This page includes ideas for using AI “behind the scenes” to assist you in developing and refining materials related to your course. The strategies below include generic, example prompts you can adapt to your teaching context. Because of the nature of generative AI, there will likely be a great deal of variability in the output generated, including output that doesn’t make sense. Remember to always evaluate and revise whenever you use AI.
Improving course alignment
As articulated in the UW Faculty Code, instructors are expected to align their teaching by intentionally designing and organizing their courses to help learners meet learning objectives. (UW Faculty Code, section 24-32). Instructors might use AI in an assistive capacity to:
Prompt AI to check your course outcomes: “You are an instructor teaching [insert topic] in a [insert course name] course. Are these course learning outcomes [insert your course learning outcomes] clear, measurable, and student-centered?” Evaluate the AI output and revise your learning outcomes to make them easily understood by students and clearly measurable.
Prompt AI to check your course alignment: “You are an instructor teaching [insert topic] in a [insert course name] course. Check that this assignment aligns with these learning outcomes.” Evaluate the AI output and revise the assignment.
Drafting learning materials
Instructors might use AI in an assistive capacity to draft a variety of teaching materials designed to help students develop critical thinking, including:
Prompt AI to draft sample case studies where students can discuss and apply what they have learned in class. For example, choose a case study that has worked well in the past and prompt AI: “Draft five case studies following the example I give, where students can apply [insert concept].” Evaluate the AI output and refine the drafts into case studies relevant to your learning outcomes.
Prompt AI to draft practice problems that progressively increase in complexity or difficulty. For example: “Draft three practice problems for [insert concept] with different levels of difficulty: easy, intermediate, advanced.” Evaluate the AI output and revise as needed to ensure accuracy and difficulty level.
Prompt AI to draft sample data sets for students to use in assignments that require the analysis and use of data. For example: “Draft three sample data sets with [insert variables] to use in practicing how to solve [insert problem].” Evaluate the AI output and revise as needed to ensure that it meets your specifications and aligns with your desired learning outcome.
Drafting assessment-related materials
Instructors might use AI in an assistive capacity to develop diverse question banks for quizzes and exams, as well as rubrics for assignments.
Prompt AI to draft questions for practice quizzes designed to help students identify knowledge gaps. For example: “Draft three true/false questions about [insert concept].” Evaluate and revise the AI output to ensure accuracy and relevance.
Prompt AI to draft a rubric you can share with students when you share the instructions for an assignment. For example: “Draft a rubric for this assignment that includes three performance criteria, with three corresponding performance levels, and short descriptions for each.” Evaluate and revise the AI output to ensure that the rubric aligns with your assignment’s learning objectives.
Analyzing student feedback
Instructors might use AI in an assistive capacity to help with some of the tasks associated with collecting and analyzing student feedback.
Important reminder: It is a violation of the Family Educational Rights and Privacy Act (FERPA) to share identifying information, including students’ names, IDs, grades, or enrollment status, when using digital tools without the consent of students (or their parents if the student is under 18 years old). If you choose to use a generative AI tool to assist in evaluating themes in student data, you must first anonymize the data and remove all identifying information.
- Analyze mid-quarter check-in feedback. For example: “Analyze this feedback and identify the top 5 things that are working well for students in the course and the top 5 changes students feel might support their learning.” Evaluate the AI output to ensure that the themes are representative of the feedback from students and determine opportunities to improve your approach.
- Analyze exit ticket responses: “Identify the top three concepts that remain unclear to students.” Evaluate the AI output and use it as the basis for a follow-up discussion with students.
- Analyze student course evaluation feedback across quarters or courses. For example: “Identify the top five suggestions from these course evaluation reports.” Use the themes to identify specific opportunities to review your course and improve your teaching practice.