dc.contributor.author | Miller, Kelly | |
dc.contributor.author | Yoo, Junehee | |
dc.contributor.author | Mazur, Eric | |
dc.contributor.author | Zyto, Sacha | |
dc.contributor.author | Karger, David R | |
dc.date.accessioned | 2018-05-16T16:32:02Z | |
dc.date.available | 2018-05-16T16:32:02Z | |
dc.date.issued | 2016-12 | |
dc.date.submitted | 2015-10 | |
dc.identifier.issn | 2469-9896 | |
dc.identifier.issn | 1554-9178 | |
dc.identifier.uri | http://hdl.handle.net/1721.1/115399 | |
dc.description.abstract | We discuss student participation in an online social annotation forum over two semesters of a flipped, introductory physics course at Harvard University. We find that students who engage in high-level discussion online, especially by providing answers to their peers' questions, make more gains in conceptual understanding than students who do not. This is true regardless of students' physics background. We find that we can steer online interaction towards more productive and engaging discussion by seeding the discussion and managing the size of the sections. Seeded sections produce higher quality annotations and a greater proportion of generative threads than unseeded sections. Larger sections produce longer threads; however, beyond a certain section size, the quality of the discussion decreases. | en_US |
dc.publisher | American Physical Society (APS) | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1103/PHYSREVPHYSEDUCRES.12.020143 | en_US |
dc.rights | Creative Commons Attribution 3.0 Unported license | en_US |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/ | en_US |
dc.source | APS | en_US |
dc.title | Analysis of student engagement in an online annotation system in the context of a flipped introductory physics class | en_US |
dc.type | Article | en_US |
dc.identifier.citation | Miller, Kelly et al. “Analysis of Student Engagement in an Online Annotation System in the Context of a Flipped Introductory Physics Class.” Physical Review Physics Education Research 12, 2 (December 2016): 020143 © 2016 American Physical Society | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | en_US |
dc.contributor.mitauthor | Zyto, Sacha | |
dc.contributor.mitauthor | Karger, David R | |
dc.relation.journal | Physical Review Physics Education Research | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2018-05-04T16:29:57Z | |
dspace.orderedauthors | Miller, Kelly; Zyto, Sacha; Karger, David; Yoo, Junehee; Mazur, Eric | en_US |
dspace.embargo.terms | N | en_US |
dc.identifier.orcid | https://orcid.org/0000-0002-0024-5847 | |
mit.license | PUBLISHER_CC | en_US |