Faculty Profiles - MONDEN Akito

Papers - MONDEN Akito

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Empirical Evaluation of Mimic Software Project Data Sets for Software Effort Estimation Reviewed

Maohua GAN, Zeynep YÜCEL, Akito MONDEN, Kentaro SASAKI

IEICE Transactions on Information and Systems E103.D ( 10 ) 2094 - 2103 2020.10

Investigating effect of stimulus modality on recollection rate in e-learning systems Reviewed

Parisa Supitayakul, Zeynep Yücel, Akito Monden, Pattara Leelaprute

International Conference on Learning Technologies and Learning Environments 2020.9

ソフトウェア開発工数予測へのAutoMLの適用

田中和也, 門田暁人

日本ソフトウェア科学会第37回大会 ( 25-P ) 2020.9

ソフトウェア開発実績データセットへのデータスムージングの適用

伊永健人, 門田暁人

日本ソフトウェア科学会第37回大会 ( 27-P ) 2020.9

An Algorithm for Automatic Collation of Vocabulary Decks Based on Word Frequency Reviewed

Zeynep YÜCEL, Parisa SUPITAYAKUL, Akito MONDEN, Pattara LEELAPRUTE

IEICE Transactions on Information and Systems E103.D ( 8 ) 1865 - 1874 2020.8

Language：English Publishing type：Research paper (scientific journal) Publisher：Institute of Electronics, Information and Communications Engineers (IEICE)

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.

DOI： 10.1587/transinf.2019edp7279

Scopus

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Identification of behavioral variables for efficient representation of difficulty in vocabulary learning systems Reviewed

Parisa Supitayakul, Zeynep Yücel, Akito Monden, Pattara Leelaprute

International Journal of Learning Technologies and Learning Environments 3 ( 1 ) 51 - 60 2020.6

Estimating Level of Engagement from Ocular Landmarks Reviewed

Zeynep Yucel, Serina Koyama, Akito Monden, Mariko Sasakura

INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION 2020.5

Language：English Publishing type：Research paper (scientific journal) Publisher：TAYLOR & FRANCIS INC

E-learning offers many advantages like being economical, flexible and customizable, but also has challenging aspects such as lack of - social-interaction, which results in contemplation and sense of remoteness. To overcome these and sustain learners' motivation, various stimuli can be incorporated. Nevertheless, such adjustments initially require an assessment of engagement level. In this respect, we propose estimating engagement level from facial landmarks exploiting the facts that (i) perceptual decoupling is promoted by blinking during mentally demanding tasks; (ii) eye strain increases blinking rate, which also scales with task disengagement; (iii) eye aspect ratio is in close connection with attentional state and (iv) users' head position is correlated with their level of involvement. Building empirical models of these actions, we devise a probabilistic estimation framework. Our results indicate that high and low levels of engagement are identified with considerable accuracy, whereas medium levels are inherently more challenging, which is also confirmed by inter-rater agreement of expert coders.

DOI： 10.1080/10447318.2020.1768666

Web of Science

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行レベルバグ予測のためのWebアプリケーション Reviewed

金平拓生, 門田暁人