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Including Content-Based Methods in Peer-Assessment of Open-Response Questions
dc.contributor.author | Luaces Rodríguez, Óscar | |
dc.contributor.author | Díez Peláez, Jorge | |
dc.contributor.author | Alonso-Betanzos, Amparo | |
dc.contributor.author | Troncoso, Alicia | |
dc.contributor.author | Bahamonde Rionda, Antonio | |
dc.date.accessioned | 2017-01-24T11:52:02Z | |
dc.date.available | 2017-01-24T11:52:02Z | |
dc.date.issued | 2016-02 | |
dc.identifier.isbn | 978-1-4673-8493-3 | |
dc.identifier.uri | http://hdl.handle.net/10651/39387 | |
dc.description | Workshop on Data Mining for Educational Assessment and Feedback (ASSESS 2015) | spa |
dc.description.abstract | Massive Open Online Courses (MOOCs) are attracting the attention of a huge number of students all around the world. These courses include different types of assignments in order to evaluate the student’s knowledge. However, these assignments are designed to allow a straightforward automatic evaluation. But, in this way it is not possible to evaluate some skills that would require answering open-response questions. Peerassessment (the students are asked to assess other assignments), is an effective method to overcome the impossibility of having staff graders for this task. Additionally, students gain a deeper knowledge about the subject of the assignments that they have to read critically. However, the grades given by student-graders must be filtered to avoid bias due to a lack of experience in assessment tasks. There are a number of approaches to do this. In this paper we present a factorization approach that in addition to the grades given by graders is able to incorporate a representation of the contents of the responses given by students using a Vector Space Model of the assignments. So we fill the gap between peer-assessment and content-based methods that use a shallow linguistic processing. The paper includes a report of the results obtained using this approach in a real world dataset collected in 3 universities of Spain, A Coru˜ na, Pablo de Olavide at Sevilla, and Oviedo at Gij´on. The scores obtained by the method presented here were compared with those provided by the staff of these universities. We report a considerable improvement whenever we use the content-based approach. In any case, we conclude that there is no evidence that staff grading would have led to more accurate grading outcomes than the assessment produced by our models | spa |
dc.description.sponsorship | The research reported here is supported in part under grants TIN2011- 23558, TIN2012-37954 and TIN2011-28956-C02 from the MINECO (Ministerio de Economía y Competitividad, Spain), all partially supported with FEDER funds. We would also like to thank our students for grading the assignments of other colleagues in the Universities of A Coruña, Pablo de Olavide, and Oviedo | spa |
dc.format.extent | p. 273-279 | |
dc.language.iso | eng | spa |
dc.publisher | IEEE | spa |
dc.relation.ispartof | 2015 IEEE International Conference on Data Mining Workshop (ICDMW) | spa |
dc.rights | © 2016 IEEE | |
dc.title | Including Content-Based Methods in Peer-Assessment of Open-Response Questions | spa |
dc.type | conference output | spa |
dc.identifier.doi | 10.1109/ICDMW.2015.256 | |
dc.relation.projectID | TIN2011-23558, | |
dc.relation.projectID | TIN2012-37954 | |
dc.relation.projectID | TIN2011-28956-C02 | |
dc.relation.publisherversion | http://dx.doi.org/10.1109/ICDMW.2015.256 | spa |
dc.rights.accessRights | open access | spa |
dc.type.hasVersion | AM |
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