In Unit 9, you learned about the principles of Open Pedagogy, a series of practices which involve engaging students in a course through the development, adaptation, or use of open educational resources. These practices might include creating renewable assignments, textbook replacement and enhancement, and open course design, among others. AI may be especially suited to an open pedagogy approach because the technology is new to both students and teachers.

AI and Open Pedagogy

With how quickly AI is evolving, we are, in some sense, going to be discovering alongside students for the foreseeable future. So, there can be a sense of camaraderie: as humans, we are grappling with the nature, ethics, and future of AI. Mills, Bali, and Eaton, in “How do we respond to generative AI in education? Open educational practices give us a framework for an ongoing process,” argue that Open Educational Practices, including Open Pedagogy, can be a “shock absorber,” “providing a rich start to helping educators find their way through generative AI and other future shocks” (2023):

Shocks in education, like the COVID-19 pandemic or the advent of ChatGPT and other AI text generators, create a need to respond quickly, even though we often have insufficient local knowledge to take action. Open and public scholarship becomes a space for us to find and support one another as we build expertise through a turbulent time.

Supporting AI Literacy through Open Pedagogy

The technological advancement of generative AI and the related discussions surrounding fair use and copyright (see Lesson 7) present a unique opportunity to raise awareness and increase student knowledge around open licensing and the ethical use and attribution of AI-generated content. Just as digital literacy is key to both college and workplace skills, critical AI literacy is becoming key and must be taught in college, and to some extent, every course must help to build critical AI literacy as it applies to the subject matter. Maha Bali, in “What I Mean When I Say Critical AI Literacy,” defines it as “the basic skill of how to use AI” + “the capacity to know when, where, and why to use it for a purpose and, importantly, when NOT to use it.”

Using AI to co-create instructional materials with students could be an opportunity to teach critical AI literacy and course content. If we invite students to use AI, we will be helping them practice a healthy skepticism about AI outputs and inviting practice critiquing such outputs for accuracy, bias, and depth of insight. For example, in spring 2023, instructor Emily Pitts Donahoe offered students the opportunity to either write a traditional final paper or collaborate on a piece with her about the ungrading experiments they undertook together. This “renewable assignment” allowed them to reflect on the potential use of AI to support and/or complete writing assignments. They published the piece in the blog “Unmaking the Grade.” (And here it is being used again — renewable assignment! — for this lesson.)

Other Ideas for AI-Supported Co-Creation of OER

Other ideas for AI-supported co-creation with students include:

• Collaboratively develop effective prompts to generate more culturally diverse and responsive images for an open textbook. 
• Have students input a chapter into generative AI and ask for assessment questions, honing both the prompts and the output for effective questions.
• Create training videos in a discipline using an AI-based platform like Synthesia.
• Ask generatie AI to adapt content to focus more on students’ specific interests or identities.
• Prompt AI to create learning materials with a specific focus or types of examples and then use their expertise to assess the quality of the outputs.

OER Textbook Template for AI Transparency and OER Literacy

The following OER textbook insert template is an example of how to model good practice around AI, foster a culture of transparency, and educate students on the ethical and critical use of AI and openly licensed content.
This OER Textbook Insert Template is free to use and adapt and includes the following sections:

• What’s different about this textbook?
• What you’ll  notice (types of citations)
• How to cite this book
• How to contribute to OER – apply an open license to your work
• How AI was used in this textbook – how it is cited
• How to cite AI-generated content in your work