Understanding AI Academic Misconduct Under the CCCC Umbrella: A Functional Analysis

Academic Misconduct and AI Under the CCCC Umbrella

The Conference on College Composition and Communication (CCCC) approaches academic misconduct with considerable nuance, acknowledging the complex factors that influence writing practices in academic settings. The present analysis examines how the CCCC's positions on plagiarism and academic integrity move beyond simplistic punitive frameworks to encompass developmental, cultural, and pedagogical considerations, while providing educators with more effective approaches to fostering authentic learning and ethical writing practices. It also draws lines between the Common Core State Standards and the Task Force recommendations. As my long-time colleague and friend Janet Hecsh documented in her dissertation research, reform is perhaps best approached by repurposing structures already in existence than by trying to throw them away and start from scratch.

The significance of what CCCC has managed to do over the past few years us a beacon to help us see a path forward from this current polarization regarding AI and writing instruction. What I find remarkable are the plethora of references to work dating back to 2001 with insights on academic integrity which seem prescient somehow. I remember reading or hearing voicings of these and similar ideas, but they didn’t seem nearly as compelling as they do today. AI has opened the aperture and forced writing teachers to rethink settled ideas.

I especially appreciate how the CCCC drew collectively from tradition to prepare a substrate from the past for the field to stand on in the present. English teachers have long known the nuances of cheating; it just hasn’t seemed so urgent to protect students from failing themselves. I offer this analysis completed over the past few weeks and ask for your charity in reading it because it deserves several months of careful study. In order to keep it short enough for a blog post, I held back some verbiage regarding specific assignments which I would have loved to include, but I provide URLs to the assignments available online. If you don’t have time to check them out, copy and paste them for later leisure viewing.

Defining the Problem with Precision

As stated in the CCCC's position statement on plagiarism: "Plagiarism occurs when a writer deliberately uses someone else's language, ideas, or other original material without acknowledging its source" (CCCC, 2021, para. 2). The statement also emphasizes that "responsibilities for defining and addressing plagiarism are complex" and that "the conditions under which students write are different from those of scholars and professionals" (CCCC, 2021, para. 4). This distinction is crucial. It recognizes the sociocultural nature of writing development and gives teachers a caution not to use standards that apply to them to the students.

The CCCC explicitly acknowledges that "there is a difference between fraud and the misuse of sources" (CCCC, 2021, para. 6). For example, I hope I haven’t misused or mischaracterized anybody’s work in this essay. I did not set out to deceive. This distinction helps instructors separate intentional academic dishonesty from errors in citation or attribution that stem from inexperience. Where citations and AI material merge, there is no settled protocol, but it remains important to teach students to report long passages of text in their writing which was generated by AI. As the position statement elaborates, "Students engaging in fraud are deliberately passing off someone else's work as their own; students misusing sources are often engaging in a learning process and making mistakes" (CCCC, 2021, para. 7).

Cultural and Educational Contexts

The CCCC recognizes that "students who come to us from other cultures may have learned research and writing practices very different from those we expect" (CCCC, 2021, para. 9). This cultural dimension is crucial for understanding some instances of apparent misconduct.

The organization notes that "writing from sources is a complex task that requires understanding of the sources and good reading comprehension" - skills that develop gradually and unevenly across different educational contexts (CCCC, 2021, para. 11). Cynthia Selfe and Gail Hawisher's research on global literacy practices demonstrates that "conceptions of intellectual property and textual ownership vary significantly across cultures," making it problematic to apply a single standard without consideration of students' educational backgrounds (Selfe & Hawisher, 2007, p. 188). Their work suggests that "what appears to be plagiarism may in fact be culturally-specific writing practices that value textual reproduction as a sign of respect" (Selfe & Hawisher, 2007, p. 192).

Similarly, Alastair Pennycook's influential study "Borrowing Others' Words: Text, Ownership, Memory, and Plagiarism" argues that "Western notions of textual ownership are culturally constructed rather than universal," highlighting how "memorization and reproduction of texts are valued practices in many educational systems globally" (Pennycook, 1996, p. 214).

