Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     27  Article  Ctrl+AI+Learn: Contextualizing Generative AI Policies for Incoming University Students Talla Enaya  University of Toronto Mississauga  Sarah Seeley  University of Toronto Mississauga  Abstract This teaching report describes a workshop delivered at the University of Toronto Mississauga as a  part of the Robert Gillespie Academic Skills Centre  s (RGASC) Head Start program, which introduces  incoming students to their new academic environment. The workshop was premised on two guiding  ideas:  (1)  since  the  University  of  Toronto  maintains  Hlexible  guidelines  regarding  generative  AI  policies across courses, undergraduate students beneHit from participation in candid discussions of  the contextual nature of shifting technological values and (2) Hirst-year university students are in the  unique  position  of  also  needing  to  contextualize  the  shift  from  high  school  to  university  learning  contexts,  so  they  are  in  particular  need  of  opportunities  to  discuss  the  diversity  of  perspectives  surrounding the permissibility of genAI use in higher education. The workshop led students through  noticing the differences between high school and university learning expectations; applying socially  oriented theories of communication; contextualizing   local   genAI syllabus policies; and crafting a  personal theory of acceptable genAI use. This report is a collaboration between an undergraduate  student (Enaya) and a writing professor (Seeley). To support educators in replicating or adapting this  exercise within their own local contexts, workshop materials are appended.   Introduction  In what follows, we describe a workshop delivered at the University of Toronto Mississauga (UTM) as  a part of the Robert Gillespie Academic Skills Centre  s (RGASC) Head Start program. This program is  meant to introduce incoming students to university-level expectations and share resources. Several   Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     28  students  working  at  the  RGASC  have  been  participating  in  research  on  and  otherwise  studying  generative AI technologies (genAI hereafter), and they were vocal about the value of including a genAI  session in the 2024 Head Start schedule. The session described below came out of that need and it  was  premised  on  two  guiding  ideas:  (1)  since  UTM  maintains  Hlexible  guidelines  regarding  genAI  policies across courses, undergraduate students beneHit from participation in candid discussions of  the contextual nature of technological values and (2) Hirst-year university students are in the unique  position of also needing to contextualize the shift from high school to university learning contexts, so  they are in particular need of opportunities to discuss the diversity of perspectives surrounding the  permissibility of genAI use in higher education.  The 75-minute workshop led students through the following activities: noticing the differences  between  high  school  and  university  learning  expectations;  applying  socially  oriented  theories  of  communication;  contextualizing    local    genAI  syllabus  policies;  and  crafting  a  personal  theory  of  acceptable  genAI  use.  This  workshop  had  four  learning  outcomes.  Following  the  session,  learners  should  have  been  able  to  (1)  notice  differences  between  high  school  and  university  learning  expectations,  (2)  begin  applying  discourse  community  theory  to  understand  their  educational  surroundings,  (3)  contextualize  genAI  syllabus  policies,  and  (4)  make  more  purposeful  decisions  about if and when to use genAI tools.   Primer: Comparing Learning Environments and Understanding Written Communication in Social Terms We began the workshop with the dual purpose of building rapport and co-constructing a baseline of  educational  experience.  To  do  this,  we  posed  a  cluster  of  open-ended  questions  for  participants    reHlection: What kinds of tasks were you assigned in high school? Were people using genAI tools? For  what purpose? These questions helped with building rapport because the Hirst one is value free and  the second two are disconnected from the self in that they ask participants to describe their peers    actions, not necessarily their own. This allowed us to generate conversation and create a basis for  comparing how university-level values and expectations differ from those of high school.  Moving forward, student contributions provided a framing for a mini-lecture on John Swales  s  discourse community framework (developed 1990; elaborated 2017). We selected this theoretical  framework in lieu of others (e.g., communities of practice or activity theory) because most students  on our particular campus enrol in a Hirst-year writing class wherein they craft a discourse community   Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     29  analysis.  