Outcomes

• Understand academic and scientific integrity conventions, including intext citations (APA 7)
• Learn the value and genre of Annotated Bibliography Conventions
• Learn to augment textual research with interviews
• Understand how to compose an evidence-based White Paper
• Understand how to give critical feedback

Deliverables

1. Annotated Bibliography + Peers’ Responses to Two Peers’ Annotations
2. Student Interviews and Analysis + Response to Two Peers’ Interviews
3. Self Evaluation Exercise – Guidelines for Evaluating and Revising Your White Paper with GenAI Feedback
4. White Paper
5. Metacognitive Report Addressing AI Usage (Upload this report in the same Canvas drop box as your White Paper.)
6. Responses to Two Peers’ White Papers

Note: The responses (responses to annotations, interviews, and White Papers) are due several days after those documents are submitted.

Introduction to the Assignment

This assignment builds directly on the first, where you examined how writing technologies have historically shaped human thought, consciousness, social structures, and power dynamics. Now, for this assignment, you will

1. engage in textual research: review survey research regarding student usage of GenAI and research and theory regarding whether educational institutions need to revise their academic integrity polices and conventions for citing sources.
2. engage in qualitative research: interview three current students at your school to understand how they use AI, how often, how they feel about it, and what policies they think the university should adopt.

This assignment asks you to treat writing about AI policy as a form of civic participation, where you not only synthesize what you’ve learned about the role of writing technologies in shaping thinking and society but also help shape institutional responses to new technological change. By engaging deeply with questions of authorship, attribution, academic integrity, and human agency, you will help the university make responsible, research-informed policy decisions about teaching and learning in the age of AI

Writing Prompt

Dr. Stacy Adams has asked you to write a white paper that addresses:

“What is the appropriate response for colleges and universities to the use of generative AI in writing: maintaining existing academic integrity standards, redefining them, or prohibiting AI use altogether?”

A White Paper is a genre of discourse. Researchers, companies and organizations write White Papers to inform readers about complex issues and to clarify their expertise on a topic. White Papers tend to be objective in tone and grounded in reviews of research and scholarship. White papers are often organized around a statement of the problem, a review of literature (or background), analysis, and conclusions.

Outcomes – Why Does This Assignment Matter?

Dr. Adams needs evidence-based guidance on whether to maintain, redefine, or prohibit GenAI. She wants to learn more about how other students are using GenAI for school and work assignments. She’s hoping that these interviews will provide a robust description of how your peers are working with GenAI and what they believe the university should do about its academic integrity policies. This work will inform the team’s effort to develop Navigating AI Disruption: A Guide for the University Community.

Rhetorical Situation

You are one of twelve students who been awarded a research stipend by your university to research GenAI. You are a member of a large research team that has been given a semester to research, design, and write “Navigating AI Disruption: A Guide for the University Community.” The aim of this “guide” is to define AI usage policies for the university community, and to justify those polices by rooted them in research, theory, and scholarship on GenAI.

By asking each of the twelve students who have been awarded a research stipend to study GenAI to interview students, Dr. Stacy Adams, your school’s AI Czar, aims to “take the pulse” of the student body. (In addition to your research team, she has also awarded twelve scholarships to members of the faculty). If these “thick descriptions” turn out to be powerful, Dr. Adams will publish these narratives on the website to further substantiate the AI policies defined in “Navigating AI Disruption: A Guide for the University Community.”

The Problem Space

Faculty opinions on AI use remain sharply divided, and universities have avoided school-wide AI policies:

• A recent analysis led by Hui Wang (2024) at the University of Arizona revealed that among the top 100 U.S. universities, over one-third had ambiguous or unsettled policies regarding AI use, while more than half deferred the decision to individual instructors. This delegation to faculty is understandable, in part because it aligns with principles of academic freedom. The American Association of University Professors (AAUP) describes academic freedom as encompassing a faculty member’s right to choose course materials, design assignments, determine instructional approaches, and evaluate student work.
• Lance Eaton (2025) has curated a list of AI policy statements from educators worldwide, highlighting deep disagreement over whether AI should be banned, permitted, or actively integrated. In disciplines such as STEM and business, some faculty allow AI use freely or for defined tasks like research and editing. By contrast, many in the humanities view AI-generated writing as unethical and incompatible with academic integrity standards, and prohibit its use entirely.

In The New Yorker, Hua Hsu (2025), a journalist and professor at Bard, reports

“Unable to keep pace, academic administrations largely stopped trying to control students’ use of artificial intelligence and adopted an attitude of hopeful resignation, encouraging teachers to explore the practical, pedagogical applications of A.I.”

This passivity on the part of U.S. institutions is problematic. In detailed interviews with NYU undergraduates, Hsu found that students are using GenAI in deeply problematic ways One student admits:

“Any type of writing in life, I use A.I. … I’m trying to do the least work possible, because this is a class I’m not hella fucking with” (Hsu, 2025).