Pedagogical Approaches Over Punishment

The organization advocates for "teaching about plagiarism and appropriate textual practices in courses rather than focusing on punishment," positioning academic integrity as primarily pedagogical rather than disciplinary (CCCC, 2021, para. 13). This insight intersects with teacher awareness of the differences between children learning to write and adults wanting to publish or perish. As composition scholar Lise Buranen notes, "The goal is not to catch plagiarists but to teach students how to work with sources effectively and to help them understand the conventions of academic writing" (Buranen, 2009, p. 72).

The CCCC recommends that "faculty design contexts and assignments for writing that help students understand how to use sources appropriately," suggesting that "well-designed assignments can reduce the likelihood of plagiarism" (CCCC, 2021, para. 14). This approach shifts responsibility partially to instructors, acknowledging that pedagogical design plays a significant role in fostering academic integrity. Requiring students to know their sources intimately before interrogating them using a bot might increase the depths of un derstandingf students bring to a text.

In her influential work "Pedagogy, Not Policing," Rebecca Moore Howard argues that "punitive approaches to plagiarism enforcement often undermine the educational mission of the university" (Howard, 2001, p. 55). She observes that "fear-based approaches to plagiarism prevention create anxious writers rather than confident ones" and suggests that "writing instruction should focus on developing students' rhetorical flexibility rather than merely avoiding transgression" (Howard, 2001, p. 58). Rhetorical flexibility covers a lot of ground, but it suggests that students ought to be taught to understand the appropriate use of offloading in particular rhetorical circumstances, i.e., the difference between a boilerplate announcement and a biographical sketch.

Developmental Perspectives on Source Use

Rebecca Moore Howard's concept of "patchwriting" offers important insight, describing it as "copying from a source text and then deleting some words, altering grammatical structures, or plugging in one synonym for another,” a developmental stage rather than an ethical violation (Howard, 1999, p. 18). Howard argues that "all writers build on the work of others," and learning appropriate boundaries is part of writing development (Howard, 1999, p. 22).

Building on this work, Sandra Jamieson's longitudinal studies of student writing have found that "novice writers often struggle to synthesize multiple sources effectively" and that "paraphrasing difficulties often stem from comprehension challenges rather than dishonest intent" (Jamieson, 2016, p. 505). Her research suggests that "students' ability to work with sources develops over time and with practice," reinforcing the developmental model (Jamieson, 2016, p. 508). Moreover, at this juncture teachers could apply content-area reading strategies activating prior knowledge before entering a text, annotating systematically to distinguish among direct quotes, paraphrasing, and a synthetic or interlinked idea from the student’s own head. These nortes might then be validated and elaborated through using AI.

According to Kathleen Blake Yancey, "Students need multiple opportunities to practice working with sources, receiving feedback, and revising their work" (Yancey, 2008, p. 63). She argues that "citation is not merely a technical skill but a rhetorical practice that requires understanding of how knowledge is constructed in different disciplines" (Yancey, 2008, p. 66). This insistence on AI us being embedded in rhetorical circumstances reappears. Yancey’s highlighting disciplinary variations points toward uses of the bot to support students by providing examples and discussions of disciplinary formats for particular writing purposes.

Sociological and Anthropological Perspectives

According to Susan Blum's anthropological research on plagiarism: "Students experience competing demands on their time and energy that can lead to shortcuts in their writing process" (Blum, 2009, p. 27). Participation structures in classrooms could be altered to accommodate more time for challenging writing projects within a workshop structure with recurrent opportunities for peers to consult and to hold conferences with the teacher. Assessment could incorporate ongoing documentation and reflection on work processes which teachers could analyze for themes and patterns using AI as a thought partner.

Blum notes that "contemporary cultural practices of sharing, remixing, and collaborative authorship often conflict with traditional academic expectations," creating a "disconnect between students' digital lives and academic requirements" (Blum, 2009, p. 32). In this instance, school culture has become inherently contradictory. On one hand, collaboration is valued and encouraged; on the other, the work that counts is individual. This tension could be eased through fairly painless adjustments.

With reference to the difference between plagiarism and adults with job requirements or income responsibilities who must produce or find other suitable employment, Blum's research further suggests that "the economy of scarcity that governs academic publishing contrasts sharply with the economy of abundance that characterizes digital information sharing," creating conceptual difficulties for students navigating these different worlds (Blum, 2016, p. 211). In other words, academic publishing offers scarcity of texts often locked behind library paywalls. Standards for academic integrity in a peer-reviewed system with high professional stakes attached are probably not appropriate for rigorous application with learners.

