Faculty Examples: Motivate Your Students

Show students why the work matters, especially for the career or life outside the classroom that brought them to your course. When purpose is visible and personally relevant, students are more likely to engage with the work itself instead of treating it as a hoop to jump through. 

Below are examples from UO faculty.

The purpose section doesn't just gesture at relevance. It ties the assignment to nine specific, named career-ready skills, checked off directly against the assignment's actual tasks. Professor Raza says, "By working collaboratively, you will gain important transferable skills used in various careers from policy and law to other advocacy-based professions."

Design Moves

• Explicitly marks which UO Core Ed Skills the assignment develops — Critical Thinking, Career & Self-Development, Communication, Teamwork, Leadership, Equity & Inclusion, Technology, and others — rather than a general statement. 
• Purpose section separately answers "why this topic," "why groups," and "why present," giving students three distinct reasons rather than one blanket rationale. 
• Builds on the Purpose/Task/Criteria structure from the AI-Aware Transparent Assignment Template, so purpose is stated before task details, not folded into instructions. 

Professor Gupta explicitly links class content to students' majors and career paths, and models responsible AI use directly in her syllabus rather than just describing it. She says, "AI is a great tool and the more we can expose ourselves and our students to it in a positive way, the better."

Design Moves

• Syllabus includes real, ready-to-use sample prompts for students, e.g. "I'm a freshman in college. Provide detailed information about electrochemistry at the level of a first-year college introduction." 
• Explicitly ties class examples to student majors and career paths. 
• Asynchronous sections require handwritten, show-your-work submissions. 
• In-person exams are preceded by full-class collaborative practice exams. 

Professor Radcliffe ties assignments directly to the career readiness expectations students will face after graduation, framing AI fluency itself as a professional competency rather than a shortcut. He says, "A key focus of my classes is career readiness. I would always contend that when students graduate, there will be an expectation that they will be AI literate, that they will understand the pros and cons of different AI platforms and tools, and that they will be able to use them and know when not to use them."

Design Moves

• Students choose their own media company or content creator to research for the "Show Me the Money" project, which raises buy-in over an assigned topic. 
• Research process is modeled and critically evaluated in class before students conduct their own, so process is demonstrated rather than just stated. 
• Assessment weights accurate, relevant citations, tying the grading criteria back to the real industry skill the assignment is meant to build. 

Rather than presenting an AI policy as a rule, Prof. Connolly explains the reasoning behind it directly to students: AI is intended to support a challenging learning process, not produce the final answer. She writes: "Objective 3 (optional): Students will learn how to use artificial intelligence in a way that assists you through the difficult process of reading a primary research article, without simply answering the questions... The assignment can be completed without AI for those students who prefer not to use it."

Design Moves

• States the rationale for the AI approach as an explicit learning objective, helping students understand why the tool is being used in this way rather than encountering it as an unexplained rule.
• Distinguishes between "assisting with a difficult process" and "answering the questions," making clear what intellectual work students are expected to do themselves.
• Maintains a valid non-AI pathway, ensuring that the learning purpose remains intact regardless of whether a student chooses to use AI.

This assignment also reflects principles highlighted in Promote Process and Build AI Literacy. See those pages for additional examples.