Salma Kalim
Assignments & Activities Archive
Assignment Description
This multi-step assignment invites students to compare their own scholarly reading practices with AI-generated analyses within the context of annotated bibliography writing. By incorporating NotebookLM—a document-grounded research tool—students engage in a guided exchange with artificial intelligence as they draft, revise, and refine their understanding of academic sources. Unlike general-purpose language models, NotebookLM generates responses strictly from uploaded documents and provides citation-linked outputs tied to specific passages. Because its design limits responses to user-supplied texts, it reduces the occurrences of fabricated claims and foregrounds evidence tracing. These constraints make the tool especially appropriate for activities that demand careful attention to argument, methodology, and disciplinary framing. In addition to text-based summaries, the platform reorganizes source material into structured formats such as study guides, glossaries, timelines, note cards, and podcast-style conversations. Presenting the same material across multiple formats allows students to approach complex scholarship from different cognitive angles while maintaining accountability to the original text. Although conversations about AI in writing classrooms often center on prompt engineering or academic integrity, fewer pedagogical models examine how document-based systems reshape foundational research practices. This assignment addresses that gap by demonstrating how document-grounded AI systems can strengthen students’ source-based reading practices, particularly when differences between human and AI interpretations prompt careful reexamination of the text. This activity is well-suited to upper-division undergraduate or graduate research writing courses.