Artificial Intelligence
Artificial Intelligence (AI):
As artificial intelligence transforms how we learn, teach, and work, grasping its core concepts, ethics, and practical applications is vital. Here, you'll find best practices, guidelines, and resources to help you navigate AI responsibly.
Developing an AI Policy for your Class:
AI tools such as Google Gemini, Microsoft Copilot, Grammarly, and other GenAI technologies can be valuable resources for learning when used appropriately. Instructors should carefully consider the role AI will play in their classroom. Developing a clear syllabus statement addressing AI, labeling appropriate AI use for assignments, and discussing AI use with students early in class can help create clear expectations and less confusion among students.
The AI Assessment Scale (AIAS), is an adaptable communication tool that can help educators articulate expectations to students, and it is a design framework that guides redesign of assessments for the AI era.
There are Five Levels of the AIAS:
- Level 1: No AI - This task is completed in a controlled environment designed to exclude AI. Knowledge, understanding, and skills are demonstrated and assessed independently.
- Level 2: AI Planning - This task focuses on planning activities such as topic exploration, outlining, and initial research. AI may be used to support this process, and the quality of planning and idea development is assessed whether or not AI was used.
- Level 3: AI Collaboration - AI may be used to help complete this task, including idea generation, drafting, feedback, and refinement. It is designed so that AI alone will not reach the required standard. Assessment covers both the work itself and how AI outputs are evaluated, modified, an integrated.
- Level 4: Full AI - There is an expectation of AI involvement in this task. The goal cannot be reached by AI or by a person working alone in the time available. Assessment focuses on the critical thinking and subject knowledge shown in directing AI.
- Level 5: AI Exploration - This task is designed for creative AI use to solve problems, generate novel insights, or develop innovative solutions in the discipline. Approaches may be co-designed by students and instructors.
Ideas how to Incorporate into your Course and Assignments:
- Assignment Instructions : At the very top of your Canvas Assignment instructions, add a clear header: “AI ASSESSMENT LEVEL: 2 (Planning Only) - You may use AI for brainstorming and outlining. Your final submission must be your own original writing.
- Rubric: Add a non-graded criterion to your Canvas Rubric called AI Transparency. Use it to confirm that students have disclosed their AI use according to the level you set.
- Simple Syllabus: Define Your "Default" Level: State which level of the AI Assessment Scale applies to the majority of your course (e.g., "This course defaults to Level 2 (describe level 2), unless otherwise specified on the assignment page.
No Generative AI Use:
Generative AI tools are not permitted in this course. All work submitted must be your own, produced without the assistance of AI writing, coding, or image-generation tools. This includes but is not limited to ChatGPT, Claude, Gemini, Copilot, Grammarly's AI features, and similar technologies.
This policy exists because the learning objectives of this course are built around the development of your own skills in critical thinking, writing, and problem-solving competencies that require genuine practice without AI usage. Submitting work generated or substantially revised by AI will be treated as academic dishonesty and subject to institutional academic integrity policies.
Conditional Generative AI Use:
Generative AI tools may be used in this course only for the specific purposes and assignments designated by the instructor. Each assignment will be clearly marked as "AI-permitted," "AI-assisted," or "AI-prohibited." Using AI in ways not explicitly authorized for a given assignment is a violation of academic integrity policy.
When AI use is permitted, you must document your process: identify the tool used, describe how you used it, and explain the revisions or decisions you made independently. This documentation helps you develop awareness of AI's capabilities and limitations, and ensures that your own learning and voice remain central to your work.
Full Generative AI Use Permitted:
Generative AI tools (such as ChatGPT, Claude, Gemini, Copilot, and similar) are permitted and encouraged in this course. You may use these tools to assist with brainstorming, drafting, editing, coding, research, and other tasks unless a specific assignment explicitly states otherwise.
However, AI use does not replace your responsibility for the quality and integrity of your submitted work. You are expected to critically evaluate all AI-generated content, correct errors, and ensure your submissions reflect your own understanding and judgment. When AI tools contribute meaningfully to your work, you must disclose this by noting which tool(s) you used and how. Submitting AI-generated content as your own without disclosure constitutes academic dishonesty.
Example 1: AI is NOT permitted. The use of artificial intelligence tools, including ChatGPT and other generative AI platforms, is not permitted for this assignment. This Weekly Writing assignment must represent your own thinking and writing. Write what you think. Ask the questions you genuinely have. The goal is thoughtful engagement.
Example 2: Since this is a research assignment, you may use AI tools for your research to find reliable sources. If you do, include your initial prompt, how AI helped you research, specific resources you might not have found otherwise, and what you learned about using AI for this assignment. If you do not use AI, describe what you learned about research using the tools you did.
Example 3: You are required to use AI in your research for this assignment. In addition to your research paper, you should include which AI tool you used, your initial prompt, how your conversation went, and what you learned about using AI for this assignment.
Guidelines for Sharing Information with AI
Information that should not be shared with AI:
Type of information | Examples | Risk |
| Personal identifiable Information (PII) | names, addresses, phone numbers, social security number, etc. | Could lead to identity theft or unauthorized access |
| Medical and health information | patient records, diagnoses, prescriptions, medical history | Could lead to financial fraud |
| Financial information | bank account information, credit card numbers, tax information | Could lead to being non-compliant with HIPAA regulations |
| Student records and academic data | grades, transcripts, disciplinary records, admission information | Could lead to being non-compliant with FERPA regulations |
| Intellectual property | creative works such as art or writing | AI tools may use your work to further train without explicit permission, repurpose it in ways you don't intend, or expose it to others without consent. |
AI Terminology:
Artificial intelligence (AI): Computer systems that can perform tasks with human-like intelligence, such as understanding language, recognizing images, learning from data, reasoning, and making decisions.
AI Literacy: The ability to understand, critically evaluate, and collaborate effectively with generative AI in a manner that is ethical and socially and academically responsible.
Machine Learning: A branch of AI where algorithms learn from data to make predictions or decisions from patterns in the data without being explicitly programmed for every scenario
Generative Artificial Learning (GenAI): A type of AI that creates new content, such as text, images, audio, video or code based on patterns learned from training data.
Large Language Models (LLMs): A type of AI trained on vast amounts of textual data to understand, summarize, generate, and converse in natural human language (i.e ChatGPT, Claude, Gemini).
Agentic AI: AI systems that operate autonomously with the ability to plan, make decisions, and take action in the world to achieve goals, often with minimal human intervention.
Prompt Engineering: The practice of crafting clear, structured instructions (prompts) to direct AI tools toward desired outputs.
AI Hallucinations: Instances where an AI model generates false, fabricated, or misleading information while presenting it as if it were factual.
Additional Resources
References
The AI assessment scale. (n.d.). The AI Assessment Scale. https://aiassessmentscale.com/