July 23

Generative AI Prompts for DI and UDL


     The goal of Differentiated Instruction (DI) is to modify and adjust  the content, instructional process, and the resulting learning artifact that each student needs to learn.

     Prompt generation and curating the prompts with the most effective rendering has replaced or at least curtailed teachers’ previous preparation practice of bookmarking weblinks. The efficiency and adaptive characteristics of Generative AI can extend to Differentiated Instruction (DI) and Universal Design for Learning (UDL). One important strategy for teachers is to apply specific prompts for AI.

     According to Nievas, an [AI] prompt such as: “‘What are three different [or differentiated] approaches to teaching the central idea of a text’ yielded research-supported options such as,  graphic organizers, visual representations, guided reading, and close reading, as well as a description of those strategies’” (2023).

     AI prompts can help teachers differentiate instruction and implement Universal Design for Learning (UDL) by generating tailored activities, assessments, and resources. Generative AI prompts can also aid in generating lesson introductions, student-friendly explanations, and feedback mechanisms. Ideas to expand Multiple Means of Representation could follow from prompts such as  “Can you give me multiple resources to introduce chemical reactions?” (Nievas, 2023).  The rendered resources included videos, websites, simulations, games, or infographics. Examples include prompts for creating choice boards, tiered activities, personalized learning plans, and accessible materials
https://www.geeksforgeeks.org/artificial-intelligence/what-is-an-ai-prompt/

Image Source: https://www.geeksforgeeks.org/artificial-intelligence/what-is-an-ai-prompt/

Here are some specific examples of AI prompts to try-out- please share your favorite prompts as a comment:
For Differentiated Instruction (DI):
  • “Create a choice board for a lesson on [topic], offering options for different learning styles and skill levels.” 
  • “Generate a list of tiered activities for [grade level] students on [topic], catering to varying levels of understanding.” 
  • “Develop a personalized learning plan for a student with [specific learning need] in [subject].” 
  • “Provide examples of how to modify a lesson on [topic] for students with [specific disability] or who are English Language Learners.” 
  • “Suggest ways to incorporate student interests into a lesson on [topic].” 
  • “Generate a list of resources for supporting students with social-emotional needs in a lesson on [topic].” 

For Universal Design for Learning (UDL):

  • “Rewrite the learning objectives for this lesson in student-friendly language.”
  • “Develop multiple means of representation for this lesson, including visual aids, audio recordings, and hands-on activities.”
  • “Suggest ways to provide multiple means of action and expression in this lesson, such as through written work, oral presentations, or digital projects.”
  • “Create a rubric for assessing student work that is clear, concise, and aligned with UDL principles.”
  • “Suggest ways to incorporate technology into this lesson to support diverse learners.”
  • “Generate a list of assistive technology tools that can support students with specific needs in this lesson.”

 

 


References

Nieves, K. (2023). 5 Ways to Use AI Tools to Meet Students’ Needs. Edutopia. https://www.edutopia.org/article/using-ai-tools-differentiated-instruction/
Archived Link: https://web.archive.org/web/20250725213652/https://www.edutopia.org/article/using-ai-tools-differentiated-instruction/

Teague, H. (2025).10-Rep Learning: Generative AI Prompts for DI and UDL. Edublogs. https://4oops.edublogs.org/2025/07/23/ai-prompts4diandudl/

February 25

Miguel Guhlin’s blog post: Differentiated Learning Powered by AI

TCEA TechNotes blog link: https://blog.tcea.org/differentiated-learning-powered-by-ai/

Internet Archive Wayback Machine Link: https://web.archive.org/web/20250227045616/https://blog.tcea.org/differentiated-learning-powered-by-ai/ 

September 1

Weekend Ed Quote ~ September 1

julianstodd.wordpress.com

 


More Weekend Ed. Quotes

#GCUTEC544 #GCUTEC595 #GCUTEC516 #GCUTEC521
#CUNE607 #CUNE604, #CUNE605
#PBSReaders4Life

June 27

The Solipsism of generative AI

The Solipsism of generative AI

 

In some of my graduate classes, we have been reading about virtual and digital learning and tools to use in instructional practice. 

ChatGPT, an artificial intelligence chat bot from the company OpenAI came into the spotlight in 2022. ChatGPT is one of a few generative text aggregators available to the public (Dehouche, 2021; Rutter & Mintz, 2023). 

Generative text renderers such as ChatGPT, can generate collections of information, and some schools are banning the tool from its devices and networks altogether (Korn & Kelly, 2023).

Some of the ways that generative text can theoretically be used include the following (Dehouche, 2021. Korn & Kelly, 2023; Rutter & Mintz, 2023; Washburn, 2023)… but is this ethical

  • Biographical references 
  • Bibliography citations
  • Lesson plan creation
  • Student assessment 
  • Define terms and explain challenging concepts  
  • Solve math equations 
  • Course syllabi 
  • Explore debate topics through theoretical lenses 
  • Render written text in various styles including descriptive and argumentative 
  • Writing samples in job application packets
  • Research reports
  • Speeches
  • Medical reports

Although the ChatGPT marketing indicates that it generates “original” writing, it does not do this because it is solipsistic, or existing only within itself and therefore not reflecting peer-reviewed sources (Teague, 2023).  Instead, artificial intelligence chatbots, such as ChatGPT, assembles and renders content based on sources indexed online, based on the prompts it is provided. This process is similar to compiling a Playlist, mixed , or mixed tape. The sources used in compilation may or may not be copyright-free and they may not be peer-reviewed.

                                                                        References

Dehouche, N. (2021). Plagiarism in the age of massive generative pre-trained transformers (GPT-3). Ethics in Science and Environmental Politics, (2), 17–23. https://doi.org/10.3354/esep00195  

Korn, J. & Kelly, S. (2023). New York City public schools ban access to AI tool that could help students cheat. CNN Business. https://www.cnn.com/2023/01/05/tech/chatgpt-nyc-school-ban/index.html

Quora (2023). Etymology of the word solipsism. https://www.quora.com/What-is-the-etymology-of-the-word-solipsism

Rutter, M.P. & Mintz, S. (2023). ChatGPT: Threat or menace? Higher Ed Gamma.

Washburn, B. (2023) How Teachers can use ChatGPT to assess students and provide feedback. Brittany Washburn.com blog. https://brittanywashburn.com/2023/03/how-teachers-can-use-chatgpt-to-assess-students-and-provide-feedback/#:~:text=ChatGPT%20is%20an%20AI%2Dbased,provide%20feedback%20efficiently%20and%20accurately.

 

To cite this post: Teague, H. (2023). The Solipsism of generative AI. 10RepLearning blog. https://4oops.edublogs.org/2023/06/27/the-solipsism-of-generative-ai/