AI
“It is important that you submit your own work so I can provide meaningful feedback to you to inform your next efforts to learn. If I don’t know what you do or don’t know, I can’t adjust my instruction to better support your learning. It’s okay not to know. It’s okay to ask questions. If you knew all of this already, there’d be no need for you to take this class.
Academic integrity means you own what you know, acknowledge what you don’t know, and are transparent about the ideas or words you use that were drawn from others’ work or through the use of AI tools. Sometimes, I’ll ask you to retrace your steps so I can affirm – or assist with – the process you’ve used to complete a task. I’ll always ask you to cite your sources. I’ll always expect you to give credit to others or to a technology tool when credit is due.
Academic dishonesty involves any attempt to take credit for knowledge or skills that you don’t actually possess as your own. If you cannot explain your work after it has been completed, it may or may not be evidence of academic dishonesty. However, it is evidence that you haven’t internalized that knowledge or those skills yet. If that is the case, I need to know so I can help you take the next steps necessary to learn.”