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Statement on AI and Writing Across the Curriculum

Unanimously endorsed by the Association for Writing Across the Curriculum’s Executive Board on September 8, 2025, this living document affirms the central role of writing in higher education—as a human-centered activity grounded in rhetorical judgment, reflection, and critical thinking. It offers guiding principles, audience-specific recommendations, and practical resources for teaching and learning with generative AI across disciplines, and will continue to evolve in response to community feedback and emerging needs.

AWAC Statement on AI and WAC PDF

Table of Contents

  • Document Information
  • Part I — Guiding Principles and Reaffirmations
    • Introduction
    • Guiding Principles for AI and Writing Across the Curriculum
    • Reaffirming Writing as Human-Centered Inquiry
  • Part II — The Role of WAC in a Changing Educational Landscape: Recommendations for Educators, Students, & Administrators
    • WAC Guidance for Educators Across the Disciplines: Teaching Writing with and about AI
    • WAC Guidance for Students: Understanding, Writing, and Building Agency with AI Across the Curriculum
    • Institutional and Policy Guidance for Ethical and Effective AI Use in Writing Instruction
    • Sustaining WAC Leadership in an AI Era
  • Part III — Appendices & Resources
    • Appendix A: Selected Glossary of AI and Writing Terms
    • Appendix B: Resources and Further Reading
    • Appendix C: Sample Activities and Decision Guides
    • Appendix D: AI Use Policy & Reflection Resources
  • Citation Information

Document Information

AWAC Statement on AI in Writing Across the Curriculum

Authors

AWAC Working Group on AI in WAC

Co-Authors & Integrating Editors (alphabetical) 

Crystal N. Fodrey, University of Louisville
Kristi Girdharry, Babson College

Primary Authors — Working-Group Leads (alphabetical)

Christopher R. Basgier, Auburn University
Kirsti Cole, North Carolina State University
Traci Gardner, Virginia Tech
Magdelyn Helwig, Furman University
Swan Kim, Brooklyn College (CUNY)
Mary Laughlin, Fairfield University
Nicole Markert, Eastern University
Paula Rosinski, Elon University

Provenance

This statement integrates and revises the conceptual frameworks and draft language developed by three AWAC working groups. Working groups and contributing authors:

  • Critical AI Literacy —  Leads: Christopher R. Basgier, Magdelyn Helwig, and Swan Kim; other contributors: Holly Anderson, Geoff Clegg, Emily Hall, William Johnson, Jenna Morton-Aiken, Alexis Ramsey, and Jamie Thornton.
  • AI & Academic Integrity — Leads: Mary Laughlin and Nicole Markert; other contributors: Bonniejean Alford, Melissa Bahle, and Charles C. Grimm.
  • AI Uses & Misuses — Leads: Kirsti Cole, Traci Gardner, and Paula Rosinski

Additional Early-Phase Contributors (project inception; no drafting role in the present version): Anthony Albright, David Grant, Sylvia Hayes, Forrest Helvie, Jeffrey Mok, Gabriel Morrison, Jennifer Wells, and Anna Zendell. We acknowledge their formative work in early scoping and planning. Inclusion does not imply authorship, review, or endorsement of this statement.

This statement builds on the original 2023 AWAC AI Statement authored by Doug Hesse, Justin Rademaekers, Ann Blakeslee, Laurie Britt-Smith, Karen Moroski-Rigney, Sherri Craig, Paula Rosinski, and Stacey Sheriff, whose leadership and insight laid the foundation for this expanded version. (Rosinski is also a Primary Author of the present statement.)

Review

We thank the following individuals for reviewing and providing helpful feedback and revision suggestions on an earlier version of this statement at the 2025 International Writing Across the Curriculum (IWAC) Conference in Fort Collins, CO: Ann Blakeslee, Paul Cook, Leslie Davis, Julie Fiorelli, Beth Harnick-Shapiro, Mark Hussey, Elizabeth Kimball, Robin Konger, Marit MacArthur, Caitlin Martin, Susan Wolff Murphy, Michael Pemberton, Tom Polk, Lisa Sperber, Max White, Carl Whithaus, Liping Yang, and others who provided feedback anonymously.

Endorsement

The AWAC Executive Board voted unanimously to endorse this statement on September 8, 2025.

Versioning

Version 2.0 — September 12, 2025 • Lead contact: ude.ellivsiuol@yerdof.latsyrc  

Permalink: https://wacassociation.org/ai-statement/ 

Role legend

  • Co-Authors & Integrating Editors: Conceptualization, Writing—review & editing, Project administration
  • Primary Authors (WG Leads): Writing—original drafts, Conceptualization, Investigation
  • Contributing Authors (WG Members): Resources, Validation, Feedback

How to Cite

APA (association as author):
AWAC Working Group on AI in WAC. (2025). AWAC Statement on AI and Writing Across the Curriculum (Version 2.0). Association for Writing Across the Curriculum. https://wacassociation.org/ai-statement/ 

APA (named co-authors):
Fodrey, C. N., & Girdharry, K. (Integrating Eds.); Basgier, C. R., Cole, K., Gardner, T., Helwig, M., Kim, S., Laughlin, M., Markert, N., & Rosinski, P. (Primary Authors). (2025). AWAC Statement on AI and Writing Across the Curriculum (Version 2.0). Association for Writing Across the Curriculum. https://wacassociation.org/ai-statement/

Part I — Guiding Principles and Reaffirmations 

Introduction

Generative artificial intelligence (AI) is transforming the teaching and learning of writing, presenting both opportunities and challenges. While AI tools can support aspects of the writing process and knowledge creation, they also complicate authorship, copyright, ethics, academic integrity, pedagogy, and student learning. These tensions are not new. Writing is itself a technology, and our writing ecologies have long included emerging tools that simultaneously support and complicate how we teach and learn, making critical AI literacy — the ability to critically analyze, evaluate, and reflect on the use of AI tools in reading, writing, and research — essential from the outset.

Writing Across the Curriculum (WAC) scholar-practitioners and programs support postsecondary literacy instruction across academic disciplines by helping educators integrate discipline-relevant writing into their teaching, guided by principles of rhetorical awareness, inclusive pedagogy, and inquiry-driven learning. WAC is uniquely equipped to respond to AI in ways that foreground these values across higher education contexts. We affirm the AWAC Executive Committee’s 2023 position articulated in the “Statement on Artificial Intelligence Writing Tools in Writing Across the Curriculum Settings” that writing is a mode of learning, not simply a means of assessment, and we build from that foundation to offer expanded guidance for writing instruction in the age of AI. We emphasize that generative AI is not inherently good, harmful, or neutral; its impact depends on how it is understood, used, taught, and integrated into our writing ecologies.

This expanded AWAC AI statement was collaboratively developed—with some AI assistance as a drafting and synthesis tool—by integrating the work of three AWAC working groups convened over the 2024–25 academic year focusing on critical AI literacy, academic integrity, and AI use and misuse. It reflects priorities shaped by their collective expertise. The statement is designed to equip educators across disciplines to integrate AI ethically and effectively, to guide students in navigating writing with AI, and to inform educators and institutional leaders shaping policy and practice. Each section can stand on its own or be used alongside others, highlighting opportunities to foreground writing as a form of critical inquiry and meaning-making—even, and especially, when AI is part of the process.

Guiding Principles for AI and Writing Across the Curriculum

The following guiding principles reflect AWAC’s values and build on our organization’s 2023 “Statement on Artificial Intelligence Writing Tools in Writing Across the Curriculum Settings,” incorporating insight from recent working groups and published scholarship. Together, these principles affirm our shared commitments and provide a foundation for the guidance offered in this statement. Across postsecondary contexts, we should: 

Champion writing as a human-centered activity grounded in rhetorical judgment and critical thinking.

Writing is not merely a means of transmitting information but a practice of inquiry, communication, and reflection across modalities. Generative AI can support and augment—but should not replace—the development of these abilities.

Recognize AI tools as sites of struggle.

