The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
A proliferação de cursos online abertos e massivos tornou um desafio para o usuário selecionar um curso adequado. Assumimos uma situação em que o usuário se concentrou no conhecimento definido por algumas categorias de conhecimento. Então, saber quanto do conhecimento da categoria é abordado pelos cursos será útil na seleção do curso. Neste estudo, definimos um conceito de cobertura de categorias de conhecimento e pretendemos estimá-la de forma semiautomática. Primeiro modelamos a categoria de conhecimento e o curso como um conjunto de conceitos e, em seguida, utilizamos uma taxonomia e a ideia de centralidade para diferenciar a importância dos conceitos. Por fim, obtemos o valor da cobertura calculando quanto dos conceitos exigidos em uma categoria de conhecimento também é ensinado em um curso. Em comparação com o tratamento dos conceitos uniformemente importantes, descobrimos que nosso método proposto pode efetivamente gerar valores de cobertura mais próximos da verdade básica atribuída por especialistas no domínio.
Yiling DAI
Kyoto University
Masatoshi YOSHIKAWA
Kyoto University
Yasuhito ASANO
Kyoto University
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Yiling DAI, Masatoshi YOSHIKAWA, Yasuhito ASANO, "Estimating Knowledge Category Coverage by Courses Based on Centrality in Taxonomy" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 5, pp. 928-938, May 2020, doi: 10.1587/transinf.2019DAP0002.
Abstract: The proliferation of Massive Open Online Courses has made it a challenge for the user to select a proper course. We assume a situation in which the user has targeted on the knowledge defined by some knowledge categories. Then, knowing how much of the knowledge in the category is covered by the courses will be helpful in the course selection. In this study, we define a concept of knowledge category coverage and aim to estimate it in a semi-automatic manner. We first model the knowledge category and the course as a set of concepts, and then utilize a taxonomy and the idea of centrality to differentiate the importance of concepts. Finally, we obtain the coverage value by calculating how much of the concepts required in a knowledge category is also taught in a course. Compared with treating the concepts uniformly important, we found that our proposed method can effectively generate closer coverage values to the ground truth assigned by domain experts.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019DAP0002/_p
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@ARTICLE{e103-d_5_928,
author={Yiling DAI, Masatoshi YOSHIKAWA, Yasuhito ASANO, },
journal={IEICE TRANSACTIONS on Information},
title={Estimating Knowledge Category Coverage by Courses Based on Centrality in Taxonomy},
year={2020},
volume={E103-D},
number={5},
pages={928-938},
abstract={The proliferation of Massive Open Online Courses has made it a challenge for the user to select a proper course. We assume a situation in which the user has targeted on the knowledge defined by some knowledge categories. Then, knowing how much of the knowledge in the category is covered by the courses will be helpful in the course selection. In this study, we define a concept of knowledge category coverage and aim to estimate it in a semi-automatic manner. We first model the knowledge category and the course as a set of concepts, and then utilize a taxonomy and the idea of centrality to differentiate the importance of concepts. Finally, we obtain the coverage value by calculating how much of the concepts required in a knowledge category is also taught in a course. Compared with treating the concepts uniformly important, we found that our proposed method can effectively generate closer coverage values to the ground truth assigned by domain experts.},
keywords={},
doi={10.1587/transinf.2019DAP0002},
ISSN={1745-1361},
month={May},}
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TY - JOUR
TI - Estimating Knowledge Category Coverage by Courses Based on Centrality in Taxonomy
T2 - IEICE TRANSACTIONS on Information
SP - 928
EP - 938
AU - Yiling DAI
AU - Masatoshi YOSHIKAWA
AU - Yasuhito ASANO
PY - 2020
DO - 10.1587/transinf.2019DAP0002
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 5
JA - IEICE TRANSACTIONS on Information
Y1 - May 2020
AB - The proliferation of Massive Open Online Courses has made it a challenge for the user to select a proper course. We assume a situation in which the user has targeted on the knowledge defined by some knowledge categories. Then, knowing how much of the knowledge in the category is covered by the courses will be helpful in the course selection. In this study, we define a concept of knowledge category coverage and aim to estimate it in a semi-automatic manner. We first model the knowledge category and the course as a set of concepts, and then utilize a taxonomy and the idea of centrality to differentiate the importance of concepts. Finally, we obtain the coverage value by calculating how much of the concepts required in a knowledge category is also taught in a course. Compared with treating the concepts uniformly important, we found that our proposed method can effectively generate closer coverage values to the ground truth assigned by domain experts.
ER -