Generative Artificial Intelligence (hereafter referred to as GenAI) in broad terms refers to a branch of computer science that utilizes machine learning and other advanced algorithms to generate new content de novo. This content includes text, images, code, audio, and video, and is created from prompts or other user inputs. A point of interest is that the output produced by GenAI systems such as ChatGPT or Copilot is often indistinguishable from that of a human.

These guidelines have been developed by the Centre for Teaching and Learning (CTL) to support faculty in navigating the evolving role of generative AI (GenAI) in teaching and learning. They focus on pedagogical integrity, transparency, and student learning, while also acknowledging that effective guidance requires a shared understanding of the broader context in which these tools operate.

Because we cannot talk meaningfully about teaching with GenAI without first understanding what it is, its limitations, and its ethical, cultural, and pedagogical implications, these guidelines bring together background information, examples, and good practices. They aim to help faculty make informed, context-sensitive decisions that reflect the diversity of our community, the complexity of this emerging technology, and the need for ongoing reflection as the field continues to evolve. 

Rather than offering a single prescriptive approach, these guidelines serve as a living document, one that supports awareness, dialogue, and/or informed experimentation with GenAI in the classroom, while remaining responsive to new developments and institutional priorities.

• Faculty Interest Group on Teaching with GenAI: The Concordia University Teach with Generative AI (GenAI) Faculty Interest Group is a monthly gathering dedicated to exploring the potential applications, benefits, and challenges of integrating GenAI technologies into teaching practices. This group serves as a collaborative platform for faculty to share experiences, discuss innovative ideas, and engage in research related to the use of GenAI in various educational contexts.
  
• Workshops and events: CTL has been offering faculty development workshops
  
• Concordia Library resources:
  AI literacy page: A hub for AI literacy resources and guidance across campus.
  GenAI Quickstart: Foundations for Faculty: Nine short modules designed to build faculty confidence and foundational skills in teaching with generative AI.

• Student Success Center:
  Suggestions for using Generative AI in academic writing
  FutureBound initiative: Digital capabilities and mindsets: Offered through the Student Success Centre’s FutureBound program, this resource supports students in cultivating adaptable digital capabilities and reflective mindsets. 

A survey conducted by the CTL at Concordia University has shed light on faculty perceptions regarding GenAI integration. The survey, based on a well-established model (Technology Acceptance Model; Davis & Venkatesh, 2000), looked at what factors influence faculty's intention to use GenAI in their teaching. The results indicate that educators who believed GenAI would be useful for teaching and learning were more likely to plan on adopting it. However, concerns about academic integrity played a key role, with results from a hierarchical multiple regression revealing that faculty were less likely to use GenAI if they believed it would enable cheating or plagiarism. 

The survey revealed diverse faculty concerns regarding the pedagogical use of GenAI, including academic misconduct, diminished critical thinking, copyright infringement, data privacy, labour issues, environmental impact, and bias perpetuation. These wide-ranging issues highlight the complexity of integrating GenAI into education and emphasize the need for a comprehensive approach that transcends technical training, addressing both the pedagogical benefits and ethical challenges. 

All faculty are encouraged to clearly state their position on the use of GenAI in their courses. This should be stated clearly in the syllabus and should be discussed in class to ensure shared understanding. If you are working with a teaching assistant, review your course policy with them to ensure alignment when supporting instruction and grading. Whether you choose to allow, partially limit, or prohibit the use of GenAI, being explicit is important. 

Clear communication of expectations serves these purposes:

• Reduces ambiguity for students
  Course policies can vary widely, which can be confusing for students. A transparent statement eliminates uncertainty and helps them understand what is acceptable in your class. 

• Sets expectations for academic integrity
  By outlining boundaries and permissible uses of GenAI, faculty can connect their course policy to Concordia’s Academic Code of Conduct and prevent misunderstandings that might otherwise lead to misconduct.

• Builds students’ digital literacy skills
  Having open conversations about how and why GenAI may or may not be used helps students think critically about AI tools. It helps them recognize potential biases, limitations, and ethical concerns. 

• Supports equity and fairness
  When expectations are stated clearly, all students are working from the same starting point, reducing the likelihood that some learners gain an advantage through hidden or assumed practices. Research such as Eslami (2024) shows that transparent, inclusive syllabi can reduce confusion by making hidden norms visible.

Because each course has unique objectives and contexts, the CTL provides sample syllabus statements for different approaches: encouraged use, limited use, or prohibited use, that faculty can adapt. We also recommend linking course-level expectations with assignment-level guidance, since the role of GenAI may vary depending on the activity.

