Machine Learning Techniques to Automate Scoring of Constructed-Response Type Assessments

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dc.contributor.author Ye, Xin en
dc.contributor.author Manoharan, Sathiamoorthy en
dc.coverage.spatial Hafnarfjordur, Iceland en
dc.date.accessioned 2019-09-30T02:31:39Z en
dc.date.issued 2018-11-15 en
dc.identifier.isbn 978-1-5386-7711-7 en
dc.identifier.issn 2472-7687 en
dc.identifier.uri http://hdl.handle.net/2292/48055 en
dc.description.abstract Automated grading tools help instructors tremendously. One challenge that needs to be addressed in constructed-response type assessments is automatic recognition of answers that are equivalent to the specimen answers but are written with different words/formats. This paper proposes schemes that use natural language processing and machine learning techniques to automatically grade short answer type assessments. The schemes compare students’ answers with specimen answers according to their semantics instead of the words in the answers. Experiments show that the proposed schemes can achieve high level accuracy while grading assessments. en
dc.publisher IEEE en
dc.relation.ispartof 2018 28th EAEEIE Annual Conference en
dc.relation.ispartofseries Proceedings of 2018 28th EAEEIE Annual Conference (EAEEIE) en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Machine Learning Techniques to Automate Scoring of Constructed-Response Type Assessments en
dc.type Conference Item en
dc.identifier.doi 10.1109/EAEEIE.2018.8534209 en
dc.rights.holder Copyright: The author en
pubs.finish-date 2018-09-28 en
pubs.start-date 2018-09-26 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Proceedings en
pubs.elements-id 777071 en
pubs.org-id Science en
pubs.org-id School of Computer Science en
dc.identifier.eissn 2376-4198 en
pubs.record-created-at-source-date 2019-07-23 en
pubs.online-publication-date 2018-09-26 en


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