AI technologies are designed, trained, and deployed within cultural, economic, political, and environmental contexts that shape how they function. Technology is neither neutral nor deterministic; it will not inherently save or doom us. Rather, technology is a site of struggle, and it is important that we intervene now to shape responsible, ethical, and pedagogically sound AI-augmented writing practices, while also addressing the environmental costs and sustainability of their use.

Ensure inclusive, equitable writing instruction.

Educators and administrators should account for uneven student access to AI tools and digital literacies. We must also resist the assumption that all students experience or use AI in the same ways.

Address academic integrity through critical engagement.

Students need support in understanding the evolving ethical and cognitive implications of AI use, not just rules for compliance. Writing instruction should invite students to consider if, when, and why certain uses of AI are appropriate.

Honor faculty agency and disciplinary context.

AI policies and practices should respect disciplinary expertise and pedagogical diversity. WAC resources can help educators craft course-level policies aligned with departmental, institutional, and ethical frameworks.

Develop transparent, flexible institutional policy informed by educators.

AI policies should be adaptable to evolving technologies and teaching contexts. They should be developed with input from WAC scholar-practitioners and other relevant faculty/stakeholders, not imposed without consultation.

Empower writing across the curriculum programs and WAC professionals to lead.

As specialists in writing pedagogy, rhetoric, and faculty development, WAC leaders are uniquely positioned to guide cross-disciplinary conversations and practices around generative AI use across all forms of multimodal writing. This presumes that WAC scholar-practitioners continually develop their knowledge in these areas and contribute—as time and context allow—to the sustained efforts required to realize these principles in practice.

These guiding principles set the foundation. The following commitments reaffirm how WAC programs and professionals as well as postsecondary institutions more broadly can enact them in practice, keeping human-centered inquiry at the heart of writing instruction in the age of AI.

Reaffirming Writing as Human-Centered Inquiry

As generative AI becomes more integrated into higher education, WAC scholar-practitioners and programs are positioned to champion teaching practices and policies that keep human learning, creativity, and rhetorical agency at the center of writing instruction. Writing is a deeply human act—a process of discovery, intellectual labor, and participation in academic and civic life. It is also a process shaped by technologies, from the printing press to the word processor to predictive text and generative AI. Therefore, across postsecondary contexts, we should: 

Treat writing as a process of inquiry.

Writing is enriched by revision and dialogue. It challenges writers to engage complex ideas and situate themselves within disciplinary and cultural contexts. Writing instruction should resist product-oriented models and avoid overreliance on generative AI, which can diminish student agency and meaningful engagement.

Make pedagogical choices intentionally.

Generative AI presents a spectrum of options for writing instruction—from restricting its use entirely, to integrating it selectively, to engaging with it as a subject of critical inquiry. These choices should be made intentionally, grounded in disciplinary values and learning goals. Educators, administrators, and institutions should reject narratives that present AI as a replacement for writing or writing instruction. Instead, they should promote approaches that enhance learning, foster transparency, and develop students’ rhetorical judgment—the ability to make informed, context-sensitive choices about communication strategies, purposes, and tools.

Invite critical engagement with AI tools as rhetorical actors.

The teaching of writing should evolve with emerging technologies intentionally, reflectively, and in alignment with pedagogical values. AI use in classrooms should never be passive or assumed. Instead, instruction should invite students to engage critically with AI tools as rhetorical actors—tools that shape meaning and discourse, are created through human choices, and are influenced by biases and cultural contexts that can reproduce inequities.

Extend intentionality beyond the classroom.

This call for intentionality applies to institutional policy, classroom practice, and cross-disciplinary collaboration. Whether educators restrict, critically engage with, or integrate AI, they should act in ways that promote equity, transparency, and the centrality of writing as inquiry. By doing so, WAC professionals, educators, and academic leaders can shape not only how AI is used in writing instruction, but also how we protect and advance the educational values that writing embodies.

Part II — The Role of WAC in a Changing Educational Landscape: Recommendations for Educators, Students, & Administrators

Building on shared WAC principles, Part II of this statement offers practical guidance for key stakeholders of WAC programs and support—educators, students, and academic administrators—navigating the changing landscape of writing instruction. What follows are recommended roles and actions designed to support informed, flexible, and pedagogically grounded approaches to AI across diverse educational contexts.

Roles and Actions Summary Table

Stakeholder Key Roles Recommended Actions
Educators Implement AI-aware pedagogy. Foster student agency and ethical engagement.
  • Develop clear course-level AI policies aligned with disciplinary goals.
  • Use AI as a subject of critical inquiry in writing assignments.
  • Incorporate student reflection on AI use and its rhetorical and cognitive impact.
  • Offer scaffolded activities to explore AI biases and decision-making.
Students Engage actively in the writing process. Reflect critically on AI use.
  • Participate in assignments that explore the ethics and rhetoric of AI.
  • Reflect on when, why, and how AI is used in their own writing.
  • Learn about how AI tools are trained, who benefits from them, and what values they promote.
  • Uphold academic integrity through transparent, intentional writing practices.
Administrators Set institutional tone and policies for AI use. Provide support for educator development.
  • Consult WAC professionals among other relevant faculty/stakeholders when creating or revising AI policies.
  • Fund educational development initiatives focused on critical AI literacy and writing instruction.
  • Promote equitable access to AI tools and technologies.

Guidance for Educators, Students, & Institutions

Guidance for Educators

WAC Guidance for Educators Across the Disciplines: Teaching Writing with and about AI

As an educator, you play a critical role in helping students navigate the rhetorical, ethical, and disciplinary dimensions of writing with AI. Whether you choose to restrict AI use, integrate it selectively, or make it a focus of critical inquiry, your decisions should align with course goals, disciplinary norms, and your institutional context (see “Guiding Principles” for values to guide these choices and Appendix C for a “Decision-Making Framework”). In any case, you do not have to do this alone. Writing Across the Curriculum (WAC) scholar-practitioners, writing centers, and other campus partners can support you in making informed, pedagogically sound decisions about AI and writing, and you can learn more about AI and writing from resources shared by the Association for Writing Across the Curriculum and the WAC Clearinghouse.

WAC is an educational approach that supports student writing and communication across modalities and disciplines—not just in writing or English courses. WAC professionals partner with faculty across fields of study to integrate writing into their courses in ways that deepen disciplinary learning, strengthen critical thinking, and foster transferable communication skills. In the context of generative AI, WAC programs, writing centers, and other campus partners can help you design assignments, policies, and teaching strategies that align with both disciplinary values and institutional mission.

Building Foundational Understanding

Regardless of stance, it is valuable to develop a foundational understanding of the capabilities and limitations of generative AI tools in order to clarify expectations and facilitate meaningful engagement with your students. These systems generate text based on probabilistic language models rather than cognition, rhetorical awareness, or subject matter expertise. Their default outputs often reflect fluency over complexity, producing smooth but shallow prose. Treating AI tools as neutral aids risks reinforcing those tendencies; positioning AI as rhetorical actors—tools that shape meaning and discourse, are created through human choices, and are influenced by biases and cultural contexts—can help students analyze both its capabilities and the ideological assumptions embedded in its design.

If you use AI in your own teaching, disclose that to your students. Reciprocal transparency models ethical practice, fosters trust, and helps students understand why and how you have used AI tools in teaching and assessment.

Four Pedagogical Domains to Explore

  • Using AI rhetorically – Keep the dynamic interplay of writer, audience, and context in mind, along with how each is impacted by bias and inaccuracy. Communicate clear guidelines around AI use while recognizing the complex positionality of learners moving between courses with differing approaches.
  • Incorporating AI into writing processes – Treat writing as a process of knowledge creation. Help students learn to use AI as a supplement rather than a replacement for critical thinking, and encourage them to engage with AI feedback in ways that support—not compromise—their learning.
  • Exploring AI ethics through writing – Use writing as a space to examine ethical issues most relevant to your discipline, discussing both potential benefits and harms, including bias, equity, and environmental impact.
  • Learning to write with AI – Work with colleagues to define locally relevant critical AI literacy standards grounded in disciplinary theories, professional ethics, and institutional missions.Examples include comparing AI-generated and human-authored prose, assessing AI’s rhetorical decisions, critiquing its biases, and investigating its training and ownership. Dialogue can also address who profits from AI’s deployment, what values it encodes, and what its limitations mean for disciplinary knowledge-making.