Syllabus statements for GenAI use (adapted from UManitoba)
Encouraged use:

• Students are encouraged to make use of technology, including generative artificial intelligence (GenAI) tools to contribute to their understanding of course materials.
• Students may use artificial intelligence tools, including generative AI, in this course as learning aids or to help produce assignments. However, students are ultimately accountable for the work they submit to be assessed and assigned grades.
• Students must submit, as an appendix with their assignments, any content produced by an artificial intelligence tool, and the prompt used to generate the content.
• Any content produced by an artificial intelligence tool must be cited appropriately. 
• Students may choose to use generative artificial intelligence (GenAI) tools as they work through the assignments in this course carefully. This use must be documented in an appendix for each assignment. The documentation should include what tool(s) was/were used, how the tool(s) was/were used, and how the result(s) from the 
• GenAI was/were incorporated into the submitted work.

Limited use:

• Students may use generative artificial intelligence (AI) tools for creating an outline for an assignment, but the final submitted assignment must be original work produced by the individual student alone.
• Students may not use artificial intelligence tools for taking tests, writing research papers, creating computer code, or completing major course assignments. However, these tools may be useful when gathering information from across sources and assimilating it for understanding.
• Students may not use artificial intelligence tools for taking tests in this course, but students may use generative artificial intelligence (GenAI) tools for other assignments.
• Students may use the following, and only these, generative artificial intelligence (GenAI) tools in completing their assignments for this course: [Insert list]. No other genAI technologies are allowed to be used for assessments in this course. If you have any question about the use of artificial intelligence applications for course work, please speak with the instructor.

Prohibited Use

• The use of generative artificial intelligence tools (GenAI) or apps for assignments in this course, including tools like ChatGPT and other AI writing or coding assistants, is prohibited.
• The knowing use of generative artificial intelligence (GenAI) tools, including ChatGPT and other AI writing and coding assistants, for the completion of, or to support the completion of, an examination, term test, assignment, or any other form of academic assessment, may be considered as academic misconduct in this course.
• Representing as one’s own an idea, or expression of an idea, that was AI-generated may be considered academic misconduct in this course.
• Students may not copy or paraphrase from any generative artificial intelligence (GenAI) applications, including ChatGPT and other AI writing and coding assistants, for the purpose of completing assignments in this course.
• The use of generative artificial intelligence (GenAI) tools and apps is strictly prohibited in all course assignments unless explicitly stated otherwise by the instructor in this course. This includes ChatGPT and other AI writing and coding assistants. Use of genAI in this course may be considered use of an unauthorized aid, which is a form of cheating. 

If you permit the use of genAI in your course or as part of an assignment, you may ask your students to disclose and document how they use genAI in their coursework. This includes identifying the tools they used, the prompts provided, and the outputs they integrated into their final submissions. Such documentation allows evaluation not only of the output but also the student’s process.

You can request this documentation in several formats, depending on the learning outcomes of the course:

• Appendices: Students attach the relevant AI outputs and prompts at the end of their assignment. This ensures that what was generated and how it was adapted is clear.
• Reflections: Students provide a short narrative explaining how they used GenAI, what limitations they encountered, and how they verified or revised the output. Reflection helps students develop digital literacy and awareness of bias, accuracy, and the ethical implications of genAI use.
  Citation practices: When AI outputs are directly quoted, paraphrased, or incorporated into a project, students should cite them in line with Concordia Library’s guidance on acknowledging AI, as well as with disciplinary citation styles (e.g., MLA, APA).

Requiring transparency statements helps strengthen accountability. Mentioned in Radwan & McGinty’s (2024) Generative AI Ethical Foundation Principles in Teacher Education (GENAIEF-TE), these statements can be implemented in two ways: 

• Educator transparency statements: Faculty share with students how they are using GenAI in course design, content creation, or assessment feedback. This models openness and sets the tone for ethical practice.
• Learner transparency statements: Students provide a short declaration at the start of the term or with their assignments, describing how they intend to use (or not use) GenAI. These statements serve as a document that encourages reflection throughout the course. 

Used together, these practices create a course culture of transparency and accountability. They also provide an alternative to unreliable AI detection tools, ensuring that students are learning how to use GenAI responsibly and critically while protecting privacy and academic integrity.

Data protection at Concordia, MS Copilot

If allowing or requiring the use of GenAI, protect instructor and students’ privacy and ensure secure data management, as well as consensual data collection and processing. Review Concordia’s Privacy and Protection of Personal Information Policies and allow students the option to opt out. Consult the Concordia Educational Technology Guidelines for Faculty and Students before using third party technology tools. At Concordia, all staff have access to Copilot Chat through an institutional Microsoft 365 license. Copilot Chat is available through this link. It requires authentication (using Concordia credentials) and it offers Enterprise Data Protection: encryption, privacy and access control, copyright protection and the protection against the usage of data to train foundation models. 

