Amanda Mireles is using hypothesis for students to get their own video clips and to annotate them for other students.

Students took scenes from THE BIG BANG and used literature and academic references to relate to the scene

I somewhat disagree - I think this community building is successful precisely because there is a shared interest or goal. It goes hand in hand. If there is no connecting theme or goal, the groups fall apart.

Learning has been shown to be linked to engagement with peers in social situations over guidance from faculty mentors.

Cross reference: David F. Feldon et al., “Postdocs’ Lab Engagement Predicts Trajectories of PhD Students’ Skill Development,” Proceedings of the National Academy of Sciences 116 (October 2019): 20910–16

Are there areas where this is not the case? Are there areas where this is more the case than not?

Is it our evolution as social animals that has heightened this effect? How could this be shown? (Link this to prior note about social evolution.)

Is it the ability to scaffold out questions and answers and find their way by slowly building up experience with each other that facilitates this effect?

Could this effect be seen in annotating texts as well? If one's annotations become a conversation with the author, is there a learning benefit even when the author can't respond? By trying out writing about one's understanding of a text and seeing where the gaps are and then revisiting the text to fill them in, do we gain this same sort of peer engagement? How can we encourage students to ask questions to the author and/or themselves in the margins? How can we encourage them to further think about and explore these questions? Answer these questions over time?

A key part of the solution is not just writing the annotations down in the first place, but keeping them, reviewing over them, linking them together, revisiting them and slowly providing answers and building solutions for both themselves and, by writing them down, hopefully for others as well.

Machine learning models for diagnosing COVID-19 are not yet suitable for clinical use. (2021, March 15). University of Cambridge. https://www.cam.ac.uk/research/news/machine-learning-models-for-diagnosing-covid-19-are-not-yet-suitable-for-clinical-use

Kerzendorf, W. E., Patat, F., Bordelon, D., van de Ven, G., & Pritchard, T. A. (2020). Distributed peer review enhanced with natural language processing and machine learning. Nature Astronomy. https://doi.org/10.1038/s41550-020-1038-y

This is the process of replying to annotations. But annotation can also be leveraged for peer review of student writing.

Read classmate's annotations, respond appropriately: respectful, challenging...