Assessment Considerations

Assessment in the age of AI requires the same intentionality that has always been essential to good teaching, while accounting for new complexities. Faculty may need to develop ways to assess student work based on whether and how students use AI—recognizing that process often reveals more about learning than product alone. This makes student reflection on and disclosure of AI use especially important, as a “messy” first draft from a student who conscientiously avoids AI may look very different—but still be strong—compared to work from a peer who uses AI throughout the writing process. Consider using approaches such as reflection, portfolio assessment, and scaffolded assignments to understand students’ decision-making and development.

In keeping with principles of good faith and mutual trust, faculty who use AI in their own teaching or feedback should also disclose that use, modeling the transparency they expect in return.

The Association for Writing Across the Curriculum also recommends against relying on AI-detection tools as a primary means of evaluation. These systems are unreliable and risk false accusations. If used at all, they should be part of a transparent, collaborative process in which students are invited to discuss their writing process and AI use.

Equity and Accessibility

Recognize that students’ relationships to AI are shaped by many factors, including disciplinary norms, language background, technological access, and prior instruction. Some multilingual learners, neurodivergent students, and students with disabilities may use certain AI tools for translation assistance and/or accessibility support; others may choose to avoid them entirely. Avoid assuming that AI use is—or is not—linked to these identities, and create space for all students to make informed, agency-driven choices.

Recommended Strategies

  • Develop and communicate clear, course-specific policies about AI use that reflect your pedagogical intent and disciplinary norms.
  • Incorporate activities that foster critical AI literacy, such as comparing human-written and AI-generated texts or investigating algorithmic bias.
  • Use reflective writing to prompt students to describe how they used AI tools as part of their process, promoting accountability and metacognition.
  • Frame AI as a site of inquiry, inviting students to examine its design, rhetorical tendencies, and broader cultural implications.

By approaching AI not as a shortcut but as a generative site for ethical reflection, rhetorical awareness, and intellectual growth, you can help students deepen their learning and prepare them for a world in which AI will continue to shape communication. For further guidance and resources, consult AWAC, the WAC Clearinghouse, and your campus WAC resources.

Guidance for Students

WAC Guidance for Students: Understanding, Writing, and Building Agency with AI Across the Curriculum

As a student, you are learning in a time when writing and communication are being shaped by powerful new technologies like generative artificial intelligence (AI). Your response to these changes likely falls somewhere on a spectrum — from excitement and curiosity, to uncertainty or skepticism, to concern about its impacts, to ambivalence — or you may shift among these feelings as you gain experience. Whatever your starting point, you can develop the skills and awareness to use AI intentionally and ethically in ways that strengthen your learning, uphold your integrity, and prepare you for future communication contexts (see “Guiding Principles” for the values behind these ideas).

Writing Across the Curriculum (WAC) can help you do this. WAC is an educational approach that supports student writing and communication in all disciplines—not just in writing or English courses. It emphasizes writing as a tool for learning, critical thinking, and professional preparation. In the context of AI, WAC invites you to see writing as a process of discovery, knowledge-making, and meaning-making—one that creates space for exploration, inquiry, and dialogue—that AI can sometimes support but should not replace.

Building Your Understanding of AI in Writing

Generative AI tools produce text based on patterns in large datasets; they do not think, understand, or hold expertise. Their default outputs often prioritize fluency over depth, producing smooth but sometimes shallow or inaccurate prose. Treating AI as a neutral helper can reinforce these tendencies; approaching it as a rhetorical actor—a tool that shapes meaning, reflects human choices, and carries biases—can help you analyze its strengths, limitations, and the values embedded in its design.

Students vary widely in their familiarity, comfort, and access to AI tools. Differences may be shaped by prior instruction, language background, disciplinary norms, personal ethics, and access to technology. This disparity is part of a growing digital divide. Being intentional about how you approach AI—building from where you are toward more critical, reflective engagement—can help you use these tools in ways that benefit your learning if you so choose.

Four Ways to Engage AI in Your Writing

  1. Use AI rhetorically – Consider the relationships among writer, audience, and context, and how each is affected by bias or inaccuracy in AI outputs. Learn the AI expectations in each of your courses, which may vary.
  2. Integrate AI into your writing process – Treat writing as a process by which knowledge is created. If you use AI, make it a supplement to—not a replacement for—your own reasoning. Engage actively with any AI-generated feedback so it supports your growth rather than substituting for your work.
  3. Learn about AI ethics through writing – Use writing to explore ethical issues relevant to your discipline, including bias, environmental impact, intellectual property, and privacy. Consider who profits from AI deployment and what values the technology encodes.
  4. Learn to write with AI – Understand your discipline’s standards for critical AI literacy — the ability to analyze, evaluate, and reflect on the use of AI tools — which may connect to professional ethics, research practices, and institutional values. 

Academic Integrity, Transparency, and Agency

Using AI without permission or acknowledgment may be academically dishonest—not because AI is inherently unethical, but because undisclosed use can misrepresent your thinking and engagement. By contrast, transparent and reflective AI use, guided by your instructor’s expectations, can be a powerful part of your learning process. Ideally, conversations about academic integrity and AI will focus on transparency, dialogue, and growth rather than only right/wrong judgments.

You also have the right to privacy and control over your intellectual property. If you are asked to use AI, be aware that entering your work into some systems may store it permanently or use it to train future models. If this concerns you, ask your instructor about alternatives.

Practical Strategies for Students

  • Ask your instructors to clarify their AI policies for each course.
  • Use reflective writing to document how and why you used AI in an assignment.
  • Compare AI-generated and human-written texts to sharpen your critical reading skills.
  • Discuss with peers and instructors the cultural, environmental, and political implications of AI.
  • Treat AI as a site for inquiry. It is something to question, test, and learn from, not just a shortcut.

By approaching AI with curiosity, responsibility, and awareness, you can strengthen your writing, deepen your learning, and prepare to communicate effectively in an AI-shaped world.

Guidance for Institutions

Institutional and Policy Guidance for Ethical and Effective AI Use in Writing Instruction

As generative AI becomes embedded in higher education, institutions need policies that protect learning while remaining adaptable to rapid change. A clear starting point is Writing Across the Curriculum (WAC): a campus-wide approach that understands writing in its broadest sense—from reflective journaling and reading annotations to collaborative reports, public scholarship, and multimedia projects—not as a peripheral task, but as a core method for learning, making knowledge, and engaging in the practices of a discipline. WAC leaders and programs help educators integrate writing into courses across fields of study so that communication practices serve the goals of the discipline, not just the requirements of a single class.

Because WAC scholar-practitioners work across departments and keep pedagogy, equity, and assessment in view, they are well positioned to convene campus conversations about AI, translate disciplinary needs into coherent policy, and align decisions with learning outcomes (see “Guiding Principles” for details). Even on campuses without a formal WAC program, administrators can leverage WAC principles by tapping writing specialists (e.g., writing center and writing program leaders) to coordinate faculty input and guide policy development. Resources from the Association for Writing Across the Curriculum (AWAC) and the WAC Clearinghouse can support this institutional work.

Institutional policy around AI should be relevant to the full range of communicative practices in higher education—writing, reading, data representation, image generation, and information literacy—and adaptable to varied disciplinary needs and uses. Policies should reflect context-specific evidence-supported practices, emerging research on student usage of AI tools, and evolving understanding of AI technologies.