Another describes prompting Claude to summarize readings he didn’t want to do:

“But, obviously, I wasn’t tryin’ to read that. … I said, ‘Turn it into concise bullet points’” (Hsu, 2025).

Asked if their use of GenAI constitutes plagiarisim, one student reports,

Of course. Are you fucking kidding me?” (Hsu, 2025).

Simplistically, professional associations such as the MLA and APA suggest students avoid plagariasm by citing their sources, just as they would do traditional primary and secondary sources. Unfortunately, however, the APA and MLA guidelines for citing AI-generated texts call for writers to cite every phrase that was generated by an AI tool. This expectation fails to account for how writers are using GenAI recursively and with multiple tools throughout the writing process. A single phrase — perhaps the gist that becomes the thesis — may be informed by a writer’s searching with Elicit, Consensus, and Perplexity. They may then upload papers they found during strategic searching to tools such ChatGPT or Perplexity and ask for summaries. They may then use LitMaps, Inciteful, and ResearchMaps to better understand canonical texts and gaps in the research. Next they may begin drafting on a blank page in gdocs, or, perhaps they will copy/paste the results of their strategic searching into an AI tool and ask it to write the first draft. Perhaps once they write a draft they will then run it by multiple AI tools to check for audience awareness, diction, voice, tone, and persona. Even more importantly, the APA and MLA citation guidelines fail to account for the extent of human labor or the percentage of AI involvement. Additionally, in the references, the MLA guidelines call for writers to list their prompts. The prompts a writer uses to generate a phrase may be pages long. When done conscientiously, a single phrase could have ten pages of prompts and citations in the references, noting the prompts they used over days or even weeks. This failure on the part of APA and MLA to account for how writers are composing with AI tools matters because it puts the careers of students and professionals at risk. To protect their reputations, authors need a viable way to clarify for their readers how they avoided plagiarism and academic dishonesty when using AI to compose texts.

These examples highlight the failure of current academic integrity guidelines to keep pace with the real-world practices of students and professional writers. In response to this conundrum. Moxley (2025a) suggests both academic and professional writers should include a metacognitive footnote with their documents that describes how they used AI to author their texts.

Eaton (2023) argues that traditional plagiarism policies—focused narrowly on unacknowledged copying—are inadequate in an era where generative AI fundamentally alters authorship, attribution, and cognitive labor. She calls for what she terms a postplagiarism approach:

“Moving to a postplagiarism approach does not mean abandoning academic integrity altogether. It means recognizing that integrity must be reconceptualized in light of changing technological and social contexts” (p. 5).

Eaton doesn’t offer a single policy blueprint. Instead, she argues that institutions must ask new questions:

1. When is AI use legitimate support for learning?
2. When does it become dishonest outsourcing of thinking?
3. How can attribution practices realistically and transparently represent AI’s role in composition?

One concrete way to operationalize this postplagiarism approach is to adopt metacognitive documentation practices. For example, Moxley has proposed that students and professionals include a metacognitive footnote in their documents describing how they used AI during composition. Such a note makes the role of AI transparent without demanding impossible, granular citation for every prompt or phrase. It asks writers to reflect on and disclose the extent and nature of their AI collaboration, promoting accountability, self-awareness, and ethical decision-making.

---

Guidelines and Evaluation

Guidelines for Annotated Bibliography

Required Readings

You need to complete the following readings to successfully complete this assignment:

1. Annotated Bibliography
2. Structured Revision – How to Revise Your Work

Purpose

This assignment strengthens your skills in summarizing, paraphrasing, and evaluating sources. It also helps you select and synthesize research that supports your White Paper and builds critical AI literacy.

Instructions

You will write annotations for the following six sources. All annotations must follow APA 7 citation format:

1. Digital Education Council. (2024). What students want: Key results from DEC Global AI Student Survey 2024. https://www.digitaleducationcouncil.com/post/what-students-want-key-results-from-dec-global-ai-student-survey-2024
2. Eaton, S. E. (2023). Postplagiarism: Transdisciplinary ethics and integrity in the age of artificial intelligence and neurotechnology. International Journal for Educational Integrity, 19, Article 23.
3. Eaton, L. (2025). Syllabi Policies for AI Generative Tools. (2025). Google Docs.
4. Freeman, J. (2025, February 25). Generative AI and the student experience: Survey findings from over 1,000 UK university students. Higher Education Policy Institute. https://www.hepi.ac.uk/wp-content/uploads/2025/02/HEPI-Kortext-Student-Generative-AI-Survey-2025.pdf
5. Hsu, H. (2025, June 30). What happens after A.I. destroys college writing? The New Yorker.
6. USF Guidance for Ethical Generative AI Usage: https://genai.usf.edu/at-usf/university-guidance

