Hiyerarşik kümeleme modeli kullanan web tabanlı bir ödev değerlendirme sistemi. Uzun, E., Erdoğan, C., & Saygılı, A. Ejovoc (Electronic Journal of Vocational Colleges), 2016. ![Hiyerarşik kümeleme modeli kullanan web tabanlı bir ödev değerlendirme sistemi [link]](https://bibbase.org/img/filetypes/link.svg "link")
Website abstract bibtex 3 downloads Assignments are one of the most important parts of education process of students. In the classical assignment evaluation process, an assignment can be evaluated whether it is correct or not. However, for the assignments to give better contribution to education, plagiarisms committed by students should be considered. Detection of plagiarism and its extent are extremely difficult assignment evaluation procedures. In this study, in order to facilitate this procedure, a web-based application, which can combine document similarity measures with hierarchical clustering model, is introduced. This application gives the opportunity to evaluate which students submit similar assignments and the assignments’ similarity degree. Cosine, Dice and Jaccard similarity measures have been investigated in terms of document similarity calculation of this application. On the other hand, three different algorithms including Single Linkage, Complete Linkage and Average Group are examined in hierarchical clustering side. Test data which covers two education period of previous years and contains 54 different assignments of 18 different courses of 6 lecturers, are created. By using document similarity methods and hierarchical clustering algorithms, 9 different cophenetic correlation coefficients are obtained for each assignment and cophenetic correlation coefficients are calculated to test how well hierarchical clustering algorithms are . When the results were analyzed, it was discovered that Jaccard measure in document similarity and Average Group algorithm in hierarchical clustering is the best matching assignment evaluation pair.
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title = {Hiyerarşik kümeleme modeli kullanan web tabanlı bir ödev değerlendirme sistemi},
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abstract = {Assignments are one of the most important parts of education process of students. In the classical assignment evaluation process, an assignment can be evaluated whether it is correct or not. However, for the assignments to give better contribution to education, plagiarisms committed by students should be considered. Detection of plagiarism and its extent are extremely difficult assignment evaluation procedures. In this study, in order to facilitate this procedure, a web-based application, which can combine document similarity measures with hierarchical clustering model, is introduced. This application gives the opportunity to evaluate which students submit similar assignments and the assignments’ similarity degree. Cosine, Dice and Jaccard similarity measures have been investigated in terms of document similarity calculation of this application. On the other hand, three different algorithms including Single Linkage, Complete Linkage and Average Group are examined in hierarchical clustering side. Test data which covers two education period of previous years and contains 54 different assignments of 18 different courses of 6 lecturers, are created. By using document similarity methods and hierarchical clustering algorithms, 9 different cophenetic correlation coefficients are obtained for each assignment and cophenetic correlation coefficients are calculated to test how well hierarchical clustering algorithms are . When the results were analyzed, it was discovered that Jaccard measure in document similarity and Average Group algorithm in hierarchical clustering is the best matching assignment evaluation pair.},
bibtype = {article},
author = {Uzun, Erdinç and Erdoğan, Cihat and Saygılı, Ahmet},
journal = {Ejovoc (Electronic Journal of Vocational Colleges)}
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Downloads: 3
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