To this end, the Association for Writing Across the Curriculum recommends institutional policies that are written by—and in consultation with—institutional stakeholders educated on AI and that:

  • Prioritize AI literacy over punitive approaches. Banning AI use outright risks conflating all use with misconduct and undermining opportunities for critical engagement. Similarly, relying on AI detection software as the primary enforcement mechanism can produce false accusations and erode trust between students and educators. Institutions should instead define what ethical, transparent, and pedagogically appropriate AI use looks like within writing and disciplinary contexts.
  • Support transparent AI use and documentation. Institutions can promote ethical engagement by encouraging and equipping educators to include discipline-specific, course-level AI use statements in their syllabi (in contexts where allowed by institutional or departmental policy), to be transparent about their own instructional use of AI tools, and to ask students to disclose and reflect on how they use AI in their processes (see Appendix D). Such transparency—by both educators and students—enables dialogue about appropriate use, supports assessment practices, and fosters accountability.
  • Acknowledge AI as a matter of equity and accessibility. Some students—especially multilingual learners, neurodivergent students, and those with disabilities—may benefit from certain AI tools as accessibility supports. Avoid assuming that AI use is linked to these identities. Policies should protect the diversity of student voices by discouraging overreliance on AI tools that homogenize language and rhetorical style. They should also differentiate between accessibility uses and academically dishonest uses, allowing for case-by-case instructional judgment, and support scaffolding so that students can use AI for feedback, brainstorming, and language support without replacing their own writing entirely.
  • Ensure privacy, data ethics, and institutional accountability. As institutions adopt AI-driven educational technologies, they should evaluate how these tools collect, store, and use student and faculty data, and assess them for bias, accessibility compliance, security, and labor practices. Writing programs and centers should advocate for data transparency, informed consent, and protection against surveillance or commercial exploitation. Students should also understand that inputting others’ work—including peer writing or faculty-created materials—into AI tools without explicit permission raises ethical concerns and may violate intellectual property expectations.
  • Engage educators across disciplines in AI policy development. The expertise of WAC professionals is essential in leading cross-disciplinary conversations that surface differences in disciplinary values, rhetorical priorities, and the goals of writing instruction. Policies should be shaped by these collaborative insights, rather than imposed through a one-size-fits-all model.
  • Use AI detection tools, if at all, only as part of a multi-pronged approach. AWAC recommends avoiding detection software as a sole enforcement measure. Where used, detection should be transparent, supplemented by process-based assessment, and mindful of false positive risks.
  • Commit to iterative policy review. Institutional policies should include a mechanism for regular review and revision as AI technology and its educational applications evolve rapidly. Institutions should revisit AI policies regularly—ideally each academic year—in consultation with faculty, students, technologists, and WAC specialists to ensure continued relevance, equity, and pedagogical grounding.

Institutional policies that support AI literacy, transparency, and equity position students to navigate complex communication environments both within and beyond the university. WAC professionals can serve as advocates and consultants in this work, ensuring that AI-related decisions are pedagogically informed, ethically grounded, and equitable in their implementation.

Sustaining WAC Leadership in an AI Era

Together, these recommendations underscore a central premise of WAC work: that writing instruction is most effective when it is context-aware, collaboratively supported, and rooted in inquiry. As institutions and individuals make decisions about how to respond to generative AI, WAC practitioners and programs can serve as essential partners in shaping approaches that uphold the integrity of student learning while embracing the opportunities—and addressing the challenges—of writing in a rapidly changing world.

Part III — Appendices & Resources 

Appendix A: Selected Glossary of AI and Writing Terms

Appendix A: Selected Glossary of AI and Writing Terms

To ensure clarity in rapidly evolving conversations about AI and writing, we offer the following definitions:

  • Academic Dishonesty: Behavior that intentionally violates academic policy, including but not limited to plagiarism, cheating, misrepresentation of data, or any practice that confers an unfair advantage. 
  • Academic Integrity: The ethical practice of representing one’s work honestly while respecting the contributions of others and upholding the standards of scholarly and educational communities. 
  • AI Literacy: The ability to critically analyze, evaluate, and reflect on the use of AI tools in reading, writing, and research. AI literacy includes awareness of AI’s limitations, biases, ethical implications, and labor impacts, as well as its potential applications.
  • Artificial Intelligence (AI) Detectors: Software tools designed to determine whether a piece of writing was generated by AI rather than a human. These tools may themselves be AI-driven and can produce false positives, especially for multilingual learners and neurodivergent students.
  • Critical AI Literacy: A framework that centers ethical reasoning, transparency, and student learning. It resists passive AI use and positions AI as a topic of inquiry, encouraging students and educators to interrogate its rhetorical, cultural, and material dimensions.
  • Generative Artificial Intelligence (AI): Technologies such as OpenAI’s ChatGPT or DALL-E, Anthropic’s Claude, Google’s Gemini, and others that can produce content (e.g., text, code, images) in response to user input. These tools are trained on massive data sets and function by predicting patterns in language rather than demonstrating understanding, originality, or rhetorical intent.
  • Hallucination: An inaccurate or erroneous output produced by an AI tool, including incorrect facts or misrepresented images, sounds, or motions. 
  • Large Language Models (LLMs): A subset of generative AI technologies trained on massive corpora of text to predict language patterns based on user input (prompts). Some LLMs are trained on closed datasets; others access the open web.
  • Plagiarism: The act of copying another person’s work and presenting it as one’s own. In the context of AI, defining plagiarism requires nuanced consideration of authorship and tool use. 
  • Prompt: The input provided by a user to elicit a response from an AI tool. Prompts can be simple or involve iterative prompting (successive refinements) or prompt engineering (strategically crafted input to optimize outputs).
  • Training (of AI): The process of refining AI behavior and output through human-rated feedback and guardrails. This hidden labor helps determine how AI tools respond to user queries and what values are embedded in their responses.
  • Writing: A social, cognitive, rhetorical, and material activity that fosters learning, communication, identity formation, and participation in disciplinary and public discourse. 
  • Writing Instruction: A pedagogical practice that helps students engage with writing as a process of discovery, reflection, and knowledge-making. Writing instruction can be enhanced—but not replaced—by technological tools. 
  • Writing Ecologies: The full range of contexts, technologies, institutions, and relationships that shape writing practices. Writing ecologies include both human and nonhuman actors, including AI. 

Appendix B: Resources and Further Reading

Appendix B: Resources and Further Reading

The following resources were recommended by the original author groups as valuable for understanding the pedagogical, ethical, and technological dimensions of AI in writing instruction. These sources may be useful for WAC professionals, educators, and institutional leaders seeking to explore these issues in greater depth.

Adisa, K., Byrd, A., Ene, E., Flores, L., Giordano, J., Green, D., Hassel, H., Hendrickson, J., Johnson, S. Z., Kirschenbaum, M., Lockett, A., Losh, E. M., Mckoy, T., Mills, A., Mina, L., Perdue, S. W., Ruttenberg, J., Wang, Z., Ward, J., & William, J. (2024, October). Building a culture for generative AI literacy in college language, literature, and writing. MLA-CCCC Joint Task Force on Writing and AI. https://hcommons.org/app/uploads/sites/1003160/2024/11/MLA-CCCC-Joint-Task-Force-WP-3-Building-Culture-for-Gen-AI-Literacy.pdf 

Anders, A. (2024). Using AI for learning: Functional, critical, and ethical considerations. Top Hat. https://tophat.com/catalog/-/-/full-course/using-ai-for-learning/6232/ 

AWAC Executive Committee. (2023). Statement on artificial intelligence writing tools in writing across the curriculum settings. https://wacassociation.org/statement-on-ai-writing-tools-in-wac/ 

Bali, M. (2023). What I mean when I say critical AI literacy. Reflecting Allowed. https://blog.mahabali.me/educational-technology-2/what-i-mean-when-i-say-critical-ai-literacy/ 

Basgier, C., Mills, A., Olejnik, M., Rodak, M., & Sharma, S. (Under review). Bad ideas about AI and writing: Toward generative practices for teaching, learning, and communicating.