Instructions

1. APA 7 Citation. Start with a correctly formatted APA 7 citation.
2. Briefly describe the main argument, purpose, and key findings. Focus on the most important points. If helpful, include a direct quote or paraphrase with a page number to clarify a core claim.
3. C.R.A.A.P. Evaluation (50–70 words). Use the C.R.A.A.P. framework to evaluate the source’s:
   • Currency – Is it recent and up-to-date?
   • Relevance – How well does it relate to your research question?
   • Authority – Is the author credible? What are their affiliations?
   • Accuracy – Is the information supported by evidence? Are sources cited?
   • Purpose – Is the source objective, persuasive, informative, biased?
4. Connection to Research Question (50–70 words. Explain how the source informs your response to the central research question: “What is the appropriate response for colleges and universities to the use of generative AI in writing: maintaining existing academic integrity standards, redefining them, or prohibiting AI use altogether?” Be specific—how will this source help shape your position?
5. Note: Because these are scholarly articles, professional guidelines, and journalism as opposed to empirical studies, you do not need to address the research methods the articles authors’ used.

Each annotation (approx. 150–200 words) should include:

Submission Instructions

1. Post Your Annotated Bibliography to the class discussion forum by the deadline specified in Canvas.
2. Review and Respond to two classmates’ posts
   By the peer response deadline in Canvas, post thoughtful, constructive responses to at least two classmates’ annotations in the discussion forum.
3. Your responses should be at least 100 words each and address the criteria below. Your responses must be at least 100 words each and should offer helpful, respectful feedback on:
   • Summary clarity and accuracy
   • Effectiveness of CRAAP evaluation
   • Clarity of connection to the research question
   • Suggestions for including more direct evidence or quotations

Criteria for Evaluating Annotations

Criteria	Excellent (9–10 pts)	Satisfactory (6–8 pts)	Needs Work (0–5 pts)
1. CRAAP Evaluation
(Currency, Relevance, Authority, Accuracy, Purpose)	Thoroughly evaluates all five aspects. Includes page numbers with paraphrases when available. Suggests where a direct quote could help.	Covers most aspects clearly. Minor gaps or generalizations.	Few areas evaluated. Missing details or unclear reasoning.
2. Clarity
(Writing style, organization, tone)	Clear, concise, well-organized, and easy to follow.	Mostly clear with minor issues in flow or tone.	Disorganized, vague, or hard to follow.
3. Purpose and Findings
(What the source is about and its main points)	Accurately and clearly explains the source’s aim and key ideas.	Covers main points but lacks some depth or precision.	Incomplete, unclear, or misrepresents the source.
4. Connection to Research Question
(How the source helps answer the assignment’s main question)	Insightful, specific connection to the question about AI and academic integrity.	General or implied connection. Could be more specific.	No clear connection to the assignment question.
5. Course Theme Engagement
(Authorship, plagiarism, ethics, critical AI literacy)	Thoughtfully engages with one or more major course themes.	Mentions themes, but could go deeper.	No mention or unclear connection to course themes.

Total Score: ___ / 50

---

Peer Review Criteria for Annotations

Please do not use GenAi to respond to your peers’ annotations.

CRAAP Evaluation of the Source

• Does the annotation evaluate the Currency, Relevance, Authority, Accuracy, and Purpose of the source?
• Are any of these areas missing, vague, or underdeveloped? Would a direct quote or a paraphrase with a page number improve clarity or support?

Clarity

• Is the annotation clearly written and easy to follow?
• Are there any vague or confusing phrases that could be clarified?

Purpose and Key Findings

• Does the annotation accurately describe the source’s purpose, main arguments, or findings?
• Does it go beyond summary to capture what’s most significant about the source?

Connection to the Research Question

• Does the annotation explain how the source helps answer the research question about GenAI and academic integrity?
• Is the connection specific, meaningful, and analytically framed?

Critical AI Literacy / Thematic Engagement

• Does the annotation show how the source contributes to broader course themes—such as authorship, plagiarism, human agency, postplagiarism, cognitive offloading, or the ethics of GenAI?

Suggestions for Improvement

• Where could the annotation be more precise or better supported?
• Could a quote, paraphrase, or clearer analysis strengthen the annotation?
• Does the annotation clearly support the direction of the white paper?

Reminder: Your goal in peer feedback is not to grade your classmate but to help them improve. Provide respectful, specific, and constructive suggestions that help them revise their annotations effectively.

---

Guidelines for Student Interviews and Analysis

Having examined Ong’s and Bolter’s arguments that writing technologies transform human consciousness and culture (Bolter, 2001; Ong, 2002), and having reviewed recent debates over student use of generative AI and the conflicts in faculty and institutional policies (Eaton, 2023; Eaton, 2025; MLA-CCCC Joint Task Force, 2024), you are now ready to move beyond textual analysis into fieldwork.