James Lang's work on cheating in higher education identifies "environmental factors that influence academic misconduct," including "time pressure, perceived unfairness, and lack of engagement with course material" (Lang, 2013, p. 88). Lang argues that "creating learning environments that foster intrinsic motivation reduces incentives for cheating" and that "authentic assessment methods aligned with real-world writing tasks promote academic integrity" (Lang, 2013, p. 92). We all have experienced the work we do when we a deeply interested in the content or the ideas. In this cocoon cheating is the last thing that would satisfy curiosity. Cultivating the drive to improve one’s thinking, knowing, and literacy will go a long way toward diminishing the attraction of AI.

Institutional and Systemic Factors

A 2016 study published in the Journal of Academic Ethics found that "institutional context and assessment design significantly impact rates of academic misconduct," suggesting systemic factors beyond individual morality (Bretag et al., 2016, p. 1045). The researchers concluded that "high-stakes writing environments that emphasize grades over learning increase the likelihood of academic misconduct" and that "institutional honor codes are most effective when they emphasize community values rather than punishment" (Bretag et al., 2016, p. 1050). Tricia Bertram Gallant's research on academic integrity emphasizes that "misconduct occurs within educational systems and reflects their values and priorities" (Bertram Gallant, 2011, p. 33). She argues that "integrity initiatives should address organizational factors rather than focusing exclusively on student behavior" and that "institutional policies should balance fairness, education, and deterrence" (Bertram Gallant, 2011, p. 37).

Common Core as a Bridge: Connecting College AI Literacy with High School Writing Curriculum

While the conversation around AI and writing has largely centered on higher education, high school teachers face equally urgent questions about how to prepare students for writing in an AI-influenced world. This is where the Common Core State Standards (CCSS), despite having receded somewhat from public discourse in recent years, offer a promising bridge between the Task Force's college-oriented vision and the realities of secondary writing instruction.

The Common Core Standards, with their emphasis on college and career readiness, critical thinking, and technological literacy, provide an existing framework that aligns remarkably well with the AI literacy competencies outlined by the Task Force. Though drafted well before the emergence of powerful generative AI systems, the standards' focus on developing students' abilities to "use technology... to produce, publish, and update writing products," "gather relevant information from multiple authoritative sources," and "apply knowledge of language to understand how language functions in different contexts" speaks directly to the skills needed for ethical and effective engagement with AI writing tools.

This alignment creates a unique opportunity. High school teachers can leverage the Common Core as a familiar and established framework through which to introduce AI literacy concepts, effectively bridging the gap between secondary writing instruction and the college writing environments for which they are preparing students. Rather than requiring an entirely new curriculum or abandoning existing standards, teachers can view AI literacy as enhancing and extending the competencies already valued in the Common Core.

Furthermore, the Common Core's emphasis on rigor—defined as the cognitive energy required to work with complex, challenging content and apply it in new situations—provides a conceptual foundation for addressing AI in high school writing contexts. Far from undermining rigorous thinking, thoughtful engagement with AI tools can deepen students' understanding of writing processes, audience awareness, and rhetorical strategies. The Task Force's pedagogical resources demonstrate numerous ways that AI can be integrated into writing instruction while maintaining—and even enhancing—the cognitive complexity that the Common Core standards demand.

By connecting the Task Force's vision with the Common Core framework, high school teachers can prepare students for the realities of writing in college while ensuring they develop the critical and ethical awareness needed to navigate an increasingly AI-influenced writing landscape. This approach doesn't require abandoning existing curricula or standards; rather, it builds upon them, creating a seamless transition between high school writing instruction and the emerging pedagogies of college writing programs.

A Balanced Approach

The CCCC position generally advocates for treating instances as teachable moments, developing preventative approaches rather than purely punitive ones, and distinguishing between deliberate fraud and citation errors or developmental writing stages (CCCC, 2021). As composition scholar Rebecca Moore Howard concludes, "Our goal should be to help students enter academic discourse communities, not to exclude them from them" (Howard, 2007, p. 12).