Academic integrity concerns

The use of GenAI can be framed within Concordia’s Academic Code of Conduct and broader standards for academic integrity. Relevant frameworks, such as the European Network for Academic Integrity (ENAI) recommendations and the International Center for Academic Integrity (ICAI) principles, emphasize honesty, trust, fairness, respect, responsibility, and courage. Applying these principles to GenAI means: 

• Encouraging students to be honest and clear about when and how they use AI tools.
• Ensuring fair treatment across courses by clearly communicating expectations. 
• Respecting intellectual property and avoiding plagiarism.

Detection Tools

At the moment, Concordia has not approved of or acquired the use of any online AI detectors and therefore the use of them by staff or faculty is not permitted due to privacy laws and regulations (see the University’s obligations concerning Privacy & Protection of Personal Information). To learn more about the University’s obligations when acquiring or using new software that could capture and/or share personal information contained in learner work, you may consult the Privacy Impact Assessment and for information about available resources, please consult the IITS Service Catalogue. 

Detection tools have proven to be: 

• Unreliable (false positives and negatives, Weber-Wulff et al., 2023).
• Inequitable (higher false positives for ESL and neurodivergent students, Gegg-Harrison & Quarterman, 2024; Rafiq et al., 2025).|
• Privacy violations (sharing student work with LLMs without consent). 
• Link to relevant academic integrity frameworks (ENAI, ICAI)

As genAI tools become more widespread, faculty should remain aware that these systems are not neutral. Because many models are trained on datasets that reflect systemic inequities, they often reproduce racial, cultural, and linguistic biases that disadvantage Indigenous and other culturally diverse communities. Educators can help students critically examine whose voices, perspectives, and forms of knowledge are represented, and whose are missing, in the outputs of AI systems.

Impact on Indigenous Communities

Within these broader equity concerns, particular attention must be given to Indigenous Peoples. AI models disregard representation of Indigenous languages, knowledge systems, and worldviews, which can result in bias, misrepresentation, or the use of Indigenous content without free, prior and informed consent.

For faculty, it’s important to be aware of these dynamics and consider the implications of GenAI for Indigenous sovereignty, cultural preservation, and data governance. Helpful resources include the UN’s statement on Indigenous Peoples’ Rights in the Age of AI as well as Concordia CTL’s Decolonization and Indigenization Hub. Integrating Indigenous perspectives into classroom discussions about AI can help ensure that students understand both the opportunities and the harms these technologies may bring.

Key Resources:

• ENAI Recommendations on AI in Education: European Network for Academic Integrity
  ICAI Fundamental Values of Academic Integrity: International Center for Academic Integrity
• UN: Ensuring Indigenous Peoples’ Rights in the Age of AI: United Nations DESA
• Concordia CTL Decolonization and Indigenization Hub: CTL Hub
• Concordia Library AI Literacy Resources: Library AI Help

As genAI tools are increasingly used in higher education, they hold significant limitations and risks that faculty should be aware of when making decisions about their use:

Bias
GenAI systems are trained on large datasets that may contain cultural, social, and linguistic biases. As a result, the outputs unintentionally reinforce stereotypes, omit some perspectives, or reflect predominantly Western views (Mak, Luo, 2025). Faculty and students should recognize that the outputs of large language models require inspection for equity and inclusivity.

Hallucinations
GenAI is known to generate text or other content that appears accurate but is fabricated or misleading. This includes non-existent citations, false summaries of academic concepts, or invented statistics (Currie, 2023). Such “hallucinations” present a risk if students do not verify the accuracy of outputs.

Cognitive Off-loading
Because GenAI can produce full drafts, summaries, or solutions to problems, there is a risk that students may over-rely on it rather than engaging deeply with the material. Recent studies indicate that frequent use of AI tools is associated with lowered critical thinking ability, especially when cognitive off-loading is high (Gerlich et al., 2025) (Chen et al., 2025).

Ethical Concerns (ethical use in teaching and learning)
Faculty play an important role in modeling responsible and transparent use of GenAI. This includes clarifying when and how AI tools may be used in coursework, encouraging citation or acknowledgment when appropriate, and fostering student reflection on academic integrity, fairness, and privacy in AI-assisted work.

Ethical issues in the technology itself
Beyond classroom use, GenAI raises broader ethical concerns about its global impact. The development and maintenance of large AI systems depend on significant environmental resources and often involve underpaid or precarious labour, including data annotators and content moderators who may face exploitative conditions. As well, questions of consent and ownership arise when AI models are trained on creative or cultural content without permission. Raising awareness of these systemic issues helps situate AI use within larger discussions of justice, sustainability, and human rights.