Your task is to interview three university students to understand if and how they are using GenAI, and how they believe colleges and universities should respond to the question: What is the appropriate response to the use of generative AI in writing—maintaining existing academic integrity standards, redefining them, or prohibiting AI use altogether?

This is not a formal research study. Instead, it is a discovery exercise designed to surface lived experiences and perspectives on GenAI. Your goal is to listen, summarize, and reflect on what you hear. Later, these interviews will inform your final White Paper’s policy recommendations.

Core Interview Questions

You may ask follow-ups or add your own questions, but start here:

• How, if at all, do you use generative AI tools (ChatGPT, Claude, Gemini, Perplexity) in daily life?
• How do you use AI for academic work? For which tasks (brainstorming, outlining, editing)?
• How frequently do you use AI for schoolwork? (daily, weekly, occasionally, never)
• How do you feel about using AI for academic work—helpful, lazy, inevitable, ethical, dishonest?
• Do you think assignments should reflect your own thinking rather than AI’s? Why or why not?
• What policies do you wish professors or the university would adopt (USF, n.d.)?
• Do you think current definitions of authorship, plagiarism, and academic integrity need to change in the AI era (Eaton, 2023)?
• What’s a moment where GenAI helped you learn—or made you uneasy (Hsu, 2025)?
• Surveys suggest most students are using AI regularly (Digital Education Council, 2024; Freeman, 2025). Do your habits fit those patterns?

Visual Component

For each interviewee, include an anonymized AI-generated image that represents the person. Use Adobe Firefly, DALL·E, or another text-to-image tool to reflect the student’s field of study, disposition, or AI habits without revealing their identity. Avoid caricature or bias; aim for symbolic rather than literal representation.

Examples:

• A pre-med student who uses AI to quiz herself could be depicted as a student in scrubs holding a flashcard app.
• A student who feels AI is cheating could be shown as a conflicted figure walking a tightrope across a digital screen.

Ethics Statement

Before you begin, follow these principles:

• Obtain verbal consent from each participant.
• Make clear they will not be identified by name and that images will not resemble their real appearance.
• Emphasize that participation is voluntary and they may decline or skip questions.

These practices align with professional research ethics standards: respect, transparency, and non-identifiability.

Requirements

• Interview three USF students (classmates, friends, roommates, or peers from other majors—but not students in this class).
• For each interviewee, include:
  • Year in school (e.g., sophomore, graduate student)
  • Major or field of study
  • An anonymized, symbolic AI-generated image
  • A ~200-word narrative summary of their views (not bullet points or Q&A)
• Write an introduction that reflects on shared or contrasting themes across the three interviews.
• Organize your report into four sections with headers: Introduction, Student #1 [Pseudonym], Student #2 [Pseudonym], Student #3 [Pseudonym].

Length: 600–800 words total, plus visuals
Submission: Canvas Discussion Post by the posted deadline

Evaluation Rubric (50 Points Total)

Insightfulness of the Interviews (25 pts)

• Narratives offer depth, detail, and specificity.
• Students’ feelings and uses of GenAI are described with clarity.
• Direct quotes and examples help elevate the report.

Clarity and Coherence of the Write-Up (15 pts)

• Report is clearly organized, well-written, and easy to follow.
• Narratives are distinct but thematically connected.

Respectful and Ethical Representation (10 pts)

• Interviewees are anonymized and represented respectfully.
• AI-generated images avoid resemblance to actual participants and demonstrate ethical care.

---

Guidelines for Responding to Peers’ Interviews

After posting your Student Interviews and Analysis document to the discussion forum, you are required to respond to at least two classmates’ posts by the response deadline in Canvas.

Please do not use GenAi to respond to your peers’ annotations.

Purpose

These responses give you practice in analyzing how your peers interpret and represent student voices. By engaging with each other’s work, you will notice themes across interviews, reflect on writing choices, and contribute to a richer understanding of how students at USF are navigating the age of GenAI.

Expectations for Responses

Each response (about 150–200 words) should:

• Refer to specifics: Highlight a particular moment, idea, or direct quote from your peer’s interviews that stood out to you.
• Address clarity: Comment on how effectively your peer told the story of the student. Did the write-up read smoothly as a narrative, or did it feel more like a FAQ/Q&A list?
• Reflect and extend: Share what you took away from the interview(s) and pose a thoughtful question or observation that might help your peer deepen their analysis in the upcoming White Paper assignment.

Response Rubric (50 Points Total)

Criterion	Points	Description
Engagement	/20	Refers to specific ideas or quotes from the interview narratives.
Clarity	/15	Comments meaningfully on whether the peer’s write-up reads as a clear, coherent narrative (not as a FAQ/Q&A list).
Reflection	/15	Offers a takeaway, question, or observation that helps extend the conversation.

