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student guide to AI

Bellevue University’s stance on AI

AI tools are an emerging technology and using them well is a skill worth developing. The University embraces new technologies and expects students, faculty, and staff to use them responsibly. 

We acknowledge that this is an evolving territory. The University commits to ongoing support and training as AI tools and norms continue to develop. 

 

know the rules and understand the tools

Is generative AI allowed?

Policies will be different from program to program, course to course, and even assignment to assignment, so always take the time to find out 1) if using generative AI is allowed, and 2) how using generative AI is allowed.

  • Check the syllabus for guidance.
  • Check assignment instructions for guidance.
  • If you aren’t sure, ask your instructor!
If generative AI is allowed, use it responsibly.
  • Follow all assignment instructions and ask questions. Make sure you follow instructions for how AI usage is allowed.
  • Learn about a generative AI tool before you use it.
  • Consider what you are learning and how generative AI can support your learning process.
  • Evaluate and verify any material created using generative AI. Remember, you are accountable for what you include in your assignments. The Personal Librarian Program can help you build skills to evaluate information.
  • Be transparent about your use of generative AI and include attribution. The Writing Center can help you create citations. You are accountable to PS 1901 Student Code of Conduct.
  • Keep your focus on your learning. Can you explain all concepts and topics without the use of generative AI?

Care and Trust: using AI responsibly

CARE is a way to create AI prompts.  
TRUST is a way to evaluate AI output. 

 

The CARE Framework for Building Prompts 

AI is only as useful as the instructions you give it. Some people find conversing with AI tools, having a back-and-forth exchange, useful for how they work. Others, looking to save time, may choose to develop prompts. Prompts provide AI tools with a lot of information up front so that fewer back-and-forth exchanges are needed.  

The CARE framework is one way to build a strong prompt: Context, Action, Role, and Expectations.  

Context provides the situational details that guide the response. This may include key information (e.g., background, history, examples, format.) that helps the AI generate a more accurate and relevant output. 

Action defines what the AI should produce. Clearly stating the task (e.g., suggesting draft revisions or developing a PowerPoint slide) ensures the output matches your objective. 

Role defines who the AI should act as or write for. Specifying a role helps shape tone, perspective, and level of expertise so the output aligns with your intended audience.  

Expectations clarify how the output should be structured or delivered. This includes tone, length, format, criteria, constraints, or any specific standards the response should meet. 

The TRUST framework for valuating AI output

Evaluating your AI-generated output is another way of acting responsibly when using AI and taking ownership over your work. 

Anytime you use AI, you should always validate the output. Even a well-written prompt can lead to an AI response that includes mistakes, missing information, or ideas that do not fully fit your situation. Because of this, AI output should always be reviewed carefully before being used in college (and beyond).  

The TRUST framework offers a clear way to evaluate AI-generated content before using it: True, Relevant, Useful, Sound, Thoughtful. 

True. Is this actually accurate? Can I verify these claims with another source? 

Relevant. Does this actually answer what I asked? Is the output connected to my information need? 

Useful. If the output is relevant, is it also useful? Does this move me forward or just fill space?  

Sound. Is the reasoning logical? Could I explain and defend this thinking in class? 

Thoughtful. Is this fair and balanced? Could this get me in trouble academically, professionally, or personally? 

AI tools available through Bellevue University

BU has identified a set of AI tools that are available for you to use as a student. These tools have been reviewed and approved by the university, so when your courses allow it, you can feel confident using them for your coursework.  

Microsoft Copilot 

Microsoft Copilot has been chosen by Bellevue University as our school’s AI assistant, meaning the work you do with this tool, when using it through your BU access, is secure, private, and won’t be used to train larger AI models for Microsoft.  

  • To access Copilot, sign in via Bruin Connect and select Microsoft 365.  
Grammarly 
  • Grammarly Premium with Generative AI & Authorship (Sign in required via Bruin Connect) 
Turnitin Draft Coach 

Turnitin Draft Coach is an integrated writing tool for Microsoft Word Online that provides Bellevue University students with instant feedback to improve writing, research, and citation skills before submitting an assignment.  

Turnitin Draft Coach can run checks for similarity and citations to help you provide attribution and avoid plagiarism.  

