AI for Students

Build a clear understanding of what generative AI is, how it learns patterns, and where it fails.

• Patterns, data, and prediction explained in plain language
• What a chatbot is and what it is not: no understanding, no guaranteed truth
• Hallucinations and confident mistakes with live examples
• Everyday AI around you: recommendations, translation, search
• Free-tier tools and age or terms-of-use rules for each

Hands-on lab: Ask an assistant five questions from your own subject, mark which answers are right, partly right, or wrong, and explain why.

Use AI as a tutor and study partner in ways that deepen understanding rather than replace effort.

• Asking for explanations at different levels and with analogies
• Self-testing: AI-generated quizzes and flashcards from your notes
• Using NotebookLM to study from your own materials with citations
• The learn-first, ask-second habit and avoiding answer-copying
• Checking your institution's rules on permitted AI use
• Prompting for feedback on your own work rather than for finished work

Hands-on lab: Build a revision pack from your own lecture notes, answer the questions without help, then use AI to review your answers.

Learn to check facts, trace sources, and judge the quality of information before you rely on it.

• Lateral reading and checking claims across sources
• Using Perplexity and library databases while opening every cited source
• Spotting invented citations and quotes
• Bias, stereotypes, and missing perspectives in AI output
• Deepfakes and manipulated media basics
• Keeping a verification log

Hands-on lab: Fact-check a short AI-written article on a topic from your course, correcting errors and recording each source.

Create original work with AI support while keeping your voice and being open about how you used it.

• Brainstorming and outlining versus writing for you
• Revising your own draft using targeted feedback prompts
• Citing and acknowledging AI assistance honestly
• Creating slides and visuals in Canva
• Copyright and image-use basics
• Plagiarism, detection tools, and why they are unreliable as proof

Hands-on lab: Write a short piece yourself, use AI only for feedback, and attach an AI-use statement listing every prompt that shaped the work.

Protect your personal information and keep healthy habits when using AI tools.

• What not to share: personal details, classmates' information, private documents
• Data settings, chat history, and account safety
• Overreliance, procrastination, and keeping practice skills sharp
• Using AI chatbots for personal advice: limits and when to talk to a person
• Respectful use: harassment, impersonation, and fake content

Hands-on lab: Create a personal AI-use code with your own rules for privacy, honesty, and limits, and test it on three scenarios.

Plan and present a project in your own field where you can show what you decided and why.

• Choosing a real problem in your discipline
• Breaking a project into steps and deciding where AI helps
• Collecting and acknowledging sources and data responsibly
• Preparing a short demonstration
• Reflecting on what AI got wrong and what you changed

Hands-on lab: Present your project to the group and answer questions about your reasoning, sources, and corrections.