Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning

Suzuki, Yuichi; Nakata, Tatsuya; He, Xuehong (Stella)

doi:10.1017/s095834402400020x

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Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning

Yuichi Suzuki

, Tatsuya Nakata

, Xuehong (Stella) He

ReCALL, Pages: 1 - 18

Swansea University Author: Xuehong (Stella) He

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DOI (Published version): 10.1017/s095834402400020x

Abstract

The aim of this study was to contribute to the field of computer-assisted language learning (CALL) by investigating the individualization of intentional vocabulary learning. A total of 118 Japanese-speaking university students studied 20 low-frequency English words using flashcard software over two...

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Published in:	ReCALL
ISSN:	0958-3440 1474-0109
Published:	Cambridge University Press (CUP) 2024
Online Access:	Check full text
URI:	https://cronfa.swan.ac.uk/Record/cronfa67957
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The participants practiced retrieval of vocabulary under different learning schedules, with short or long time intervals between encounters of the same word in each learning session: Short–Short, Short–Long, Long–Short, and Long–Long. Two individual difference measures – learning efficiency and language aptitude – were examined as predictors of long-term second language (L2) vocabulary retention. Learning efficiency was operationalized as the number of trials needed to reach a learning criterion in each session, whereas a component of aptitude (rote memory ability) was measured by a subtest of Language Aptitude Battery for the Japanese. Multiple regression and dominance analyses were conducted to evaluate the relative importance of learning efficiency and language aptitude in predicting delayed vocabulary posttest scores. The results revealed that learning efficiency in the second learning session was the strongest predictor of vocabulary retention. 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spelling	v2 67957 2024-10-10 Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning 1c41e6239b6d4e82cbb36333088e3293 0000-0002-6419-0187 Xuehong (Stella) He Xuehong (Stella) He true false 2024-10-10 CACS The aim of this study was to contribute to the field of computer-assisted language learning (CALL) by investigating the individualization of intentional vocabulary learning. A total of 118 Japanese-speaking university students studied 20 low-frequency English words using flashcard software over two learning sessions. The participants practiced retrieval of vocabulary under different learning schedules, with short or long time intervals between encounters of the same word in each learning session: Short–Short, Short–Long, Long–Short, and Long–Long. Two individual difference measures – learning efficiency and language aptitude – were examined as predictors of long-term second language (L2) vocabulary retention. Learning efficiency was operationalized as the number of trials needed to reach a learning criterion in each session, whereas a component of aptitude (rote memory ability) was measured by a subtest of Language Aptitude Battery for the Japanese. Multiple regression and dominance analyses were conducted to evaluate the relative importance of learning efficiency and language aptitude in predicting delayed vocabulary posttest scores. The results revealed that learning efficiency in the second learning session was the strongest predictor of vocabulary retention. Language aptitude, however, did not significantly predict vocabulary retention. Moreover, the predictive power of learning efficiency increased when the data were analyzed within each learning schedule, underscoring the need to assess learners’ abilities under specific learning conditions for optimizing their computer-assisted learning performance. These findings not only inform the development of more effective, individualized CALL systems for L2 acquisition but also emphasize the importance of gauging individuals’ abilities such as learning efficiency in a more flexible, context-sensitive manner. Journal Article ReCALL 0 1 18 Cambridge University Press (CUP) 0958-3440 1474-0109 vocabulary learning; individualized CALL; language aptitude; learning efficiency; practice distribution 10 10 2024 2024-10-10 10.1017/s095834402400020x COLLEGE NANME Culture and Communications School COLLEGE CODE CACS Swansea University Another institution paid the OA fee This research was supported by JSPS KAKENHI grant (23K20482), awarded to the first author, and JSPS KAKENHI grant (22K00743), awarded to the second author. We greatly appreciate the invaluable suggestions given by the editor and anonymous reviewers. We would also like to thank Dr Keiko Hanzawa for her help with data collection. 2024-11-07T14:52:21.4043958 2024-10-10T16:30:41.1377295 Faculty of Humanities and Social Sciences School of Culture and Communication - English Language, Tesol, Applied Linguistics Yuichi Suzuki 0000-0002-1197-0315 1 Tatsuya Nakata 0000-0002-1152-653x 2 Xuehong (Stella) He 0000-0002-6419-0187 3 67957__32886__101af3b3ee4e428890eb1f7b57793171.pdf 67957.VoR.pdf 2024-11-07T14:45:28.0795696 Output 422957 application/pdf Version of Record true © The Author(s), 2024 This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence. true eng https://creativecommons.org/licenses/by/4.0/
title	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning
spellingShingle	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning Xuehong (Stella) He
title_short	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning
title_full	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning
title_fullStr	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning
title_full_unstemmed	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning
title_sort	Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning
author_id_str_mv	1c41e6239b6d4e82cbb36333088e3293
author_id_fullname_str_mv	1c41e6239b6d4e82cbb36333088e3293_***_Xuehong (Stella) He
author	Xuehong (Stella) He
author2	Yuichi Suzuki Tatsuya Nakata Xuehong (Stella) He
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description	The aim of this study was to contribute to the field of computer-assisted language learning (CALL) by investigating the individualization of intentional vocabulary learning. A total of 118 Japanese-speaking university students studied 20 low-frequency English words using flashcard software over two learning sessions. The participants practiced retrieval of vocabulary under different learning schedules, with short or long time intervals between encounters of the same word in each learning session: Short–Short, Short–Long, Long–Short, and Long–Long. Two individual difference measures – learning efficiency and language aptitude – were examined as predictors of long-term second language (L2) vocabulary retention. Learning efficiency was operationalized as the number of trials needed to reach a learning criterion in each session, whereas a component of aptitude (rote memory ability) was measured by a subtest of Language Aptitude Battery for the Japanese. Multiple regression and dominance analyses were conducted to evaluate the relative importance of learning efficiency and language aptitude in predicting delayed vocabulary posttest scores. The results revealed that learning efficiency in the second learning session was the strongest predictor of vocabulary retention. Language aptitude, however, did not significantly predict vocabulary retention. Moreover, the predictive power of learning efficiency increased when the data were analyzed within each learning schedule, underscoring the need to assess learners’ abilities under specific learning conditions for optimizing their computer-assisted learning performance. These findings not only inform the development of more effective, individualized CALL systems for L2 acquisition but also emphasize the importance of gauging individuals’ abilities such as learning efficiency in a more flexible, context-sensitive manner.
published_date	2024-10-10T14:52:19Z
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Efficiency trumps aptitude: Individualizing computer-assisted second language vocabulary learning

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