---

Self Evaluation – Guidelines for Evaluating and Revising Your White Paper

Purpose

This assignment teaches you how to use GenAI tools (e.g., ChatGPT, Claude, Gemini) as revision partners. You will practice structured revision at four levels—global, section, paragraph, and sentence—while keeping your own voice and purpose central.

Important: Before beginning, review the section immediately below titled Guidelines for White Paper — Generative AI, Ethics, and Academic Integrity Policy Recommendations and draft your White Paper. Your self-evaluation depends on having a complete draft to revise.

Instructions

1. Draft your White Paper using the guidelines in the section below. Note: You are free to use GenAI tools to write your White Paper.
2. Read Structured Revision – How to Revise Your Work
3. Choose one or two GenAI tools. Copy your draft into the system(s) and ask for revision feedback at four levels:
   • Global (argument, purpose, evidence, audience, overall organization)
   • Section (headings, proportions, section clarity, use of visuals)
   • Paragraph (unity, coherence, logic, transitions)
   • Sentence (clarity, style, grammar, punctuation, APA formatting)
4. Revise your draft critically. Do not accept suggestions wholesale—decide what strengthens your argument and what to reject.
5. Write a revision plan and reflection on how GenAI served as an editor for you. Please do not use GenAi to respond to write your revision plan/reflection.
6. Submit two files in Canvas:
   • File 1: Your revised White Paper draft (required but not graded).
   • File 2: A 250-word revision plan and reflection (graded).

Format for File 2 (250 words total)

• Global-Level Revisions: Identify two global-level changes GenAI suggested. Summarize the advice and explain how you revised.
• Section-Level Revisions: Describe one section-level suggestion and what you changed.
• Paragraph-Level Revisions: Choose one paragraph you revised. Summarize GenAI’s advice and describe your before/after changes.
• Sentence-Level Revisions: Choose one sentence you revised. Summarize GenAI’s advice and describe your before/after changes.
• Reflection (about 50 words): What did you learn about revision, writing, and directing GenAI feedback?

Response Rubric (50 Points Total)

Criterion	Points	Description
Global Revisions	/15	Identifies two global-level changes, explains revisions clearly.
Section Revisions	/10	Summarizes at least one section-level change and its effect.
Paragraph & Sentence Revisions	/15	Provides one example at each level with clear before/after explanation.
Reflection	/5	Offers insight about revision and GenAI feedback.
Clarity & Organization	/5	250 words, well-structured, easy to follow.

---

Guidelines for White Paper — Generative AI, Ethics, and Academic Integrity Policy Recommendations

Audience + Purpose

You are writing for Dr. Adams, the University’s AI Czar, and other university stakeholders working on the research initiative Navigating AI Disruption: A Guide for the University Community. To contribute meaningfully to this project, you need to show that you understand what writing is and how writing fosters thought, consciousness, and society.

In your earlier assignments, you read Walter Ong and Jay David Bolter to see how different writing technologies — from cuneiform tablets to typewriters — shape what and how humans think and communicate. Your goal was to understand the value of writing without AI so that you could better appreciate what might be lost if humanity relies solely on machines to do the writing — the loss of thought, creativity, and consciousness that writing has historically cultivated.

This White Paper asks you to extend that inquiry. Building on the scholarship you’ve annotated, the interviews you’ve conducted, and the presentation you delivered to your co-researchers, your task now is to synthesize your perspective on the question,

What is the appropriate response for colleges and universities to the use of generative AI in writing: maintaining existing academic integrity standards, redefining them, or prohibiting AI use altogether? 

What is a White Paper?

A White Paper is a professional document used in academia, government, and business to present research-based analysis and propose solutions to complex problems. Unlike essays, White Papers are designed to inform decision-makers and guide policy. They combine clear explanations, evidence from credible sources, and actionable recommendations. In this assignment, you will use the White Paper format to translate your research and interviews into practical guidance for university leaders grappling with AI and academic integrity.

Point of View

Write in first-person as a representative of the student research team established by Dr. Adams. While your point of view is first person, this doesn’t mean you should write causally and wander off into personal speculation. Instead, the document you produce should be professional: it should be grounded in the conversations (i.e., the articles and peer-reviewed research) that faculty, students and knowledge workers are having about whether to use GenAI and how to do so ethically. It’s fine for you to use the research we’ve already conducted as opposing to incorporating new sources.

