Skip to main content

Reading in the Age of AI: Designing for Engagement

Monday
A woman reads on her phone during a WAC workshop while others work on laptops around the table.

Students have always used tools to navigate course readings, from marginal notes and study guides to audiobooks and digital annotation. What feels different now is the speed and scale of AI-mediated reading. Students can ask AI tools to summarize, translate, explain, quiz, simplify, reorganize, or even convert assigned texts into audio or other study materials.

 

These practices raise urgent questions for instructors: 

  • What do we want students to do when we ask them to read? 
  • What parts of reading should remain slow, active, and reflective? 
  • Which technologies can support access without replacing intellectual engagement?

Recent conversations in higher education suggest these questions are already reshaping classrooms. Inside Higher Ed reports that students are increasingly turning to YouTube, podcasts, AI generated summaries, and other supports to keep up with assigned reading, while instructors are experimenting with guided reading, in class reading time, and more explicit instruction in how to approach disciplinary texts.

Faculty Learning Community - Reading with AI 

This summer, WAC’s Reading with AI Faculty Learning Community brought faculty and instructors together to explore those questions through conversation, tool experimentation, and assignment design. Over four meetings, participants considered how AI is shaping students’ reading practices and how instructors can design reading experiences that are purposeful, transparent, and connected to course learning outcomes.

 

The FLC began with a foundational question: Why do we assign reading? Participants reflected on what counts as reading in their courses, what students are expected to do with assigned texts, and where students often struggle. From there, the group moved through different stages of AI-supported reading: purpose, inputs, outputs, critical literacy, reflection, and revision.

 

Participants experimented with tools such as NotebookLM, Speechify, UA AI, and other AI-supported reading technologies. They considered how these tools might help students access dense or technical materials, but also how polished summaries can create an “illusion of competence,” making students feel they understand a text before they have practiced analysis, synthesis, or application.

 

One especially productive conversation focused on AI outputs and critical literacy. Participants asked what AI-generated summaries, podcasts, mind maps, or explanations make visible, what they leave out, and how students might learn to compare and question those outputs. The group also discussed the environmental costs of repeated AI use and the need to help students make thoughtful choices about when and why to use these tools.

 

By the final meeting, participants were applying these ideas to their own teaching contexts. Some planned to make AI expectations more explicit in assignment instructions, including which parts of a project may involve AI support and which parts should remain students’ own work. Others planned to build in class discussions about AI and learning, ask students to compare outputs across multiple tools, or use tools like NotebookLM and Speechify to support disciplinary reading and accessibility.

 

Reading with AI Resources

For instructors interested in continuing this work, the FLC highlighted several resources that can support thoughtful, accessible, and critically engaged reading practices.

AI and WAC

WAC’s teaching resources offer guidance on prompt design, AI-supported feedback, process-based writing, critical AI literacy, multilingual writers, environmental impacts, and syllabus language.

NotebookLM 

Google NotebookLM is an AI-powered research assistant that helps users synthesize information from their own documents, including PDFs, Google Docs, and copied text. It can also support questions, summaries, and idea exploration. NotebookLM is available at no cost for U of A students, faculty, and staff when signed in with a NetID.

Speechify 

Speechify is a text-to-speech app that converts written content into audio, allowing users to listen to texts across devices. Speechify licenses are available to anyone with an @arizona.edu email address.

2026 Student Guide to Artificial Intelligence

This student-facing guide from Elon University, AAC&U, and The Princeton Review offers practical activities for helping students keep human judgment, curiosity, ethics, and critical thinking at the center of AI use.

To learn more or talk through ideas for your course, contact the WAC team for a consultation!