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An empirical investigation of neural methods for content scoring of science explanations.

, , , , , , and . BEA@ACL, page 135-144. Association for Computational Linguistics, (2020)

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Co-ML: Collaborative Machine Learning Model Building for Developing Dataset Design Practices., , , , , , , and . CoRR, (2023)Supporting Student Choice and Collaborative Decision-Making During Science Inquiry Investigations.. CSCL (2), page 291-292. International Society of the Learning Sciences, LuLu, Amazon, (2013)An empirical investigation of neural methods for content scoring of science explanations., , , , , , and . BEA@ACL, page 135-144. Association for Computational Linguistics, (2020)The Idea Manager: A Tool to Scaffold Students in Documenting, Sorting, And Distinguishing Ideas During Science Inquiry., , , , , and . ICLS, International Society of the Learning Sciences, (2012)Collaborative Machine Learning Model Building with Families Using Co-ML., , , , , , and . IDC, page 40-51. ACM, (2023)Towards a taxonomy of explanations in science education., , , , , , and . ICLS, page 493-495. International Society of the Learning Sciences / ACM DL, (2010)Examining the Impact of Student Choice in Online Science Investigations., , and . ICLS, International Society of the Learning Sciences, (2020)Impact of Choice on Students' Use of an Experimentation Model for Investigating Ideas About Thermodynamics., and . CSCL, International Society of the Learning Sciences, (2019)Collaboration as Scaffolding: Learning Together with Dynamic, Interactive Scientific Visualizations and Computer Models., , , , , , , , , and 9 other author(s). CSCL, International Society of the Learning Sciences, (2011)Impact of a Teacher Action Planner that Captures Student Ideas on Teacher Customization Decisions., , , , , and . ICLS, International Society of the Learning Sciences, (2020)