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT), 610–623. https://s10251.pcdn.co/pdf/2021-bender-parrots.pdf 

Bowen, J. A., & Watson, C. E. (2024). Teaching with AI: A practical guide to a new era of human learning. Johns Hopkins University Press.

Buyserie, B., Thurston, T. N., & Daniels, T. (2024). Teaching and generative AI. Utah State University. https://uen.pressbooks.pub/teachingandgenerativeai/ 

Cardona, M. A., Rodríguez, R. J., & Ishmael, K. (2023, May). Artificial intelligence and the future of teaching and learning: Insights and recommendations. U.S. Department of Education, Office of Educational Technology. https://www.ed.gov/sites/ed/files/documents/ai-report/ai-report.pdf 

Conrad, K. (2024). A blueprint for an AI bill of rights for education. Critical AI, 2(1). https://criticalai.org/2023/07/17/a-blueprint-for-an-ai-bill-of-rights-for-education-kathryn-conrad/ 

Crawford, K. (2021). Atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.

Fernandes, M., McIntyre, M., Gray, K., & Messina, C. M. (2024). Resources on refusing, rejecting, and rethinking generative AI in writing studies and higher education. https://tinyurl.com/ewwaibib 

Fernandes, T., & McIntyre, M. (2024). Everyone’s writing with AI (except me!): Episode 1. Kairos: A Journal of Rhetoric, Technology, and Pedagogy, 29(2). https://www.technorhetoric.net/29.2/disputatio/fernandes-mcintyre/ep1.html 

Gardner, T. (n.d.). Teaching writing across the curriculum with AI. https://teachingwacwithai.tracigardner.com/ 

Gegg-Harrison, W., & Quarterman, C. (2024). AI detection’s high false positive rates and the psychological and material impacts on students. In S. Mahmud (Ed.), Academic integrity in the age of artificial intelligence (pp. 199–219). IGI Global.

Goodlad, L., & Stone, M. (Eds.). (2024). Special issue on LLMs. Critical AI, 2(1) & 2(2). https://read.dukeupress.edu/critical-ai/issue/2/1 

Howard, R. M. (1992). A plagiarism pentimento. Journal of Teaching Writing, 11(2), 233–245.

Lang, J. M. (2013). Cheating lessons: Learning from academic dishonesty. Harvard University Press.

Law, J. (2024, October). Meeting students where they are: Data-driven generative AI opportunities. TYCA-GA Fall 2024 Conference. PowerPoint presentation.

McCombs, B. L. (2015, March 9). Developing responsible and autonomous learners: A key to motivating students. American Psychological Association. https://www.apa.org/education-career/k12/learners 

Mills, A. (Curator). (2023). AI text generators and teaching writing: Starting points for inquiry. WAC Clearinghouse. https://wac.colostate.edu/repository/collections/ai-text-generators-and-teaching-writing-starting-points-for-inquiry/ 

MLA-CCCC Joint Task Force on Writing and AI. (n.d.). Working papers. https://aiandwriting.hcommons.org/working-papers/ 

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. NYU Press.

Pitt, P., Dullaghan, K., & Sutherland-Smith, W. (2020). ‘Mess, stress and trauma’: Students’ experiences of formal contract cheating processes. Assessment & Evaluation in Higher Education, 46(4), 659–672.

Refusal to use generative AI. (n.d.). https://refusinggenai.wordpress.com/ 

Schnitzler, C., Vee, A., & Laquintano, T. (Eds.). (2024). TextGenEd: Continuing experiments. https://doi.org/10.37514/TWR-J.2024.2.1.01 

Shojaie, A. (2025, January 29). AI in education: Preparing students to lead in the age of machines. Forbes. https://www.forbes.com/councils/forbescoachescouncil/2025/01/29/ai-in-education-preparing-students-to-lead-in-the-age-of-machines/ 

Vee, A., Laquintano, T., & Schnitzler, C. (2023). TextGenEd: Teaching with text generation technologies. https://doi.org/10.37514/TWR-J.2023.1.1.02 

Wang, C., & Tian, Z. (Forthcoming). Rethinking writing education in the age of generative AI. Routledge.

Wang, H., & Dang, A. (2024). Enhancing L2 writing with generative AI: A systematic review of pedagogical integration and outcomes. System. https://doi.org/10.13140/RG.2.2.19572.16005 

Watkins, M. (2024). Engaging with AI isn’t adopting AI. Rhetorica. https://marcwatkins.substack.com/p/engaging-with-ai-isnt-adopting-ai 

Appendix C: Sample Activities and Decision Guides

Appendix C: Sample Activities and Decision Guides

In support of the educators and institutional strategies outlined in this document, the following sample activities and decision-making tools are provided to help educators engage with generative AI in writing-intensive courses. These materials can be adapted to various disciplines, course levels, and institutional policies, and are grounded in WAC principles of writing as a process of inquiry, reflection, and learning.

Rather than issuing universal mandates, we encourage flexible, context-sensitive approaches that allow for nuance and responsiveness across course levels and disciplines.

Decision-Making Framework for AI Integration

Before implementing AI-related activities, educators should determine whether a restrictive, critical engagement, or productive integration model best aligns with their course, discipline, and institutional context. Below is a decision-making framework to guide educators in tailoring AI use to their specific teaching needs:

Consideration Restrictive Approach (Minimal or No AI Use) Critical Engagement Approach (AI as a Site of Inquiry) Productive Integration Approach (AI as a Writing Tool)
Course Level Introductory writing courses where foundational skills need to be established without AI assistance. First-year writing, general education, and upper-level writing courses where students analyze AI’s rhetorical and ethical dimensions. Graduate research courses, professional writing, and advanced composition where AI is integrated into research, revision, or multimodal projects.
Disciplinary Context Disciplines with strict originality requirements (e.g., philosophy, creative writing, law). Humanities and social sciences where AI’s bias, credibility, and authorship can be analyzed critically. STEM, business, and technical writing where AI may already be industry-standard for drafting and data analysis.
Institutional Policy Constraints Universities with AI restrictions or strong plagiarism policies discouraging AI use. Institutions encouraging academic integrity discussions but leaving AI use open-ended. Programs that encourage AI literacy and integration as a professional skill.
Assessment Focus Emphasizes human-driven composition, rhetorical awareness, and traditional research skills. Focuses on evaluating AI critically—its rhetorical, ethical, and informational accuracy. Encourages strategic AI use for drafting, revision, or data-driven research writing.
Classroom AI Policy Prohibits AI use for assignments or allows only limited use with transparency. Requires students to evaluate AI outputs, critique AI’s role in writing, and engage in AI literacy activities. Encourages intentional AI use, asking students to document and reflect on how AI enhances or challenges their writing process.

How to Use This Guide

  • Educators of first-year writing may opt for a restrictive or critical engagement model, ensuring students develop core writing skills before introducing AI into the process.
  • Upper-division and interdisciplinary courses may take a critical engagement approach, using AI as an object of study to examine issues like authorship, bias, and credibility.
  • Graduate or professional writing courses may integrate AI productively, focusing on how AI functions as a tool for research, drafting, and revision while maintaining academic integrity.

By aligning AI integration with course goals, disciplinary needs, and institutional policies, educators can make informed pedagogical choices that support student learning while addressing ethical concerns. To accommodate a variety of teaching contexts, the following AI engagement strategies are flexible and adaptable, drawing from best practices outlined in Gardner’s Teaching WAC with AI. Educators can modify these activities to fit their pedagogical goals, disciplinary needs, institutional policies, and student experience levels. These activities align with a critical AI literacy approach, helping students examine AI’s affordances and limitations, ethical concerns, and rhetorical implications rather than merely using AI as a writing shortcut.

1. AI-Assisted Writing vs. Human Writing Analysis

Objective:

This exercise encourages students to compare AI-generated and human-authored texts, evaluating rhetorical effectiveness, coherence, depth, and originality.

