AI enhances learning and institutional efficiency by providing personalized learning experiences, automating administrative tasks, and transforming assessment methods.

It has the potential to adapt coursework to meet individual student needs, boosting engagement and outcomes (Liu & Bates, 2025). AI can also streamline administrative functions such as grading and scheduling, freeing educators to focus on teaching (Pratschke, 2024).

Moreover, AI supports competency-based assessments that measure deeper learning and move beyond traditional exams (TEQSA, 2024).

This external resource is not affiliated with SMU policy. It is provided for reference and broader context.

Generative AI tools—like ChatGPT, Microsoft Copilot, Gemini, or Claude—can help make your work more efficient and creative. Here are some practical ways faculty and staff can benefit:

For Faculty:

• Save time on planning: AI can help draft lesson plans, create quizzes, or suggest learning activities.
• Give better feedback: AI tools can help you provide personalized comments on student work.
• Design better courses: Use AI to brainstorm new teaching ideas, examples, or ways to explain difficult topics.
• Support diverse learners: AI can help create accessible materials for students with different needs or learning styles.

For Staff:

• Speed up admin tasks: Draft emails, reports, or meeting summaries quickly.
• Help with data: Use AI to analyze data for student support, scheduling, or operations.
• Improve communication: Create clearer messages and FAQs for students or staff.
• Brainstorm solutions: Use AI as a creative partner to solve everyday challenges.

Why Use It?

• It saves time and reduces repetitive work.
• It opens up space for more creative and meaningful tasks.
• It can improve the quality of teaching and support services.

Getting started can be as simple as trying out a tool or exploring how it could support your daily work.

Remember: Always use generative AI tools ethically and responsibly, and in line with SMU’s guidelines on academic integrity and data privacy.

Universities are implementing various strategies to integrate AI while upholding academic integrity.

Many are launching AI literacy programs to educate students and faculty on ethical and effective AI usage (Russell Group, 2024). Institutions are also developing clear policies on AI use in coursework and research to establish guidelines and best practices (U15 Canada, 2024).

Furthermore, universities are rethinking traditional assessments by introducing innovative evaluation methods that emphasize critical thinking and problem-solving over rote memorization (TEQSA, 2024).

This external resource is not affiliated with SMU policy. It is provided for reference and broader context.

The following draft guidelines, created by the Joint Subcommittee of Academic Integrity, which consists of student representatives, faculty, and staff, are meant to help faculty make informed decisions about the allowed use of generative artificial intelligence in their courses and communicate their policy to their students.

These guidelines are a living document. Feedback is welcomed and encouraged.

SMU Faculty Guidelines on the Use of Generative AI in Courses (Draft)

To provide feedback on these draft guidelines, please email Academic.Regulations@smu.ca.

Use of generative AI in your teaching and assessment design should be ethical, intentional, and support student learning while maintaining academic integrity. Below are some key questions to consider:

1. Are your AI usage policies clear and aligned with institutional guidelines?
   • Have you communicated specific rules on AI use for your course, unit, or assessments?
   • Do students understand the permitted and prohibited ways they can engage with AI?
2. How should students document their use of generative AI?
   • Are you encouraging students to track and reflect on how they use AI in their learning process?
   • Should students include an AI usage statement in their assignments?
3. How can you ensure that student work remains authentic and not overly reliant on AI?
   • Have you designed assignments that require original thought, critical analysis, and process-based engagement?
   • Are there clear expectations on how AI-generated content should be used, cited, or modified?
4. How can you help students develop critical thinking when working with AI-generated content?
   • Are students being taught to evaluate AI outputs using disciplinary knowledge and academic rigor?
   • Do students understand AI’s limitations and the risks of misinformation?
5. How can you mitigate biases in generative AI tools?
   • Are students aware of how AI models can reinforce societal biases in their responses?
   • Have you provided strategies for cross-checking AI-generated information with reliable academic sources?

This resource was created by Lance Eaton for the purposes of sharing and helping other instructors see the range of policies available by other educators to help in the development of their own for navigating AI-Generative Tools (such as ChatGPT, MidJourney, Dall-E, etc.).

View Document: Syllabi Policies for AI Generative Tools

This external resource is not affiliated with SMU policy. It is provided for reference and broader context.

Despite its benefits, AI in education presents several challenges. Bias and fairness concerns arise as AI models may reflect societal biases from their training data, potentially affecting equitable outcomes (Russell Group, 2024).

Academic integrity is another issue, with AI-generated content raising concerns about plagiarism and the authenticity of student work (U15 Canada, 2024).

