2026-09-19T16:34:52Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1450122022-08-30T03:04:01Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Karger, David
Schoen, Alizee
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2022-08-29T16:27:11Z
2022-08-29T16:27:11Z
2022-05
2022-05-27T16:19:06.281Z
https://hdl.handle.net/1721.1/145012
NB is an online tool where students can annotate readings and lecture notes, while also discussing with other classmates and instructors. Currently, classes that are using NB have hundreds of students, which results in thousands of annotations per document. After discussing with users of NB, and looking at other platforms, we found methods for students to navigate through the large collections of annotations. These methods include having statistics for each document, the ability to endorse a comment, follow authors, and minimize the number of comments on a document. Once these features were implemented, we studied their impact on NB by collecting user engagement data and feedback.
M.Eng.
Massachusetts Institute of Technology
In Copyright - Educational Use Permitted
Copyright MIT
http://rightsstatements.org/page/InC-EDU/1.0/
Scalable methods for navigating large annotation collections in NB
Thesis
application/pdf
Master
Master of Engineering in Electrical Engineering and Computer Science
Publication
unknown
unknown
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<Abstract>NB is an online tool where students can annotate readings and lecture notes, while also discussing with other classmates and instructors. Currently, classes that are using NB have hundreds of students, which results in thousands of annotations per document. After discussing with users of NB, and looking at other platforms, we found methods for students to navigate through the large collections of annotations. These methods include having statistics for each document, the ability to endorse a comment, follow authors, and minimize the number of comments on a document. Once these features were implemented, we studied their impact on NB by collecting user engagement data and feedback.</Abstract>
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