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1. Define learning objectives and key concepts: Begin by clearly outlining the learning objectives and key concepts you want to address. For instance, if the goal is to understand the principles of physics, specify concepts such as motion, energy, and forces.
2. Generate general learning outcomes: Utilize a generative AI tool to create overarching learning outcomes. Example: “Generate student learning outcomes for a physics course covering motion, energy, and forces.” AI-generated outcomes may include statements like “Students will explain the relationship between force and motion” or “Students will apply the principles of energy conservation to solve real-world problems.”
3. Refine and tailor outcomes: Review the AI-generated outcomes and refine them to align with specific course objectives. Tailor the language to fit the educational context and the level of understanding expected from students.
4. Create specific learning objectives: Use generative AI to create more granular learning objectives for each key concept.
   Example: “Generate specific learning objectives for understanding motion in a physics course.” AI-generated objectives may include statements like “Students will calculate speed and acceleration using appropriate formulas” or “Students will analyze graphs to interpret an object’s motion.”
5. Ensure measurability and clarity: Review each learning outcome to ensure it is measurable and clear. Adjust language or add specificity as needed to enhance clarity. For instance, if an outcome states “Students will understand,” consider revising it to “Students will demonstrate understanding through practical applications.”

1. Define lecture topics and objectives: Identify the main topics and objectives you want to cover in your lecture. For instance, if the lecture is on “Introduction to Artificial Intelligence,” outline key subtopics such as AI history, applications, and ethical considerations.
2. Generate lecture overview: Prompt the generative AI with a request for a general lecture overview.
   Example: “Generate an overview for a lecture on ‘Introduction to Artificial Intelligence’ covering history, applications, and ethical considerations.” The AI might produce a concise summary, outlining key points and subtopics.
3. Outline main points and subtopics: Use the AI to help outline the main points and subtopics for each section of your lecture.
   Example: “Outline key points for the section on AI history in the ‘Introduction to Artificial Intelligence’ lecture.” The AI could generate an organized list of historical milestones and developments in AI.
4. Expand on subtopics with details: To add depth to your lecture, use the AI to generate detailed information for each subtopic.
   Example: “Provide detailed information on the ethical considerations related to AI in the ‘Introduction to Artificial Intelligence’ lecture.” The AI might generate content on topics such as bias in AI algorithms, privacy concerns, and responsible AI practices.
5. Incorporate relevant examples and case studies: Enhance your lecture with real-world examples and case studies.
   Example: “Generate examples illustrating the applications of AI in the ‘Introduction to Artificial Intelligence’ lecture.” The AI might offer instances of AI in healthcare, finance, or autonomous vehicles, providing concrete illustrations for your lecture.
6. Craft engaging lecture introductions and transitions: Use the AI to help craft engaging introductions for each section and smooth transitions between topics.
   Example: “Create an engaging introduction for the section on AI applications in the ‘Introduction to Artificial Intelligence’ lecture.” The AI might generate an attention-grabbing anecdote or a relevant statistic to captivate your audience.
7. Ensure coherence and flow: Review the content generated by the AI to ensure coherence and flow between different sections of your lecture. Adjust language or reorder information as needed to create a seamless and logical progression of ideas.

Generative AI, with its ability to understand context and generate diverse responses, can assist instructors in formulating open-ended questions that encourage deeper understanding and analysis.

1. Define assignment or discussion topics: Start by clearly defining the topics or themes for the assignment or discussion. For instance, if the focus is on literature, identify specific works, themes, or concepts you want students to explore.
2. Generate overall assignment or discussion prompt: Prompt the generative AI with a request for a general assignment or discussion prompt.
   Example: “Generate an assignment prompt for analyzing symbolism in ‘The Great Gatsby’ by F. Scott Fitzgerald.” The AI may provide a broad question like, “Explore and analyze the use of symbolism in ‘The Great Gatsby’ and its impact on character development and themes.”
3. Break down into specific tasks or questions: Use the AI to help break down the overall prompt into specific tasks or questions.
   Example: “Generate specific questions for analyzing symbolism in ‘The Great Gatsby’.” The AI might produce questions such as, “How does the green light symbolize the American Dream?” or “Examine the symbolic significance of the Valley of Ashes in the novel.”
4. Tailor for different learning levels: Adjust the complexity of the prompts based on the learning level of your students.
   Example: “Create discussion prompts on genetic inheritance suitable for high school biology students.” The AI may generate questions like, “Explain the principles of Mendelian inheritance” or “Predict the outcomes of genetic crosses involving specific traits.”
5. Include real-world applications: Enhance the relevance of the assignment or discussion by incorporating real-world applications.
   Example: “Generate prompts for a business ethics assignment discussing the ethical implications of a real-world corporate case.” The AI might provide questions like, “Analyze the ethical decisions made by the company in response to environmental concerns” or “Propose alternative strategies that prioritize ethical considerations.”
6. Encourage critical thinking and reflection: Prompt the AI to generate prompts that encourage critical thinking and reflection.
   Example: “Create discussion prompts for a philosophy class exploring existentialism.” The AI might generate questions like, “How does existentialism influence personal identity?” or “Reflect on the existential themes in a contemporary work of literature or film.”
7. Check for clarity and coherence: Review the prompts generated by the AI to ensure clarity and coherence. Adjust language or rephrase questions as needed to ensure that students can easily understand and respond to the prompts.

Rubric design is a critical aspect of assessing student work. Generative AI can streamline this process by helping instructors create fair and comprehensive rubrics. In this session, we will learn how to leverage AI to design rubrics tailored to specific assignments and projects. By examining real-world examples, participants will gain insights into how AI can enhance the assessment process, providing more nuanced and objective evaluation criteria.

1. Identify assessment criteria: Define the assessment criteria for the assignment or project. For example, if grading a research paper, criteria might include thesis clarity, evidence quality, organization, and writing mechanics.
2. Generate overall Rubric structure: Prompt the generative AI with a request for an overall rubric structure.
   Example: “Generate a rubric structure for grading a persuasive essay.” The AI may provide a general format, including categories like “Thesis Statement,” “Supporting Evidence,” and “Organization.”
3. Break down categories into subcriteria: Use the AI to break down each category into specific subcriteria.
   Example: “Generate subcriteria for assessing ‘Thesis Statement’ in a persuasive essay rubric.” The AI might generate subcriteria such as “Clarity of thesis,” “Relevance to the prompt,” and “Originality.”
4. Determine scoring levels: Define the scoring levels for each subcriterion.
   Example: “Generate scoring levels for ‘Clarity of thesis’ in a persuasive essay rubric.” The AI might provide levels like “Excellent (4): Clearly stated and focused,” “Good (3): Mostly clear,” “Satisfactory (2): Somewhat clear,” and “Needs Improvement (1): Unclear or vague.”
5. Tailor for assignment specifics: Adjust the rubric based on the specific requirements of the assignment.
   Example: “Customize a rubric for assessing creativity in a student presentation.” The AI could generate categories like “Creativity in Content,” “Presentation Style,” and “Engagement with the Audience.”
6. Include weighting for importance: Prompt the AI to generate weighting for each category or subcriterion based on their relative importance.
   Example: “Generate weightings for categories in a coding project rubric.” The AI might suggest higher weight for categories like “Functionality” and “Efficiency” compared to “Aesthetics.”
7. Check for clarity and objectivity: Review the rubric generated by the AI to ensure clarity and objectivity. Adjust language or modify criteria as needed to ensure that the rubric provides clear guidance for both instructors and students.