’s analysis. ChatGPT models various quoting strategies, such as introducing the context of Odysseus’s encounter with the Cyclops, using signal phrases like “declaring,” and explaining the significance of Odysseus’s taunt. This practical example showcases how ChatGPT can help you not only create well-embedded sources, but also clearly communicate your meaning.

Strategy in Action #3

View the following example prompt and response with ChatGPT focused on integrating sources and quotes.

If you’d like to interact directly with ChatGPT in the above conversation, access the original chat through this link^[9] and click the ‘Continue the conversation’ button in the opened dialogue window.

Check out table 4 for additional tips and suggestions related to integrating sources and quotes

Table 4

Tips and Suggestions: Avoid Sharing Sensitive or Confidential Information

What’s a pitfall to avoid when collaborating with ChatGPT on a research paper?

Overreliance on ChatGPT Can Cost Originality and Time

The research paper assignment is often the longest essay you will write for a rhetoric and composition course, which makes it tempting to rely heavily on a tool like ChatGPT to slog through to the finish line. This temptation is not your fault—the brain is hardwired to prefer the path of least resistance. However, you can practice self-discipline through the knowledge that there is a price for overreliance, particularly in regard to originality and time.

Consider first the basic purpose of doing research: to make original discoveries or insights amid the complexities of the world. Overusing ChatGPT undermines this purpose. You run the risk of just echoing its output, which lacks originality since it relies on existing data patterns. It can’t make original discoveries or insights; that’s your role.

Additionally, consider how ChatGPT can affect time management. It is easy to spend a significant amount of time interacting with the chatbot without making significant progress on an assignment. Imagine, for example, a student who is researching climate change but gets caught up exploring related topics (e.g. deforestation) through their interactions with ChatGPT. While such engagement is interesting, this student could end up not having enough time to finish their work. In general, part of learning how to write a research paper is the time management the assignment requires. Research papers are too complex and too lengthy of a writing assignment to put off to the last minute. As such, relying too heavily on ChatGPT can impede finishing a research paper in a timely manner.

Learning Outcomes for ENGL 1302: How does this tutorial apply to state standards?

This tutorial is designed to support your success in ENGL 1302 (Composition II) by aligning with the student learning outcomes established by the Texas Higher Education Coordinating Board. As highlighted in Table 5 below, this tutorial directly addresses three key standards. By aligning with these specific learning outcomes, this tutorial not only provides you with skills and knowledge that transfer across diverse learning environments but also gives your education value outside your institution.

Table 5

Applicable State Learning Outcomes