Activity:

  1. Generate or provide two versions of a short essay or argument: one written by a human and another generated by an AI tool.
  2. Ask students to analyze both texts in terms of tone, coherence, depth of argumentation, and originality, using a structured rubric.
  3. Facilitate a discussion on:
    • How AI-written texts differ in style, complexity, and engagement with ideas.
    • Whether AI-generated content meets academic standards and rhetorical expectations.
    • What the presence of AI-generated writing means for authorship, citation, and academic integrity.
  4. Reflective Writing Assignment:
    • Students write a short reflection discussing where AI succeeds or fails in producing strong writing and what this means for writing as a cognitive process.

Assessment Guidelines:

  • Depth of analysis: Does the student critically engage with differences between AI-generated and human writing?
  • Use of evidence: Are claims supported with concrete examples from the texts?
  • Ethical implications: Does the student thoughtfully discuss AI’s role in authorship, citation, and academic integrity?

2. Ethical Use of AI in Writing: Case Studies

Objective:

This activity helps students explore the ethical dimensions of AI in academic, professional, and creative writing contexts.

Activity:

  1. Present real-world case studies where AI has been used unethically or controversially, such as:
    • AI-generated misinformation in news articles.
    • AI-assisted plagiarism or ghostwriting.
    • AI-generated resume writing or job application materials.
  2. Small group discussions:
    • What ethical dilemmas arise in each scenario?
    • How do institutions, employers, and educators regulate AI use?
    • Should AI be allowed in these contexts, and if so, under what conditions?
  3. Reflective Writing Assignment:
    • Students write a short response evaluating how AI should or should not be incorporated into different writing contexts (e.g., academic, professional, creative).

Assessment Guidelines:

  • Critical thinking and ethical reasoning: Does the student consider multiple perspectives on AI use?
  • Contextual understanding: Does the response address AI’s impact in specific writing situations?
  • Proposed solutions: Does the student offer well-reasoned recommendations for ethical AI use?

3. AI Bias and Transparency Exercises

Objective:

This exercise engages students in examining AI-generated content for bias, transparency, and accuracy, helping them understand how AI shapes knowledge production.

Activity:

  1. Generate AI-produced text on a controversial or complex topic.
  2. Students analyze the output for:
    • Bias in language or framing.
    • Omissions or inaccuracies.
    • Source credibility and verifiability.
  3. Compare AI-generated text to reputable human-authored sources.
  4. Class discussion:
    • How does AI’s training data shape its responses?
    • What are the implications of biased AI-generated texts in journalism, academia, and policy-making?
  5. Reflective Writing Assignment:
    • Students write an evaluation discussing how AI’s biases and limitations influence research, writing, and communication.

Assessment Guidelines:

  • Identification of bias and transparency issues: Does the student clearly articulate how AI-generated content reflects bias?
  • Comparison with human-authored sources: Does the student make meaningful distinctions between AI and traditional research methods?
  • Implications for writing and research: Does the student address how AI’s biases might affect knowledge production?

Additional AI Engagement Strategies

Beyond the core activities, educators can incorporate alternative AI literacy assignments into their courses:

4. AI Critique Assignments

  • Activity: Students critique an AI-generated text, assessing its effectiveness, coherence, and ethical considerations.
  • Learning Outcome: Helps students develop critical AI literacy by actively evaluating machine-generated content.

5. Comparative Analysis Projects

  • Activity: Students compare AI-generated and human-authored works in various genres (e.g., op-eds, research abstracts, creative writing).
  • Learning Outcome: Reinforces understanding of rhetorical and stylistic differences between human and machine writing.

6. AI-Assisted Research Reflection Exercises

  • Activity: Students use AI tools for preliminary research, then evaluate the credibility and biases of AI-generated summaries.
  • Learning Outcome: Encourages students to develop information literacy and recognize AI’s limitations as a research tool.

Ensuring Pedagogical Flexibility

AI engagement in writing instruction is not one-size-fits-all. Educators can:

  • Modify activities based on course level, disciplinary context, and student experience with AI.
  • Incorporate AI discussions into existing assignments rather than creating entirely new units.
  • Encourage students to document and reflect on their AI use to reinforce critical thinking and transparency.

By adopting these adaptable AI literacy strategies, educators can ensure that AI supports rather than undermines student learning. These approaches help students critically analyze AI outputs, assess ethical implications, and navigate AI’s role in writing responsibly.

Appendix D: AI Use Policy & Reflection Resources

Appendix D: AI Use Policy & Reflection Resources

Purpose and Use
Institutional policies on generative AI should be accompanied by concrete tools that help educators translate high-level guidance into classroom practice. The following resources are designed to:

  • Support faculty and TAs in creating clear, discipline- and course-specific policies about AI use in their syllabi.
  • Encourage transparency and accountability by prompting students to reflect on and disclose their AI use in their writing and learning processes.

These tools may be adapted for use across disciplines, course levels, and modalities. They are intended to foster dialogue, support pedagogical intent, and uphold academic integrity while promoting critical AI literacy.

AI Use Syllabus Policy Planning Heuristic

When drafting a syllabus policy on AI use, consider:

  1. Pedagogical Intent
    • How do you expect students to learn in this course?
    • How might AI support, supplement, or interfere with these learning goals?
  2. Disciplinary Norms & Professional Ethics
    • What are the values and ethical considerations in your field around AI and authorship?
    • How does this policy prepare students for real-world contexts in your discipline?
  3. Permitted Uses (if any)
    • Be specific about which AI tools or functions are allowed, restricted, or prohibited.
    • Clarify distinctions between acceptable support (e.g., brainstorming, language refinement) and unacceptable replacement of student work.
  4. Transparency & Disclosure
    • Ask students to indicate when and how they used AI (see reflection prompt below).
    • Model transparency by disclosing your own AI use in teaching, if any, in contexts where allowed by institutional or departmental policy.
  5. Assessment & Accountability
    • Consider how AI use will be evaluated in student work.
    • Avoid over-reliance on AI detection tools; if used, ensure they are part of a transparent, multi-pronged approach.
  6. Equity & Accessibility
    • Acknowledge that some students may use AI for accessibility or language support needs.
    • Avoid assumptions about AI use based on identity, and create pathways for equitable access to permitted tools.

Student Reflection & AI Disclosure Prompt

Instructions:
With your final submission for each major assignment, please respond briefly to the following questions. Your response will not affect your grade except where required for transparency or when non-disclosure violates the course AI policy.

  1. Did you use any AI tools for this assignment? (Examples: ChatGPT, Grammarly, translation tools, image generators.)
  2. If yes, describe:
    • Which tool(s) you used
    • At what stage(s) of your process (e.g., brainstorming, outlining, drafting, revising, editing)
    • What you asked the tool(s) to do
    • How you evaluated, adapted, or rejected its output
  3. If no, explain how you approached this work without AI tools.
  4. Reflection: What did you learn about your own writing and thinking from this process?

Citation Information

APA (association as author):
AWAC Working Group on AI in WAC. (2025). AWAC Statement on AI and Writing Across the Curriculum (Version 2.0). Association for Writing Across the Curriculum. https://wacassociation.org/ai-statement/ 

APA (named co-authors):
Fodrey, C. N., & Girdharry, K. (Integrating Eds.); Basgier, C. R., Cole, K., Gardner, T., Helwig, M., Kim, S., Laughlin, M., Markert, N., & Rosinski, P. (Primary Authors). (2025). AWAC Statement on AI and Writing Across the Curriculum (Version 2.0). Association for Writing Across the Curriculum. https://wacassociation.org/ai-statement/

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Brad Jacobsen, University of Texas El Paso

Bio: Brad Jacobson is Assistant Professor of English at The University of Texas at El Paso, where he teaches courses in writing studies and English education. His research focuses on student experiences writing across the high school to college transition and writing teacher education, and his work has appeared in Writing Program Administration, Currents in Teaching and Learning, and the Journal of Writing Assessment. In addition to his membership in AWAC, Brad is affiliated with CCC, NCTE, NWP, and the Coalition for Community Writing.