As  such,  this  seemed  like  a  good  opportunity  to  build  synergy  between  the  Head  Start  program  and  the  curricular  experiences  its  participants  were  soon  to  encounter.  That  said,  any  of  these  theories  could  serve  the  same  purpose.  The  workshop  offered  a  mini-lecture  focusing  on  Swales  s suggestion that a discourse community (DC) can be understood in terms of eight criteria,  which we paraphrase here (2017, para. 19,   Reconsidering DC criteria  ):  (1) general goals  (2) means for intercommunication  (3) various participatory structures  (4) communicative genres   (5) speciHic vocabulary  (6) a core group of experienced members  (7) a sense that certain things can be left unsaid  (8) social rhythms, histories, and values  Swales  s  ideas  provided  a  framing  for  the  following  observations:  communication  practices  always  change  as  we  move  between  social  contexts  (e.g.,  work  vs.  school);  frames  like  discourse  community theory are tools for understanding new contexts (e.g., university); expectations, goals,  and values, will change and, in so doing, cause   ripple effects   (e.g., current and emergent responses  to genAI); large scale changes take time to   settle,   and this is an unsettled historical moment. Finally,  we observed that the foregoing phenomena are typically negotiated dialogically  and it  s weird when  they  re not! This is to say that, the proliferation of genAI tools has not only made the contemporary  moment  feel    unsettled,    but  this  unsettled  feeling  is  particularly  weird  because  there  is  so  much  silence  around  it.  Increased  discussion  of  technopedagogical  values  may  not    settle    things,  but  increased dialogic negotiation amongst learners and educators may ease the weirdness.   This  mini-lecture  primed  students  to  begin  to  imagine  university  as  a  set  of  overlapping  disciplinary  discourse  communities  with  their  own  unique  expectations,  issues,  debates,  uses  of  language, and, most importantly, technological values. It also opened the door to imagining genAI use  in higher education as a dynamic phenomenon with its own evolution and contextual histories, and  it foregrounded the need for candid and sustained conversations around this topic.         Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     30     Group Activity: Discussing Conflicting GenAI Policies Following the mini-lecture, we engaged students in a group activity. In preparation for the workshop,  we conducted a search for genAI policies within UTM  s syllabus archive and analyzed 80 syllabi across  30 departments from Fall 2024. We tracked whether each document contained a genAI policy and  whether the use of genAI was deemed permissible (see Section 5 below for additional details and  discussion).  This  exercise  illustrated  how  much  inconsistency  exists  within  the  syllabus  archive,  which  is  not  surprising  given  the  relative  newness  and  continuous  evolution  of  genAI  as  well  as  instructors    various  social  and  disciplinary  responses  to  these  technologies.  This  inconsistency  is  surely not unique to a single institutional context, and it highlights the need for communication and  transparency between students and instructors regarding the use of genAI.  The activity asked students to form small groups and skim a handout listing 15 syllabus policies  from classes across the disciplines. From there, the groups were asked to identify 1-2 policies from  disciplines of interest to them and 1-2 statements from totally different kinds of disciplines. From  there, the groups were asked to engage with these questions:     Are all the statements clear? Are there points of confusion?      What social values are the statements based on? Is it clear? Unclear?      How could you use genAI tools in the context of these speciHic classes?      Do permissible uses mesh with your educational goals and values?   Given the large format of this workshop (50-70 students in attendance), most of the conversation  needed to occur within the small groups, not across the group as a whole. Nevertheless, we will now  convey a few (paraphrased) observations that came from this portion of the exercise.  One  group  discussed  the  fact  that  policies  may  apply  to  other,  less  commonly  known  or  understood  AI  tools  (e.g.,  tools  beyond  ChatGPT  may  be  banned;  Grammarly  may  be  included  explicitly in this ban). While discussing a policy from a course with a strict ban, another group agreed  that genAI use in this class wouldn  t be consistent with their values or goals because they  d want to   master  the  subject  matter  themselves1.  