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Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages

Research output: Contribution to Journal/Magazine › Journal article › peer-review

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Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages. / Mehler, Alexander; Hemati, Wahed; Welke, Pascal et al.
In: Frontiers in Education, Vol. 5, 562670, 03.11.2020.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Mehler, A, Hemati, W, Welke, P, Konca, M & Uslu, T 2020, 'Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages', Frontiers in Education, vol. 5, 562670. https://doi.org/10.3389/feduc.2020.562670

APA

Mehler, A., Hemati, W., Welke, P., Konca, M., & Uslu, T. (2020). Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages. Frontiers in Education, 5, Article 562670. https://doi.org/10.3389/feduc.2020.562670

Vancouver

Mehler A, Hemati W, Welke P, Konca M, Uslu T. Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages. Frontiers in Education. 2020 Nov 3;5:562670. doi: 10.3389/feduc.2020.562670

Author

Mehler, Alexander ; Hemati, Wahed ; Welke, Pascal et al. / Multiple Texts as a Limiting Factor in Online Learning : Quantifying (Dis-)similarities of Knowledge Networks across Languages. In: Frontiers in Education. 2020 ; Vol. 5.

Bibtex

@article{f07451e8ff24496491a10d2193d9692e,
title = "Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages",
abstract = " We test the hypothesis that the extent to which one obtains information on a given topic through Wikipedia depends on the language in which it is consulted. Controlling the size factor, we investigate this hypothesis for a number of 25 subject areas. Since Wikipedia is a central part of the web-based information landscape, this indicates a language-related, linguistic bias. The article therefore deals with the question of whether Wikipedia exhibits this kind of linguistic relativity or not. From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading. For this purpose, it develops a hybrid model of intra- and intertextual similarity of different parts of the information landscape and tests this model on the example of 35 languages and corresponding Wikipedias. In this way the article builds a bridge between reading research, educational science, Wikipedia research and computational linguistics. ",
keywords = "cs.CL, 68T50 (Primary) 68T30, 91F20 (Secondary), I.2.7; J.5; K.3.m",
author = "Alexander Mehler and Wahed Hemati and Pascal Welke and Maxim Konca and Tolga Uslu",
note = "40 pages, 13 figures, 5 tables",
year = "2020",
month = nov,
day = "3",
doi = "10.3389/feduc.2020.562670",
language = "English",
volume = "5",
journal = "Frontiers in Education",
issn = "2504-284X",
publisher = "Frontiers",

}

RIS

TY - JOUR

T1 - Multiple Texts as a Limiting Factor in Online Learning

T2 - Quantifying (Dis-)similarities of Knowledge Networks across Languages

AU - Mehler, Alexander

AU - Hemati, Wahed

AU - Welke, Pascal

AU - Konca, Maxim

AU - Uslu, Tolga

N1 - 40 pages, 13 figures, 5 tables

PY - 2020/11/3

Y1 - 2020/11/3

N2 - We test the hypothesis that the extent to which one obtains information on a given topic through Wikipedia depends on the language in which it is consulted. Controlling the size factor, we investigate this hypothesis for a number of 25 subject areas. Since Wikipedia is a central part of the web-based information landscape, this indicates a language-related, linguistic bias. The article therefore deals with the question of whether Wikipedia exhibits this kind of linguistic relativity or not. From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading. For this purpose, it develops a hybrid model of intra- and intertextual similarity of different parts of the information landscape and tests this model on the example of 35 languages and corresponding Wikipedias. In this way the article builds a bridge between reading research, educational science, Wikipedia research and computational linguistics.

AB - We test the hypothesis that the extent to which one obtains information on a given topic through Wikipedia depends on the language in which it is consulted. Controlling the size factor, we investigate this hypothesis for a number of 25 subject areas. Since Wikipedia is a central part of the web-based information landscape, this indicates a language-related, linguistic bias. The article therefore deals with the question of whether Wikipedia exhibits this kind of linguistic relativity or not. From the perspective of educational science, the article develops a computational model of the information landscape from which multiple texts are drawn as typical input of web-based reading. For this purpose, it develops a hybrid model of intra- and intertextual similarity of different parts of the information landscape and tests this model on the example of 35 languages and corresponding Wikipedias. In this way the article builds a bridge between reading research, educational science, Wikipedia research and computational linguistics.

KW - cs.CL

KW - 68T50 (Primary) 68T30, 91F20 (Secondary)

KW - I.2.7; J.5; K.3.m

U2 - 10.3389/feduc.2020.562670

DO - 10.3389/feduc.2020.562670

M3 - Journal article

VL - 5

JO - Frontiers in Education

JF - Frontiers in Education

SN - 2504-284X

M1 - 562670

ER -