IEICE TRANSACTIONS on Information
An Algorithm for Automatic Collation of Vocabulary Decks Based on Word Frequency
Summary :
This study focuses on computer based foreign language vocabulary learning systems. Our objective is to automatically build vocabulary decks with desired levels of relative difficulty relations. To realize this goal, we exploit the fact that word frequency is a good indicator of vocabulary difficulty. Subsequently, for composing the decks, we pose two requirements as uniformity and diversity. Namely, the difficulty level of the cards in the same deck needs to be uniform enough so that they can be grouped together and difficulty levels of the cards in different decks need to be diverse enough so that they can be grouped in different decks. To assess uniformity and diversity, we use rank-biserial correlation and propose an iterative algorithm, which helps in attaining desired levels of uniformity and diversity based on word frequency in daily use of language. In experiments, we employed a spaced repetition flashcard software and presented users various decks built with the proposed algorithm, which contain cards from different content types. From users' activity logs, we derived several behavioral variables and examined the polyserial correlation between these variables and difficulty levels across different word classes. This analysis confirmed that the decks compiled with the proposed algorithm induce an effect on behavioral variables in line with the expectations. In addition, a series of experiments with decks involving varying content types confirmed that this relation is independent of word class.
- Publication
- IEICE TRANSACTIONS on Information Vol.E103-D No.8 pp.1865-1874
- Publication Date
- 2020/08/01
- Publicized
- 2020/05/07
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2019EDP7279
- Type of Manuscript
- PAPER
- Category
- Educational Technology
Authors
Zeynep YÜCEL
Okayama University
Parisa SUPITAYAKUL
Okayama University
Akito MONDEN
Okayama University
Pattara LEELAPRUTE
Kasetsart University
Keyword
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Zeynep YÜCEL, Parisa SUPITAYAKUL, Akito MONDEN, Pattara LEELAPRUTE, "An Algorithm for Automatic Collation of Vocabulary Decks Based on Word Frequency" in IEICE TRANSACTIONS on Information,
vol. E103-D, no. 8, pp. 1865-1874, August 2020, doi: 10.1587/transinf.2019EDP7279.
Abstract: This study focuses on computer based foreign language vocabulary learning systems. Our objective is to automatically build vocabulary decks with desired levels of relative difficulty relations. To realize this goal, we exploit the fact that word frequency is a good indicator of vocabulary difficulty. Subsequently, for composing the decks, we pose two requirements as uniformity and diversity. Namely, the difficulty level of the cards in the same deck needs to be uniform enough so that they can be grouped together and difficulty levels of the cards in different decks need to be diverse enough so that they can be grouped in different decks. To assess uniformity and diversity, we use rank-biserial correlation and propose an iterative algorithm, which helps in attaining desired levels of uniformity and diversity based on word frequency in daily use of language. In experiments, we employed a spaced repetition flashcard software and presented users various decks built with the proposed algorithm, which contain cards from different content types. From users' activity logs, we derived several behavioral variables and examined the polyserial correlation between these variables and difficulty levels across different word classes. This analysis confirmed that the decks compiled with the proposed algorithm induce an effect on behavioral variables in line with the expectations. In addition, a series of experiments with decks involving varying content types confirmed that this relation is independent of word class.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2019EDP7279/_p
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@ARTICLE{e103-d_8_1865,
author={Zeynep YÜCEL, Parisa SUPITAYAKUL, Akito MONDEN, Pattara LEELAPRUTE, },
journal={IEICE TRANSACTIONS on Information},
title={An Algorithm for Automatic Collation of Vocabulary Decks Based on Word Frequency},
year={2020},
volume={E103-D},
number={8},
pages={1865-1874},
abstract={This study focuses on computer based foreign language vocabulary learning systems. Our objective is to automatically build vocabulary decks with desired levels of relative difficulty relations. To realize this goal, we exploit the fact that word frequency is a good indicator of vocabulary difficulty. Subsequently, for composing the decks, we pose two requirements as uniformity and diversity. Namely, the difficulty level of the cards in the same deck needs to be uniform enough so that they can be grouped together and difficulty levels of the cards in different decks need to be diverse enough so that they can be grouped in different decks. To assess uniformity and diversity, we use rank-biserial correlation and propose an iterative algorithm, which helps in attaining desired levels of uniformity and diversity based on word frequency in daily use of language. In experiments, we employed a spaced repetition flashcard software and presented users various decks built with the proposed algorithm, which contain cards from different content types. From users' activity logs, we derived several behavioral variables and examined the polyserial correlation between these variables and difficulty levels across different word classes. This analysis confirmed that the decks compiled with the proposed algorithm induce an effect on behavioral variables in line with the expectations. In addition, a series of experiments with decks involving varying content types confirmed that this relation is independent of word class.},
keywords={},
doi={10.1587/transinf.2019EDP7279},
ISSN={1745-1361},
month={August},}
Copy
TY - JOUR
TI - An Algorithm for Automatic Collation of Vocabulary Decks Based on Word Frequency
T2 - IEICE TRANSACTIONS on Information
SP - 1865
EP - 1874
AU - Zeynep YÜCEL
AU - Parisa SUPITAYAKUL
AU - Akito MONDEN
AU - Pattara LEELAPRUTE
PY - 2020
DO - 10.1587/transinf.2019EDP7279
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E103-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2020
AB - This study focuses on computer based foreign language vocabulary learning systems. Our objective is to automatically build vocabulary decks with desired levels of relative difficulty relations. To realize this goal, we exploit the fact that word frequency is a good indicator of vocabulary difficulty. Subsequently, for composing the decks, we pose two requirements as uniformity and diversity. Namely, the difficulty level of the cards in the same deck needs to be uniform enough so that they can be grouped together and difficulty levels of the cards in different decks need to be diverse enough so that they can be grouped in different decks. To assess uniformity and diversity, we use rank-biserial correlation and propose an iterative algorithm, which helps in attaining desired levels of uniformity and diversity based on word frequency in daily use of language. In experiments, we employed a spaced repetition flashcard software and presented users various decks built with the proposed algorithm, which contain cards from different content types. From users' activity logs, we derived several behavioral variables and examined the polyserial correlation between these variables and difficulty levels across different word classes. This analysis confirmed that the decks compiled with the proposed algorithm induce an effect on behavioral variables in line with the expectations. In addition, a series of experiments with decks involving varying content types confirmed that this relation is independent of word class.
ER -
English