Instructions for Writing Your White Paper

1. Use a professional writing style.
2. Title: White Paper — Generative AI, Ethics, and Academic Integrity Policy Recommendations.
3. Include your name and word count in the top left corner.
4. Length: 800–1000 words.
5. Citations: APA 7 in-text citations + References section.
6. In text- source engagement: include at least one direct quote from four of the provided resources: (Bolter, 2001), (Ong, 2002), (Eaton, 2023), (Eaton, 2025), (Digital Education Council, 2024), (Freeman, 2025), (Hsu, 2025), (USF Guidance).
7. Reference list must include the assigned sources (see list below) plus any others you cite.
8. You are encouraged to use multiple GenAI tools to write this document. That said, you must ensure that any quotations or paraphrases the GenAI provides are accurate. Misinformation will result in an F on the project. Also, you are expected not to cut and past whole sections of your report from GenAI tools but to be in charge of the writing word-by-word, section-by section. Be sure to address how you used GenAI tools in your metacognitive note and keep a record of your chat history for each tool used in case I have concerns about plagiarism.

Recommended Structure and Content

Purpose

In one sentence explain the purpose of the document and the audience it invokes (your co-researchers and Dr. Adams.)

Problem Statement / Context

In the introduction (a few paragraphs) you want to clarify the problem statement — the rise of GenAI and its impact on writing in school and workplace settings. You also want to introduce the research question your White Paper addresses. Then, as an organizational move to aid readability and persuasiveness, you briefly want to summarize your argument, your response to the research question. Here you don’t have the space to provide all of the evidence your audience (Dr. Adams and your co-researchers) need to be convinced of the quality of your argument. Instead, you are just outlining the arguments you’ll make later in the document.

Background and Literature Review

After the brief intro, provide a literature review to help the audience understand the complexity of the problem being addressed. Here is the space were you will synthesize what you’ve written before — the value of human writing, the emergence and quick takeup of GenAI by students and knowledge workers, and an analysis of ways this phenomenon undermines the ethical values of society (the theft of copyright and undermining of authorship), and challenges traditional notions of academic honestly. Here you may sidestep Sarah Eaton’s (2023) call for postplagiarism.

Note: Some writers may merge the problem statement with the literature review. That approach is also ok.

Analysis, Discussion, and Recommendations

This is your place to stand strong and make your argument based on what you’ve read, heard from the interviews, or experienced as a student or professional writer. Here you are free to express what you believe universities should do, whether that’s reject GenAI altogether, change its testing environment to allow classrooms to be air gapped, or embrace Sarah Eaton’s argument for redefining plagiarism.

Just be interesting and smart. Don’t belabor the obvious. Share the details of your reasoning so the other members of the research team can guage how sentiment is evolving over this problem.

References (Required Sources)

• Bolter, J. D. (2001). Writing space: Computers, hypertext, and the remediation of print (2nd ed.). Lawrence Erlbaum Associates.
• Digital Education Council. (2024). What students want: Key results from DEC Global AI Student Survey 2024. https://www.digitaleducationcouncil.com/post/what-students-want-key-results-from-dec-global-ai-student-survey-2024
• Eaton, S. E. (2023). Postplagiarism: Transdisciplinary ethics and integrity in the age of artificial intelligence and neurotechnology. International Journal for Educational Integrity, 19, Article 23.
• Eaton, L. (2025). Syllabi Policies for AI Generative Tools. Google Docs.
• Freeman, J. (2025, February 25). Generative AI and the student experience: Survey findings from over 1,000 UK university students. Higher Education Policy Institute. https://www.hepi.ac.uk/wp-content/uploads/2025/02/HEPI-Kortext-Student-Generative-AI-Survey-2025.pdf
• Hsu, H. (2025, June 30). What happens after A.I. destroys college writing? The New Yorker.
• Ong, W. J. (2002). Orality and literacy: The technologizing of the word (2nd ed.). Routledge. https://monoskop.org/images/d/db/Ong_Walter_J_Orality_and_Literacy_2nd_ed.pdf
• USF Guidance for Ethical Generative AI Usage: https://genai.usf.edu/at-usf/university-guidance

White Paper FAQs

How Can I Use Findings from the Student Interviews I Conducted?

When it comes to incorporating your learnings from the interviews, you have two choices: You may integrate what you’ve learned into the above problem definition. For instance in the problem statement when you are explaining how GenAI has disrupted conventions for copyright, quotation, or summary, you could include comments from students to make that point more cogently. This is the smoothest, most professional approach.

Or, and this is probably the easier move, you can just have a separate section when you talk about the learnings from your interviews. Top make this rhetorical move, you could have a signpost such as “Students at my university, USF, have experienced these problems first hand…” and then go on from there.

Evaluation Rubric (50 Points Total)

Criterion	Points	Description
Clarity and Coherence	/15	Writing is clear, concise, and logically organized; paragraphs flow smoothly; professional and persuasive tone throughout.
Problem Statement & Context	/10	Clearly defines the policy question, explains why it matters now (kairos), and situates student voices in Dr. Adams’s project.
Use of Sources & Literature Review	/10	Accurately integrates and cites all required sources with at least one direct quote from each; demonstrates understanding of debates around integrity and AI.
Interview Findings	/10	Effectively summarizes key themes from student interviews; integrates them into the policy discussion.
Recommendations	/5	States a clear, well-justified policy recommendation with specific, actionable strategies.