Statement: As a scholar and teacher, I am committed to facilitating reciprocal research, teaching, and learning opportunities across K-16 and community contexts. I believe AWAC is uniquely positioned to contribute to such collaborations. As Chair of the Partnerships committee, I would work with the committee to solidify our developing partnership with NWP while seeking new partnerships with like-minded organizations. I look forward to creating and sustaining opportunities like sponsored panels and collaborative events with our partners in the coming years.

Alisa Russell

Bio: Alisa Russell is an Assistant Professor of English and WAC Director in the Writing Program. Her areas of interest include rhetorical genre studies, public writing, and WAC, and her research focuses on increasing community access through writing and writing innovations. Her work has appeared in journals such as Composition Forum, The WAC Journal, Across the Disciplines, and Pedagogy. Alisa is a founder of the WAC Graduate Organization, and she currently serves as Co-Chair of the WAC Summer Institute Committee for AWAC. She enjoys hiking and re-watching television series.

Statement: For the first institute in 2019, our planning group met every month for a year and half prior: We juggled registration, housing, and catering logistics; we balanced budgets; we designed a jam-packed agenda and materials; we worked closely with local hosts; etc. And then the institute arrived, and it was like magic. WAC faculty from vastly different institutions and programs had this three day gift dedicated to learning from one another, developing their next steps, reenvisioning their program possibilities, and building community. All that hard planning work paid off. I would be honored to continue facilitating and improving this event as one piece of AWAC’s networked vision, the best part of which is collaborating closely with colleagues across WAC.

Mandy Olejnik

Bio: Mandy is a third-year PhD Candidate and Graduate Assistant Director of WAC Programs at the Howe Center for Writing Excellence (HCWE). Previously, she served as Graduate Assistant Director of the Howe Center for Business Writing where she worked with students and faculty across Miami’s business school. Mandy currently serves as Chair of WAC-GO and is conducting her dissertation research on graduate student writing support through case study research with graduate faculty on how WAC programming can support graduate students in the moment and, over time, in making meaningful programmatic change. She also is conducting research with the HCWE WAC team on innovative teaching of writing across disciplines.

Statement: As current Chair of the WAC-Graduate Organization (WAC-GO), I hope to bring more graduate student involvement in AWAC activities and membership in this role as WAC-GO AWAC chair. Specifically, I see overlap in some of WAC-GO’s research and mentoring plans and ongoing AWAC initiatives that could lead to beneficial partnerships (e.g., I could see WAC-GO members joining AWAC writing groups). WAC-GO is dedicated to connecting graduate students interested in WAC work with scholars and practitioners in the field. I would work to provide graduate students with such opportunities by learning more about and relaying the work of AWAC and its various committees.

Heather Falconer | Chris Basgier

Heather Falconer, Curry College

Bio: Heather is an Assistant Professor of Writing and WAC Coordinator at Curry College. Her research focuses on diversity, equity, and inclusion in disciplinary spaces (particularly STEM), and has focused her time with the Research and Publications Committee (first as Chair, then as Co-Chair) on planning opportunities to support scholars at all stages of research.

Chris Basgier, Auburn University

Bio: Christopher currently works as Acting Director of University Writing at Auburn University, where he helps faculty integrate high impact practices into their courses and leads professional development for the writing center staff. His research on WAC, rhetorical genre theory, writing program administration, and threshold concepts has appeared in Across the Disciplines, the WAC Journal, Double Helix, Prompt, and Composition Forum. He served on the IWAC 2018 planning committee and currently chairs the CCCC WAC Standing Group. As a founding member of AWAC, he participated in the organization’s planning group, and he is interim co-chair of the AWAC Research and Publications committee.

Joint Statement: As co-chairs of the Research and Publications Committee, Drs. Basgier and Falconer intend to continue our successful initiatives, including virtual writing groups, awards for excellent publications, and support for cross-organizational presentations with the AAC&U and others. We also plan to continue developing grants to support WAC/WID research. Finally, we plan to collaborate with WAC-GO on a survey to understand the current level of preparation graduate students receive in WAC theory and practice, with the goal of making recommendations to AWAC and the discipline in general.

Amy Cicchino | Lindsay Clark

Amy Cicchino, Auburn University

Bio: Amy Cicchino is Associate Director of University Writing at Auburn University. At Auburn, she supports faculty development within the WAC program, leads the Graduate Writing Partners program, facilitates workshops related to writing and writing instruction, and is currently expanding online resources for writing across the curriculum. Her research takes up writing program administration, multimodal online instruction, and teacher professionalization. She is a member of the AWAC Mentoring Committee, an Executive Board At-Large member of the Global Society for Online Literacy Educators (GSOLE), and a member on the Association for Authentic, Experimental, Evidence-Based Learning (AAEEBL)’s Digital Ethics taskforce.

Lindsay Clark, Sam Houston State University

Bio: Lindsay Clark is an Assistant Professor of Business Administration at Sam Houston State University where she teaches business and managerial communication courses, directs the College’s Communication Lab, and serves as Co-Chair of the University Writing in the Disciplines Committee. Her research includes visual and multimodal communication, genre theory and pedagogy, and writing across the curriculum. She is a member of the AWAC Mentoring Committee and serves as the Secretary/Treasurer for the Association for Business Communication, Southwest Region.

Joint Statement: As Co-Chairs of the AWAC Mentoring Committee, we hope to grow the initiatives developed by the committee in the last year, including the AWAC Board of Consultants, the workshop series on WAC leadership and pedagogy, and an online repository for WAC resources in collaboration with the WAC Clearinghouse. Additionally, we hope to create new opportunities for conversation and mentorship. In looking forward to the return of the WAC Summer Institute and IWAC conference, we would like to develop opportunities for semi-structured horizontal mentorship in those spaces in addition to more flexible mentoring events that could take place online throughout the academic year.

Chris M. Anson | Federico Navarro

Chris M. Anson, North Carolina State University

Bio: Chris Anson is Distinguished University Professor, Alumni Association Distinguished Graduate Professor, and Director of the Campus Writing and Speaking Program at North Carolina State University, where he works with faculty across the disciplines to enhance writing and speaking instruction. He has published 19 books and 140 articles and book chapters relating to writing, WAC, and WID, and has spoken widely across the U.S. and in 33 other countries. He is Past Chair of CCCC and Past President of the CWPA. He has received or participated as a co-principal investigator in over $2.1 million in grants. His full CV is at www.ansonica.net

Federico Navarro, Universidad de O’Higgins (Chile)

Bio: Federico Navarro is an Associate Professor and the President of the Latin American Association of Writing Studies in Higher Education and Professional Contexts (ALES) and the Chief Editor of International Exchanges: Latin America Section, The WAC Clearinghouse, Colorado State University. He has published more than 100 research papers in 12 countries, including the Spanish edition of “Reference Guide to WAC” (2016).

Joint Statement: Since AWAC was created, we have co-chaired the International Collaborations Committee with a goal of exploring how AWAC could extend its reach to learn from and exchange with people in many countries and organizations. We focused on three projects: 1) developing international AWAC affiliates and partnering, for starters, with organizations in Europe and Latin America; 2) working with international WAC representatives to collectively document trends in WAC and WID worldwide; 3) creating AWAC panels in international conferences. It would be a pleasure to see these projects to fruition and to embark on new initiatives for internationalization that will enrich research and instructional innovation across countries and cultures.

Swan Kim | LaKeisha McClary

Swan Kim, Bronx Community College at City University of New York

Bio: Swan Kim is an associate professor of English and Writing Across the Curriculum (WAC) coordinator at Bronx Community College (BCC) at City University of New York (CUNY). She received her PhD in English at University of Virginia specializing in Asian American diaspora. She teaches courses in composition and ethnic American literature. She has been directing the WAC program at BCC since 2015, and serving as the departmental personnel and budget committee, member of the faculty senate, and one of the co-leaders for the CUNY-wide WAC Professional Development.

