GenAI tools can do some tasks quite well, such as:
- Finding the right wording
- Processing an experience
- Drudgery of a repetitive task
- Brainstorming lots of ideas
- Testing out an argument or idea
- Visualizing data
- Getting suggestions for improvements.
Ed tech companies may promote a variety of tools to make faculty’s and student’s lives easier. We have responsibilities to determine our own comfort levels and uses of these technologies. Not everyone will draw the same lines or boundaries, with consideration of a variety of concerns and needs, from intellectual property to personal strengths. We offer some ideas for you to consider and experiment with. Please reach out to us if you have additional suggestions to include in this section.
Offload Mundane Tasks
“You know what the biggest problem with pushing all-things-AI is? Wrong direction. I want AI to do my laundry and dishes so that I can do art and writing, not for AI to do my art and writing so that I can do my laundry and dishes.”
Author Joanna Maciejewska
This quote from Joanna Maciejewski highlights concerns about what tasks are offloaded to genAI. You may find that genAI can save you time by offloading mundane tasks.
For instance, do you need to create a project management timeline with all the Monday dates for a calendar year that avoid federal holidays? Sure, you could manually generate this list from a calendar, cross-checking with internet lists of holidays. This might take 15 minutes. A genAI tool can make this list in 15 seconds.
Maybe you want to create a series of reminders to send to students via Canvas about a semester-long project. While it might take you 30 minutes to draft these, a genAI tool could create them much faster using assignment instructions you’ve already drafted.
Have you ever quickly typed an email only to realize the recipient is confused? GenAI tools can serve as an editor by simplifying or clarifying your writing or checking for errors.
Ample evidence exists showing that students learn more when they are engaged in active learning. And, facilitating active learning can require faculty time to create instructional materials, time that sometimes just doesn’t exist. As a result, we don’t always choose the active learning pathway, even when we know it is more effective. You can leverage genAI to support your active learning goals. Here are some ideas to get started:
Generate Case Studies
Intimate Debate Case Study
Interactive Role Play
Develop Interactive, Guided Notes Worksheets
Guided notes are basically an outline with key terms and details redacted. Instructors created a worksheet that follows the structure of a lecture (of any length). As students listen, they take notes onto the worksheet, filling in the missing information. This is a great way to help students learn how to take notes. You can use a genAI tool to create these worksheets. Upload a slidedeck or set of lecture notes and prompt the tool to generate an outline with sufficient structure and appropriate redactions.
Maximize the Testing Effect by Generating a Volume of Practice Quiz Questions
Quizzing is an excellent way to learn information (activating several strategies for effective learning including retrieval practice, spacing, interleaving, and elaboration), especially when students are given short-answer questions and immediate feedback. From a technical perspective, this can be set up in Canvas easily. However, generating multiple sets of questions (to allow students sufficient practice) can be time-consuming. GenAI tools can rapidly create quiz questions in a variety of formats. Make sure to check the output for accuracy, which is a much faster experience than writing all the questions from scratch.
Make Assignments More Transparent with Purpose, Tasks, & Criteria
The Transparency in Learning and Teaching (TILT) project has identified that if faculty restructure two assignments in a course to describe the purpose, detailed tasks, and criteria for high marks, students not only do better on the assignment, but also in the course and are more likely to persist past that semester.
The CTLI has created a Transparent Assignment Template to assist faculty with converting assignments using the principles of the TILT framework. GenAI can assist with these conversions. For instance, with a structured prompt including your existing assignment instructions, you could ask the genAI chatbot to identify detailed, sequenced, concrete steps students would need to take to successfully complete the assignment as a starting point. Asking the genAI to take on a persona, such as a first-year, first-gen college student, may highlight assumptions you might have made about student knowledge or skills, that are actually integral to include in the task list. Or you could use genAI to draft a checklist of criteria or rubric for evaluating the strength of student submissions. While you would need to edit the output, having a starting point to refine can save time.
You can even test out the CTLI-developed Transparent Assignment Design Bot, a custom genAI agent meant to help faculty. It’s in beta format – please give us feedback if you use it!
Proactively Anticipate Student Questions
The further we get as faculty from the student experience, the easier it is to overlook a detail or make an assumption about students’ knowledge of college. Some faculty are using genAI tools to create FAQs based on their syllabi. Simply feed your syllabi to a genAI chatbot, ask it to assume a persona similar to students in your class, and have it generate questions and answers that students might be shy to ask, but important to their success. Even if you don’t use the FAQs as published, it may help you make your syllabus content more student-focused or may give you ideas for how to discuss the class on the first day.
Generate Alt-Text and Image Descriptions
In teaching, we often use images, graphs, charts, and graphic organizers to present information to students. In doing so, if we don’t consider digital accessibility, we can exclude students with disabilities. One important step you can take is including Alternative Text (frequently called Alt-Text) when you share visual information. While programs such as Microsoft Word and Powerpoint will attempt to generate Alt-Text for you, they are often laughably inaccurate. Arizona State University has built a genAI Image Accessibility Generator to assist with this work.
Example 1: Photograph
Image Descriptions by ASU’s Image Accessibility Generator:
Alt-Text: A serene lake reflecting a forest and sunlit mountains, with a rainbow in a cloudy sky.
(Compare with Microsoft’s automatically generated Alt-Text: A body of water with trees and mountains in the background.)
Image Description: The image shows a tranquil landscape with a serene lake in the foreground, reflecting the surrounding scenery. Stretching across the surface of the water are soft ripples, catching the sunlight in varying shades of green and yellow. In the middle ground, a dense forest of evergreen trees lines the lake’s edge, with tall coniferous trees, mostly pine, creating a thick, green band. Behind the forest rise majestic mountain peaks partially covered by shadows, with slopes illuminated by warm sunlight. Over the mountains, a subtle rainbow arcs gently across a cloudy sky, which transitions from dark gray to lighter tones, hinting at clearing weather.
Example 2: Table
Table Descriptions by ASU’s Image Accessibility Generator:
Alt-Text: Table of sample sizes for varying confidence intervals and errors.
(Compare with Microsoft’s automatically generated Alt-Text: A table with numbers and text.)
Image Description: The image is a table displaying sample sizes needed for different confidence intervals and sampling errors. The table is divided into two main sections: one for a 90% confidence interval and the other for a 95% confidence interval. Each section is further divided by columns indicating sampling errors of ±15%, ±10%, and ±5%. The rows represent different population sizes: 25, 50, 100, 200, and 400. The values in the table are represented in a grid with alternating light green and white background for each row, with white text on a dark green header and black text throughout.
CustomGPTs are trained on narrow data and have specific functions.
Some faculty are carefully and thoughtfully building custom GPTs to support activities like group work or to turn feedback into narrative. Dr. Graham Clay has worked with OneHE to demonstrate how he’s using custom GPTs to enhance his teaching efforts. Here’s how you can access his ideas:
- Create a free account with OneHE: https://onehe.org/register/member/
- Access the videos with your free membership: https://onehe.org/resources/how-ai-can-help-with-grading-feedback-and-assessment-a-chat-with-graham-clay
Note that Dr. Clay does not upload student work into a genAI tool – this is extremely important to protect student privacy.
Other faculty such as Dr. Martin Puchner have created custom GPTs for dialogic purposes with historical figures.
If you are interested in building custom GPTs, work with VSC IT Shared Services to ensure that the tool you are using has been properly vetted for data security, privacy, and accessibility, particularly if you are having students use what you create.