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We have dabbled with social annotation through Hypothes.is in a previous course during our program, but I never thought much about it. It was interesting to see my classmates perspectives and thoughts as we read but my takeaway from the task of annotating was minimal at best. I didn’t walk away seeing or understanding the value of it.
After hearing Dr. Remi Kalir discuss social annotation I’m intrigued to revisit this idea more intentionally.
With my younger students I work with them to learn about how to annotate, whether it’s highlighting a text and adding a comment in the margins, or a new assignment I created this year where students are creating a song about a specific topic and adding annotations to add in addition information or details to explain what the line in the song means or is referring to. But we never really move past “private” annotations. I use quotation marks because the students annotations are not shared with peers but I do look at them in order to provide feedback. They are private in the sense of they aren’t being shared with their peers or the public, but they are being viewed by me.
For my older students we move completely away from private annotations, and regularly annotate in small groups as a class, often using sticky-notes where students write thoughts or ideas and stick them together as a collective brainstorm. These are then shared out, and often used to inform my teaching and the direction we will head in next as a class. However, doing annotations this way is still individual, the students aren’t truly building off of one another or discussing what others are saying in a meaningful way.
The question then is how can I change my relationship with social annotations within my teaching practice?
My first thought was about generative AI, and the role it could play with annotating. Could students use AI to annotate a text as the starting point of their conversations, and build upon what the AI has included. Because the AI generated work comes from someone, somewhere, students can interact with it as though it is another person in the room. Could they annotate the annotations with questions, and reasonings, together, building upon both the AI’s work and each others in a social and collaborative way? What if after they built on the AI generated annotations they put their own work back into the AI software and asked it to further analyze and annotate their work to see where else meaning could be made, creating a dialogue between the students and the technology.
I wonder also how we can use social annotation to further develop students conceptual understanding within classrooms. I wonder if students could use social annotations to demonstrate not only their knowledge but also their thinking skills in relation to a conceptual understanding of a unit. If the class is annotating a document about a concept together, could they use their own understanding of whatever topic they explored to demonstrate their understanding of the concept. Could they then comment on and ask questions about their classmates annotations to further demonstrate their thinking as they build connections between each other?
There is a lot for me to think about and unpack as I reflect on this discussion and I look forward to discussing it further with my colleagues as I think about it further in the coming days and weeks.
Annotation has been a staple in my high school English classes. Like many educators, I use sticky notes for group annotation exercises—students write their thoughts, post them on a shared space, and we use them as a launching point for discussion. But upon reflection, I realize that while this is happening in a “group setting,” it isn’t genuinely collaborative. Students share their observations, but they don’t often engage in meaningful commentary or analysis of each other’s ideas.
As you mentioned, this is why the idea of collaborative annotation is so relevant. It isn’t just about putting ideas in the same place—it’s about building on them, questioning them, and refining them collectively. The challenge is finding ways to push students beyond surface-level sharing to deeper engagement with their peers’ insights.
One intriguing approach I hadn’t considered before is using AI as a scaffold for annotation. Rather than letting AI do the cognitive work for students, it could be an interactive participant, prompting critical thinking. For example, students could begin with AI-generated annotations on a text and then analyze, refine, or challenge the AI’s input. This forces them to engage rather than passively accept what’s presented actively. Could they respond to AI-generated annotations with questions? Expand on them with textual evidence. Debate their accuracy or relevance.
This approach offers a structured way to integrate critical AI interactions into the classroom. Instead of simply providing answers, students use AI as a thought partner—one they can push back against, engage with, and ultimately learn from.
But I have questions. What are the best tools for this? How do we design prompts that encourage deep engagement rather than superficial agreement? How do we ensure that students still do the intellectual heavy lifting?