LaKeisha McClary, George Washington University

Bio: LaKeisha McClary is an assistant professor of Chemistry. She has spent 9 years teaching a writing-in-the disciples (WID) 2000-level chemistry laboratory course that explicitly teaches students how to write a science manuscript. Her writing assignment received the 2020 Best Assignment Award from the GW WID Program. LaKeisha received her PhD in Chemistry from The University of Arizona and completed a postdoctoral fellowship in chemistry education research at Miami University. She currently serves as the mentor for GW Posse 2 cohort, a leadership and merit based scholarship program aimed to increase diversity, equity, and inclusion on campus. She also is the inaugural Director of Undergraduate Studies in Chemistry.

Joint Statement: Participating in the Diversity, Equity, and Inclusion (DEI) committee meetings through the pandemic, we found ourselves sharing the same vision for AWAC. We are both eager to bring what we learned in theory and practice over the years: Dr. McClary, as a seasoned instructor of WID in Chemistry and mentor of DEI initiatives, and Dr. Kim, as a WAC coordinator at a Hispanic Serving Institution and who has also specialized in Asian diaspora. As co-chairs of the DEI committee, we will collaboratively lead, support, and promote efforts to find creative, simple, and impactful ways to incorporate DEI into AWAC. Our goal is to work toward implementing DEI so that it does not become an add-on but an integral part of AWAC.

Paula Rosinski

Bio: Paula Rosinski is a professor of English/Professional Writing & Rhetoric and Writing Across the University Director at Elon University. She led her university’s 5-year Writing Excellence Initiative (QEP), which sought to enhance the teaching and learning of academic, professional, and co-curricular writing for students, faculty, and staff. Her recent research focuses on the transfer of rhetorical knowledge and writing strategies between self-sponsored, academic, and professional contexts; the writing lives of alumni; reframing rhetorical theories and writing practices in multimodal environments; and Writing Center Fellows. She is currently co-leading Elon’s Writing Beyond the University multi-year, multi-institution research seminar.

Statement: I’m running for this position to support and connect colleagues across the country/world as they work to develop sustainable cultures of writing and infrastructures to support WAC on their own campus. I’m particularly interested in exploring/supporting what WAC means in the 21st century, as writing is increasingly visual, newer genres are emerging, and we’re learning more about writing transfer between academic and co-curricular, professional, and personal contexts. I see in this moment great opportunities for collaboratively designing multi-institutional faculty development and research projects, as a way to address these emerging issues and to continue supporting faculty, staff, and students/alumni.

Jacqueline Kauza

Bio: I earned my doctorate in Rhetoric, Composition, and Literacy from The Ohio State University in 2020. Currently, I am a Visiting Assistant Professor at Indiana University East. My areas of scholarly interest include WAC/WID, writing center theory and practice, and composition pedagogy. My current research builds on my WID dissertation, which explores history and social work instructors’ writing-related expectations for their undergraduate students. One of my primary research goals is to uncover trends, patterns, and complexities in the writing-related expectations for undergraduates in a variety of disciplines. I pursue this avenue of inquiry with the aim of making implicit disciplinary writing expectations more explicit for students. Ideally, this research can help to reduce inadvertent gatekeeping into academic communities and to promote more just and equitable pedagogy.

Statement: As an early-career scholar, I want to connect with and contribute to the broader WAC/WID community of practice. As a member at large, I would hope both to share new ideas with like-minded scholars, as well as learn from established figures in the field. There are several areas in which I would like to see WAC/WID work expand. First, I would like to foster more collaborative partnerships with faculty across the disciplines, involving disciplinary instructors more directly in shaping WAC/WID scholarship and practice. Second, I would like to promote more mentorship and support for graduate students interested in WAC/WID as an area of inquiry. Finally, I would like to enhance WAC/WID initiatives at the undergraduate level, exploring new avenues to promote undergraduate engagement in WAC/WID work and study.

Sherri Craig

Bio: Sherri Craig is an Assistant Professor of Professional and Technical Writing at West Chester University where she specializes in teaching diversity and inclusion through business and non-profit writing courses. Much of her research centers upon the experiences of Black women in their academic and industry careers and their professionalization and mentorship. As a student organization advisor and a diversity and inclusion consultant, Sherri enjoys sharing her knowledge with others and being inspired by those around her. Her work can be found in WPA: Writing Program Administration and at SparkActivism.com.

Statement: As the former Chair of the AWAC Advocacy Committee, I have spent the last two years engaged in many conversations with the DEI committee about the relationships between Advocating for and with our AWAC members and supporting the organization’s commitment to inclusion and equity. As the member-at-large for the committee, I would be able to bring these ever-important issues to the forefront of our actions in the WAC community. As the member-at-large, I am most interested in offering my support and experience with diversity and inclusion to help the chair and members of the DEI committee.

Doug Hesse

Bio: Doug Hesse is Professor and Executive Director of Writing at the University of Denver, where he’s been named University Distinguished Scholar. He’s a past president of NCTE, chair of CCCC, president of CWPA, and editor of Writing Program Administration. Starting at Illinois State in the late eighties, he directed a large writing program that included a WAC effort. His current role includes directing a writing intensive general education requirement that has involved some 250 faculty in three-day seminars, plus ongoing support. His 75+ articles/chapters focus on program development and leadership, writing pedagogy, creative nonfiction, and professional issues in writing studies.

Statement: In addition to ongoing work supporting writing-to-learn and writing in the disciplines, AWAC should encourage research, practices, and policies toward four challenges. We must better understand (1) how conditions for WAC will differ in post-pandemic institutions; (2) how increasingly multimodal-by-default texts are effectively and ethically produced and circulated; (3) how writers with diverse identities, pasts, and futures negotiate academic languages; (4) how WAC might better connect with discourse beyond the academy. Current events demonstrate why publics need information and ideas grounded in scientific, social, and humanistic knowledge. In addition to cognitive growth and epistemological savvy, WAC should foster writers for a world that surely needs expertise.

Crystal N. Fodrey

Bio: Crystal N. Fodrey is director of writing at Moravian College in Bethlehem, PA. Her recent scholarship on writing pedagogy and curriculum development has appeared in Across the Disciplines, Composition Forum, and Implementing Multimodal Curricula and Programs and is forthcoming in multiple edited collections on WEC, faculty development, and multimodal writing. In addition to leading first-year writing and WEC efforts at Moravian, she is currently working with colleagues to develop a conceptual framework for promoting digital multimodal teaching praxes across the disciplines and co-leading a team of undergraduate researchers in studying the role of multimodality across the curriculum.

Statement: As a leader in AWAC, I will strive to promote and embody rhetorical listening, reflection, and flexibility in order to understand and represent the diverse needs of writers, writing faculty, and WAC program administrators across myriad situational ecologies. My vision is for AWAC to expand our influence through strategic and effective communication and outreach efforts, promote faculty development that highlights inclusive assignment design and assessment practices, promote the possibility of both the WEC model and designing college curricula for vertical writing transfer, explore the roles of digital multimodal composing and media literacy in a WAC context, and celebrate innovative work.

Erika Scheurer

Bio: Beginning in 1993, I have been a member of the English department at the University of St. Thomas, serving first as Director of the interdisciplinary Academic Development Program for underprepared students (in which I still teach each year) and then, since its inception in 2009, serving as Director of Writing Across the Curriculum. With a supportive WAC Committee as well as Chris Anson as a mentor and guide, I have weathered the early years of program development. After a WPA Program Review in 2019, UST-WAC is now an established, growing part of our curriculum, and larger university culture.

Statement: As a Member-at-Large, my primary goal would be to make sure the needs of our members are met as they work to build, maintain, and grow their WAC programs during these challenging times. In order to achieve this goal, I would familiarize myself with the work of the AWAC committees and listen carefully to the needs expressed by our membership. As someone who has worked to build a WAC program over the past twelve years, I know how important it is to receive both practical and moral support; I will make sure our members receive these as well.