While on one hand, AI has been described as a way of democratizing education, the digital divide remains a significant challenge, as unequal access to AI tools may widen gaps in learning opportunities (Liu & Bates, 2025).

Privacy and ethical concerns also persist, requiring institutions to ensure responsible data use and compliance with ethical guidelines (Russell Group, 2024).

This external resource is not affiliated with SMU policy. It is provided for reference and broader context.

Why We Don’t Recommend AI Detectors for Student Work

AI detection tools may seem like a simple way to check if a student used generative AI—but they don’t actually work very well. Here’s what you need to know:

1. They’re unreliable. AI detectors frequently make mistakes in both directions. They may flag original student work as AI-generated, and they can fail to catch work that was heavily AI-assisted. Even small rewordings or paraphrasing can fool these tools.
2. They’re biased. Studies have shown that AI detectors are more likely to falsely accuse students who are non-native English speakers, have disabilities, or come from under-resourced backgrounds. This raises serious equity and inclusion concerns.
3. They damage trust. Using AI detectors creates an environment of suspicion. Instead of fostering open conversations about learning and digital literacy, they can lead to punitive responses based on flawed technology.
4. There are better approaches. Research suggests moving away from policing and toward thoughtful assessment design, open dialogue, and teaching students how to use AI responsibly and ethically.

Bottom line: We advise faculty not to rely on AI detection software. Instead, let’s focus on meaningful learning, transparent communication, and inclusive academic integrity practices.

A Note on Privacy and AI Detectors

Faculty are strongly discouraged from uploading student work to AI detection tools. Here's why:

• Privacy Risks: Uploading student assignments to third-party AI detectors may violate privacy policies or laws, especially if the platforms collect, store, or reuse the data for training AI models. This could breach your institution’s academic and data governance rules.
• Consent Concerns: Students are often unaware their work is being used in this way. Using their intellectual property without consent can undermine trust and contravene academic ethics.
• Legal Uncertainty: Many AI detection tools operate in legal grey areas when it comes to how they handle uploaded content. Faculty are advised to consult with your university’s Privacy Office or legal counsel before using these tools.
• Better Alternatives Exist: If academic misconduct is suspected, a more educational and fair approach involves open conversations with students, transparent course policies, and thoughtfully designed assessments.

Remember: AI detection tools are not only unreliable—they can also raise serious ethical and legal issues when used carelessly.

Generative AI tools—like ChatGPT, Copilot, or Claude—can help you learn more efficiently, stay organized, and express your ideas more clearly. Here are some practical ways students can benefit:

For Learning:

• Understand difficult topics: Ask AI to explain concepts in simple terms or give examples.
• Get study help: Use AI to summarize readings, quiz you on key points, or create flashcards.
• Improve writing: Get help brainstorming ideas, checking grammar, or refining your drafts.

For Organizing Your Work:

• Plan assignments: Break big tasks into steps and create timelines.
• Draft emails or resumes: Write more clearly and professionally with AI suggestions.
• Take better notes: Use AI to summarize class materials or meeting notes.

For Creative Projects:

• Explore new ideas: Brainstorm stories, presentations, or project themes.
• Get feedback: Use AI as a sounding board to improve your work or spot errors.

Why Use It?

• It helps you study smarter, not harder.
• It can boost your confidence in writing and communication.
• It’s like having a digital assistant that’s available 24/7.

Please remember: Always use generative AI tools ethically and responsibly and follow SMU’s guidelines on academic integrity and fair use. If you're unsure, ask your instructor or refer to the course outline.

This flowchart provides guidance for students at SMU on how to properly acknowledge and cite the use of generative AI in coursework, based on institutional expectations.

Usage Instructions:

1. Begin at the top of the chart and follow the arrows according to the relevant use case.

Key Decision Points Include:

• Whether generative AI use is permitted in the course (as outlined in course materials).
• The type of AI tools being used (standalone vs. embedded).
• The nature of the AI use (e.g., content generation, editing, or support).

Additional Considerations:

• Course-specific policies may vary; always refer to the course outline.
• When unsure, consult with the instructor or default to acknowledgment and citation.
• Citation formats and additional resources are available in the Patrick Power Library’s AI Guide.

General Principles:

• AI-generated content used directly in assignments generally requires citation.
• Use of AI for learning or editing support may also require acknowledgment.
• Embedded tools (e.g., grammar checkers) may fall under different citation policies.

These guidelines aim to promote transparency and uphold academic integrity in the use of AI technologies in academic work.

Visual Flowchart:

(Created with LucidChart)