---

After submitting your own White Paper, you will respond to at least two classmates’ White Papers by the response deadline in Canvas.

---

Guidelines for Metacognitive Report Addressing AI Usage

Please do not use GenAI to respond to write your metacognitive report. Let your peers hear your authentic voice. .

The purpose of your metacognitive report is to describe how you used GenAI to compose your White Paper and its supporting research (annotated bibliography, interviews, design). Your audience for this report is your instructor and potentially other students in the class.

Instructions

Review the guidelines for writing a Metacognitive Report: Metacognitive Report – AI Writing Ethics: Balancing Agency, Voice & Disclosure. Critically reflect on the possible ways you used GenAI to compose the deliverables associated with this major project:

• Thought Partner – brainstorming, counterarguments, refining claims
• Research Assistant – finding, summarizing, and cross-checking sources
• Composing Assistant – supporting invention, drafting, revising, rereading
• Citation Assistant – formatting and checking references
• Editorial Assistant – improving clarity, coherence, and flow
• Designer – shaping tables, figures, or layouts
• Publishing Assistant – adapting work for new audiences or media
• Teaching Assistant – clarifying complex concepts or modeling skills

Prepare a metacognitive report that is at least 250 words long, following these guidelines:

• Title the report, Metacognitive Report – White Paper: Academic Integrity in the Age of AI.
  • Provide a link to the url for each Chat Log you conducted
  • URL or Archive (link to the exported transcript or note where it is saved)
  • Beneath the title, left justified, record the number of words in the report.
• At the top of your document,
  • Overview – Identify the tools you used and why. (2–3 sentences)
  • Insert one table for each GenAI tool you used.
    • Each table should have the following columns:
      • Step in the Writing Process (Prewriting, Drafting, Revising, Designing, Annotating, Interview Support, etc.)
      • Number of Chats / Sessions (be precise; agency often shows in how many iterations you chose to pursue)
      • Primary Purpose(s) (Brainstorming, outlining, citation help, interview prep, design drafting, etc.)
      • Notes on Use (2–3 sentences) – Describe briefly what you did with the tool, how many iterations it took to get something usable, and how you integrated/revised it.

Narrative Structure

Beneath the table(s), write a narrative that explains not just what you used but how you iterated. More specifically, use this organizational structure:

1. Overview – Name the tools you used and why you chose them. (2–3 sentences)
2. Iterations as Critical Moments or Lessons – Exemplify 2–3 key ways influenced your thinking, writing, and composing process. Or talk about 2 or three lessons you learned from engaging with GenAI, such as how to dialog with it or identify misinformation or hallucinations. Give Examples of ongoing chats:
   • what the AI gave you first,
   • what you rejected or revised in later iterations,
   • and why those changes mattered to your accuracy, ethics, or voice. (1–2 paragraphs each)
3. Reflection – Explain how your agency depended on iterating. How did multiple rounds of questioning, revision, or redirection keep you in charge? What risks did you notice (fabricated references, misleading summaries, style drift), and how did iteration help you detect/correct them? (1 paragraph)
4. Takeaway – What did you learn about iteration as a habit of mind in research-based writing? What practices will you carry forward into future projects? (1 paragraph)
5. Submission

Upload to Canvas by due date. (Upload this assignment in the same Canvas drop box as your White Paper.)

---

Metacognitive Report Rubric – White Paper

Documentation of AI Use (0–15 points)
You must include one table for each GenAI tool you used. Each table should contain the following columns:
– Step in the Writing Process (e.g., Prewriting, Drafting, Revising, Designing, Annotating, Interview Support)
– Number of Chats / Sessions (be precise; agency shows in how many iterations you pursued)
– Primary Purpose(s) (Brainstorming, outlining, citation help, interview prep, design drafting, etc.)
– Notes on Use (2–3 sentences: what you did with the tool, how many iterations it took to get something usable, how you revised/used it)
– Chat Log URL or Archive (link to transcript or note where saved)
Reports missing these tables or incomplete columns will lose points.

Iteration and Critical Reflection (0–20 points)
Your narrative must follow this structure:

1. Overview – Name the tools you used and why (2–3 sentences).
2. Iterations as Critical Moments – Select at least 2–3 points in your process (e.g., revising a White Paper section, developing an annotated bibliography entry, preparing interview questions, designing a figure). For each:
   – Describe what AI gave you first.
   – Explain what you revised or rejected.
   – Explain why those changes mattered (accuracy, ethics, voice).
3. Reflection – Discuss how iteration kept you in charge. What risks did you notice (fabricated references, misleading summaries, style drift) and how did you detect/correct them?
4. Takeaway – What did you learn about iteration as a habit of mind? What practices will you carry into future projects?