Some  students  noted  how  they  appreciated  policies  that  offered examples of when genAI use is  and is not  permissible. They found this to be transparent  and  realistic.  They  generally  wished  there  was  more  speciHicity  and  clarity  across  the  15  sample   Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     31  policies examined. One student noted a policy that struck them as   sensible.   They discussed how the  class allowed for the use of genAI to help with understanding the course material, but not with the  completion of course assessments. This is where many students described   drawing the line   in their  own technological practices. We will turn to the issue of how students may develop such personal  discernments and ethical stances in the next section.   Independent Writing: Crafting a Theory of Acceptable GenAI Use The Hinal component of this workshop gave students space for independent writing. Again, thinking  of the fact that many of the workshop attendees would soon enrol in our Hirst-year writing course, the  reHlective writing component we  re about to describe mirrors an assignment from that class. Here,  we asked students to build on all the ideas we  d been discussing in order to start articulating a theory  of acceptable genAI use. The students were reminded that theories explain and predict the world, and  they are constantly evolving. As such, they were instructed to keep in mind that the   theory   they  started developing that day would  and MUST  evolve as they experienced new university contexts  and gained new knowledge. Within this context the students were asked to draft a statement that  accounted for anticipated genAI use in terms of their personal goals, disciplinary values, and their  understandings of academic integrity. Please see Appendix 1 for a complete prompt.    Discussion: The Archived Syllabi While some syllabi list policies that go in depth about the impacts of misusing genAI, others omit the  mention of genAI altogether Of the thirty programs whose syllabi we sampled, only one maintained  a consistent policy, with identical wording and permissibility. In contrast, of those same 30 programs,  two had no mention of AI in their documents. Nevertheless, students   use of genAI in university is  inevitable, and we suggest that guidelines must be explicitly (and regularly) addressed by professors  to ensure responsible and effective usage.     In  our  analysis,  we  also  tracked  methods  of  assessment.  However,  we  found  no  correlation  between the method of assessment and the question of genAI permissibility. For instance, two syllabi  from  the  same  program  prohibited  the  use  of  genAI  despite  having  contrasting  methods  of  assessment. One of these courses assessed students through tests and exams, while the other used  essays,  projects,  and  presentations.  Syllabi  from  other  programs  that  assessed  students  in  similar  ways also revealed no correlation between the form of assessment and the permissibility of genAI.  This lack of cohesion was observable within programs, between professors, and even across courses   Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     32  with the same professor. For instance, one program offers a Hirst-year course with a genAI policy, yet  the syllabus for a second-year course taught by the same professor has no mention of genAI, despite  both courses being mounted in the same department and assessing students through similar means.   Syllabi  from  six  programs  included  detailed  policies  with  clear  guidelines  and  realistic  expectations. We describe the policies as clear and realistic because they include speciHic examples of  prompts  and  scenarios  that  model  appropriate  genAI  use  within  the  speciHic  course  context.  Additionally,  the  policies  explain  how  using  genAI  unethically  can  negatively  impact  students    learning.  For  example,  one  syllabus  describes  how  the  course  is  structured  to  help  students  build  strong research and writing capabilities, which involves prioritizing originality and creativity. It goes  on  to  discuss  originality  in  terms  of  mistakes  and  discoveries.  It  closes  by  noting  that  genAI  use  forecloses on this kind of processual intellectual development.   In  contrast,  some  instructors  have  begun  integrating  genAI  into  their  existing  assignments  for  their 2024-2025 courses. For instance, one course asks students to prompt ChatGPT to formulate an  essay, analyze its biases, and then form their own essay that exceeds the quality of the AI-generated  version.  This  activity  encourages  critical  reHlection  on  the  quality  and  reliability  of  genAI  outputs,  while also ensuring that submitted work cannot be identical to a genAI response. We also noticed that  in courses where genAI is permitted, students are often required to include additional citations or  metacognitive  reports  explaining  how  and  why  they  used  the  technology.  