AI-resilient assignments are designed to minimize student misuse of AI tools and encourage original work by tapping into students' motivation and sense of agency. 

AI-Vulnerable assignments are those that can easily be performed by AI tools and in which students feel little interest or ownership, making AI use more likely. 

To understand what makes assignments AI vulnerable, it's helpful to consider what drives students to use AI in the first place. Students are more likely to use AI when they feel apathetic about their coursework and see little value in it. Additionally, students report using AI to boost efficiency, freeing up time for tasks they find more creative or meaningful. These insights suggest the following traits of AI Vulnerable assignments:

• Low perceived relevance: Work that students view as disconnected from their goals and interests, potentially leading to outsourcing.
• Limited personal agency or creativity: Assignments offering few opportunities for student voice, critical analysis, or creative interpretation.
• Product, not process, focused: Assignments emphasizing final outcomes without showcasing progress (e.g., a final paper with no prior drafts or outlines submitted).
• Easily automated: Tasks with common AI capabilities, such as text summarization, basic calculations, or factual question-answering.

Below is a list of traits that increase AI Resilience in assignments. Incorporating any of these features enhances resilience; it's not necessary to include all of them.

• Process-oriented: Requires students to demonstrate knowledge evolution through multiple submissions (e.g., concept maps, outlines, analytical memos). Enables instructors to track progress and identify original work.
• Project-based: Culminates in a tangible final product that is worked on over an extended time and offers an authentic setting to practice skills and apply knowledge from the course; may involve collaboration and encourages problem-solving and grappling with novel approaches and solutions.
• Authentic: Poses contextualized, complex challenges that mirror real world tasks students would do outside the classroom, and thus has a practical value beyond the classroom.
• Multimodal: Engages students in creating content across various formats (written, visual, audio, interactive). Encourage creativity and personal expression while challenging AI replication. 
• Personally relevant: Taps into students’ personal interests, experiences, or goals to produce work they find meaningful.
• Experiential: Involves active participation in real-world activities (fieldwork, interviews, experiments). Ground work in personal experience and data collection.
• Reflective and metacognitive: Promotes critical thinking about learning processes and decisions. Enhances metacognitive skills through activities like portfolios, exam wrappers, or reflective essays that discuss students' learning process, integration of feedback, and areas to improve.