Learn more about Turnitin Draft Coach and how to use it to help you revise and refine your work with confidence. 

AI Conversations in Blackboard 

AI Conversation is an interactive learning activity built directly into Blackboard that allows students to have a guided chat with an AI-powered persona created for a course. Microsoft Azure powers these conversations, and all data generated remains secure within your course site and is not used to train the underlying AI system. 

Two types of AI Conversations could be built into courses. 

  • Socratic Questioning. The AI persona encourages students to think critically through continuous questioning. This type is designed to help students examine assumptions, explore different perspectives, and deepen understanding of a topic. 
  • Role-Play. Role-play scenarios give students a chance to practice important communication, decision-making, and problem-solving skills in a safe setting. Role-play situations are explained before students start conversations. 

After an AI conversation, students are asked to complete brief reflections or answer questions.  

Note: Like all AI tools, this system can sometimes produce responses that are inaccurate or biased. The tool will include this reminder as well. Think critically and always validate responses.

AI and career development

How are the industries you’re interested in using AI, and which tools, trends, and skills will best support your long-term career goals? How can you prioritize building transferable skills, such as data literacy, critical thinking, and communication, that will remain valuable as AI continues to evolve? The resources below can help you build these skills and apply them effectively in your career development. 

 

Common AI terminology

The following common terminology is organized conceptually instead of alphabetically so that when read in order, you build an understanding of how the terms fit together. 

 Traditional AI: Traditional AI relies on explicit rules written by humans (like spam filters) instead of generating new content. It has been in use since the 1950s. It involves rules, logic, and is trained on specific data. In order for these AI systems to work, humans need to explicitly program the rules. 

 Artificial Intelligence (AI): A broad field of computer science focused on building systems that can perform tasks that typically require human intelligence, such as understanding language, recognizing patterns, and making decisions. 

 Machine Learning (ML): ML allows computers to learn from data. ML is the mechanism underneath AI tools. 

Natural Language Processing (NLP): NLP helps computers understand, interpret, and generate human language. NLP is what enables LLMs to work. 

 Large Language Model (LLM): LLM is a type of GenAI tool trained on vast amounts of text to understand and generate human-like language. It can answer questions, write text, summarize information, and assist with many language-based tasks. LLMs power many tools such as Copilot (your BU AI tool), ChatGPT, Claude, and Gemini. You may also hear the term GPT (Generative Pre-trained Transformer); this refers to the specific architecture behind Copilot and ChatGPT, but other LLMs, including Claude and Gemini, use different architectures to achieve similar results. 

 Generative AI (GenAI): These AI software tools are trained on massive sets of data to go beyond simply predicting “what comes next” and create brand new content (e.g., text, images, code, audio) in response to your prompts.  

 Generative Pre-trained Transformer (GPT): Used to answer questions and generate text and graphics in response to a prompt. 

 Prompt / Input: The request or question you give to a GenAI tool. Good prompts = better results. 

Response / Output: The answer given to you from the GenAI tool. 

 Hallucination: When AI makes up information that sounds true but isn’t. At their root, these are prediction tools. The tool might believe it’s being helpful even when it what it gives you is false or unsupported by evidence. This is why AI can sound confident, while being completely wrong. This is also why your human brain is still the most important tool in the room. 

Additional topics to consider

Accuracy and Accountability

Generative AI may not be accurate and may hallucinate sources. Make sure to verify any claims made or sources provided by generative AI. Remember, you are accountable for what you include in your assignments.

Data Privacy

If you use an AI tool, have you reviewed and considered how your data is being protected? Have you reviewed if or how your data is being used?

Ethics

Academic integrity is an essential part of academic excellence. As a student you are accountable to PS 1901 Student Code of Conduct. If you are not sure if your AI usage is ethical, please ask! We are here to help you learn and succeed!

Additional ethics considerations:
  • Copyright concerns about what information is used to train generative AI and who owns what is produced.
  • Digital divide concerns regarding what access to AI costs and the quality of free versus paid access to generative AI tools.
  • Environmental concerns around the resources required to power AI.
  • Misinformation and bias concerns around the content created using generative AI.

Stay curious! Explore responsibly, and ask questions when in doubt.