A  few  policies  also  discussed alternative sources for   help   beyond genAI, including ofHice hours and campus resources,  such as the RGASC. We suggest that each of these approaches offer nice models and/or starting points  for  using  the  syllabus  as  a  space  for  setting  realistic  expectations  and  fostering  a  communicative  classroom environment.   Impressions &amp; Conclusions We  ve  described  here  a  workshop  offered  as  a  part  of  the  Head  Start  program  at  UTM  which  introduces incoming students to their new academic environment. Because we  re reporting on oneshot  instruction,  we  cannot,  for  example,  comment  on  students    learning  in  or  experience  of  the  session.  That  said,  we  envision  this  set  of  activities  as  adaptable  and  replicable  across  classroom  contexts,  wherein  educators  would  have  access  to  more  speciHic  details  and  feedback  regarding  student learning.   Whether it takes place in a one-off workshop or across a series of class meetings within a course,  there is value in the transparent discussions of genAI any educational context. As we seek to help   Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     33  students progress in their academic and professional careers, learning how to effectively utilize genAI  tools can be greatly beneHicial. This is especially true in Hirst-year contexts, since genAI tools are an  emergent  part  of  an  educational  landscape that is itself new for incoming and Hirst-year students.  These inconsistencies can cause high stakes confusion for students, and they signal the need for open,  sustained  conversations  between  students,  TAs,  professors,  departments,  and  administrators.  Additionally, strictly prohibiting the use of genAI might prompt students to seek loopholes and resort  to  unethical  practices,  rather  than  openly  developing  new  skills  in  collaboration  with  their  instructors.  Experimenting  with  genAI  tools  encourages  students  to  enhance  valuable  skills,  including evaluative judgement and rhetorical load sharing. Fostering an open and communicative  environment is a signiHicant step in encouraging students to share their experiences as we learn to  navigate signiHicant, emerging technologies.   Endnotes 1. Please note the selection bias here. The Head Start program often draws keen students, and this  is  an  anecdotal  report  of  a  group  conversation  led  by  a  professor,  so  there  is  a  likelihood  of  students engaging in   teacher pleasing.    References Swales,  John  M.  (2017).    The  concept  of  discourse  community:  Some  recent  personal  history.    Composition Forum, 37, https://compositionforum.com/issue/37/swales-retrospective.php   Swales,  John  M.  (1990). Genre  analysis:  English  in  academic  and  research  settings.  Cambridge  University Press.   Appendix 1   Crafting a Theory of Acceptable GenAI Use   (a student-facing prompt)  Theories explain and predict the world, and they are constantly evolving and changing. The   theory    you start developing today will  and MUST  change as your university context grows, as you have  time to experience new things and gain new knowledge.   Your theory of acceptable genAI use should first account for your personal goals. What do you  want out of university? What kind of knowledge do you hope to gain? What goals will this degree   Discourse and Writing/Rédactologie  Volume 35, 2025  http://journals.sfu.ca/dwr     34  help you achieve? Where do you see yourself having moments of struggle in achieving these goals?  (It happens for everyone!)   It should also account for disciplinary values. You are only just starting the process of becoming  a professional in your field, so your knowledge here is limited. But what values do you see reflected  in the syllabus statements we reviewed? Does your intended field seem to embrace genAI tools? Can  you tell why/not based on the syllabus statement? What more do you need to learn in this regard?    Finally,  your  theory  should  demonstrate  a  strong  understanding  of  academic  integrity  expectations. Sometimes the use of genAI tools is permissible from an academic integrity standpoint,  but does that mean you think it  s ethical and/or good for your learning process?  In other cases, genAI  tools are banned altogether, which means you may need to change your workflow from class-to-class.  How do you plan to deal with these shifting expectations?

## Références

Swales, John M. (2017). “The concept of discourse community: Some recent personal history.” Composition Forum, 37, https://compositionforum.com/issue/37/swales-retrospective.php

Swales, John M. (1990). Genre analysis: English in academic and research settings. Cambridge University Press.