Analysis of Clustering Evaluation Considering Features of Item Response Data Using Data Mining Technique for Setting Cut-Off Scores
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Byoungwook | - |
dc.contributor.author | Kim, Jamee | - |
dc.contributor.author | Yi, Gangman | - |
dc.date.accessioned | 2021-09-03T06:37:19Z | - |
dc.date.available | 2021-09-03T06:37:19Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-05 | - |
dc.identifier.issn | 2073-8994 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/83565 | - |
dc.description.abstract | The setting of standards is a critical process in educational evaluation, but it is time-consuming and expensive because it is generally conducted by an education experts group. The purpose of this paper is to find a suitable cluster validity index that considers the futures of item response data for setting cut-off scores. In this study, nine representative cluster validity indexes were used to evaluate the clustering results. Cohen's kappa coefficient is used to check the conformity between a set cut-off score using four clustering techniques and a cut-off score set by experts. We compared the cut-off scores by each cluster validity index and by a group of experts. The experimental results show that the entropy-based method considers the features of item response data, so it has a realistic possibility of applying a clustering evaluation method to the setting of standards in criterion referenced evaluation. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | MDPI | - |
dc.subject | AGREEMENT | - |
dc.title | Analysis of Clustering Evaluation Considering Features of Item Response Data Using Data Mining Technique for Setting Cut-Off Scores | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Byoungwook | - |
dc.contributor.affiliatedAuthor | Kim, Jamee | - |
dc.identifier.doi | 10.3390/sym9050062 | - |
dc.identifier.scopusid | 2-s2.0-85019268110 | - |
dc.identifier.wosid | 000404181900003 | - |
dc.identifier.bibliographicCitation | SYMMETRY-BASEL, v.9, no.5 | - |
dc.relation.isPartOf | SYMMETRY-BASEL | - |
dc.citation.title | SYMMETRY-BASEL | - |
dc.citation.volume | 9 | - |
dc.citation.number | 5 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Science & Technology - Other Topics | - |
dc.relation.journalWebOfScienceCategory | Multidisciplinary Sciences | - |
dc.subject.keywordPlus | AGREEMENT | - |
dc.subject.keywordAuthor | clustering data mining | - |
dc.subject.keywordAuthor | cut-off scores | - |
dc.subject.keywordAuthor | item response data | - |
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