Clarity, Structure, and Authentic Voice (0–15 points)
Your report must:
– Be titled: Metacognitive Report – White Paper: Academic Integrity in the Age of AI
– Record the number of words beneath the title (left justified)
– Be at least 250 words long
– Follow the narrative structure above (Overview, Iterations, Reflection, Takeaway)
– Be coherent, easy to follow, and professional in tone
– Demonstrate your authentic human voice. If prose appears AI-generated (flawless but generic, lacking individuality), points may be reduced significantly, including a score of 0. Students receiving a 0 must schedule a meeting with the instructor to verify authorship.
Metacognitive Report – Quick Grading Checklist (50 points)

Basic Requirements
☐ Title correct: Metacognitive Report – White Paper: Academic Integrity in the Age of AI
☐ Word count recorded beneath title (left justified)
☐ Minimum 250 words

Tables (0–15 pts)
☐ One table per GenAI tool used
☐ Columns complete: Step | # Chats | Purpose(s) | Notes (2–3 sentences) | Chat Log/Archive
☐ Iterations (# of chats/sessions) recorded with precision

Narrative (0–20 pts)
☐ Overview: names tools + why chosen
☐ At least 2–3 critical moments described (first output, revisions/rejections, why changes mattered)
☐ Reflection: how iteration maintained agency + risks detected/corrected
☐ Takeaway: what was learned about iteration as a habit of mind

Clarity & Authentic Voice (0–15 pts)
☐ Structure followed (Overview, Iterations, Reflection, Takeaway)
☐ Clear, coherent, professional tone
☐ Authentic human voice (not AI-generated; if questionable → 0 pts + follow-up meeting)

Example Metacognitive Report

Metacognitive Report – White Paper: Academic Integrity in the Age of AI
Word Count: 356

Step in Writing Process	Tool Name	Number of Chats	Primary Purpose(s)	Notes on Use
Prewriting (Interview Prep + Annotated Bib)	ChatGPT	3	Brainstorming interview questions, checking APA style	I drafted questions myself, then asked AI for alternatives. It suggested overly formal phrasing, so I rewrote them into conversational questions. For APA, I cross-checked against Purdue OWL to correct AI’s formatting errors.
Drafting (Outline + Paragraph Starters)	ChatGPT	4	Outlining, sentence openers	AI produced a generic outline. I rejected most of it but kept the order of sections. I also asked for paragraph starters, but rewrote them in my own words.
Revising (Student Narratives + Analysis)	ChatGPT	5	Tone and concision	AI fabricated material for student interviews, so I replaced it with my own authentic notes. Its feedback on transitions was helpful, but I cut repetition manually.
Proofreading	Grammarly	1	Grammar/punctuation	Grammarly caught missing commas and extra spaces. I ignored its style suggestions that made the writing too robotic.
Citation Help	ZoteroBib + ChatGPT	2	APA references	ChatGPT gave me draft citations, but I corrected them with ZoteroBib and verified against the original texts.

Narrative
I used ChatGPT, Grammarly, and ZoteroBib for this assignment. My strategy was to draft in my own words first, then use AI for feedback and fine-tuning. Iteration was essential: for example, AI’s first draft of a conclusion was repetitive, so I rewrote it into a more concise synthesis. When AI gave me summaries of readings, they were too formal, so I rewrote them until they sounded like me. I also noticed AI sometimes hallucinated citations; cross-checking forced me to verify accuracy.

Through this process, I realized that iteration is what keeps me in charge. Each round forced me to decide what to keep, what to cut, and what to rewrite. AI was most useful for catching small issues or showing me organizational possibilities, but the substance of the argument was mine. Going forward, I will continue drafting independently, then use AI in small, deliberate steps as a support—not as a shortcut.

---

Guidelines for Responding to Peers’ White Papers

Please do not use GenAI to respond to your peers’ White Papers. Let your peers hear your authentic voice.

Purpose

The goal of this exercise is to learn from one another. By reading your peers’ White Papers, you will see different approaches to argument, evidence, and recommendations. By offering feedback, you will practice identifying what works well and what could be improved in professional policy writing.

Expectations for Responses

Each response (150–200 words) should:

• Quote specifically: Include at least one direct quote from your peer’s White Paper (a sentence or short passage). Explain why it stood out to you.
• Acknowledge strengths: Highlight one idea, strategy, or argument that was particularly effective or persuasive.
• Suggest improvements: Identify two areas where your peer could improve (e.g., clarity, organization, source integration, recommendation strength). Be specific and constructive.
• Write clearly: Your response should be organized, respectful, and easy to follow.

Response Rubric (50 Points Total)

Criterion	Points	Description
Clarity and Professionalism	/15	Response is clearly written, organized, respectful, and easy to follow.
Specific Engagement	/15	Includes at least one direct quote and discusses it thoughtfully.
Constructive Feedback	/20	Offers at least two specific, constructive suggestions for improvement.