This nuanced approach recognizes that academic integrity exists on a continuum rather than as a binary condition, acknowledging the complex interplay of intentionality, educational background, developmental stage, and institutional context (Bertram Gallant, 2017). By moving beyond simplistic notions of "cheating," the CCCC framework provides a more productive basis for addressing academic misconduct in ways that support student learning.

As writing scholar John Bean notes, "The ultimate goal is to help students develop an ethical stance toward knowledge creation that will serve them throughout their lives" (Bean, 2011, p. 88). This perspective positions academic integrity not merely as rule-following but as part of students' broader intellectual and ethical development. If teachers succeed at this task, AI will become a fringe benefit, not a distraction or an intruder.

References

1. MLA-CCCC Joint Task Force on Writing and AI. (2023). Student Guide to AI Literacy. Modern Language Association of America. https://style.mla.org/student-guide-to-ai-literacy/

2. Hess, K. (2009). Common Core State Standards: Rigor. Pennsylvania Department of Education. https://www.pdesas.org/Page/Viewer/ViewPage/11

3. The Conference on College Composition and Communication. (2023). Principles for the Postsecondary Teaching of Writing. National Council of Teachers of English. https://cccc.ncte.org/cccc/resources/positions/postsecondarywriting

4. MLA-CCCC Joint Task Force on Writing and AI. (2023). Working Paper 1: Overview of the Issues, Statement of Principles, and Recommendations. Modern Language Association of America. https://hcommons.org/app/uploads/sites/1003160/2023/07/MLA-CCCC-Joint-Task-Force-on-Writing-and-AI-Working-Paper-1.pdf

5. MLA-CCCC Joint Task Force on Writing and AI. (2024). Working Paper 3: Building a Culture for Generative AI Literacy in College Language, Literature, and Writing. Modern Language Association of America. https://aiandwriting.hcommons.org/working-paper-3/

6. Tekobbe, C. (2023). Critical AI and Indigenous Storytelling: Asking Purposeful Questions. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/12/04/critical-ai-and-indigenous-storytelling-asking-purposeful-questions/

7. McKee, H. (2023). Rhetorical Strategies for Prompting: Developing Prompt Literacies. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/27/rhetorical-strategies-for-prompting-developing-prompt-literacies/

8. Bjork, C. (2024). Write a story about... Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2024/04/19/write-a-story-about/

9. Law, J. B. (2024). Collaborating with AI to Engage Information Literacy. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2024/02/20/collaborating-with-ai-to-engage-information-literacy/

10. Marino, M., & Traester, M. (2023). The Turing Test. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/27/the-turing-test/

11. Rettberg, S. (2023). Authors Reviewing Authors Reviewing Authors Reviewing Authors Reviewing Authors Reviewing Authors Reviewing Authors Reviewing Authors. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/17/authors-reviewing-authors-reviewing-authors-reviewing-authors-reviewing-authors-reviewing-authors-reviewing-authors-reviewing-authors/

12. Jensen, K. (2023). Building Generative AI Literacy During the Writing Process. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/15/building-generative-ai-literacy-during-the-writing-process/

13. Kong, Y. (2023). Teaching Voice and Tone Through ChatGPT. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/12/20/teaching-voice-and-tone-through-chatgpt/

14. Watkins, M. (2023). AI Feedback Assistant: MyEssayFeedback. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/27/ai-feedback-assistant-myessayfeedback/

15. Knowles, A. M. (2023). The Few-Shot Prompt Booklet. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/27/the-few-shot-prompt-booklet/

16. Knowles, A. M. (2023). Exploring the Utility of LLMs through Prompt (Reverse) Engineering. Exploring AI Pedagogy. https://exploringaipedagogy.hcommons.org/2023/11/27/exploring-the-utility-of-llms-through-prompt-reverse-engineering/

17. UMass Amherst Writing Program. (2024). Additional AI Resources for Instructors. University of Massachusetts Amherst https://www.umass.edu/writing-program/additional-ai-resources-instructors

18. Common Core State Standards Initiative. (2010). Common Core State Standards for English Language Arts & Literacy in History/Social Studies, Science, and Technical Subjects. Council of Chief State School Officers and the National Governors Association. http://www.corestandards.org/ELA-Literacy/