Cross-linguistic comparison of utterance shapes in Korean- and English-learning children: An ambient language effect

Ha, Seunghee; Johnson, Cynthia J.; Oller, Kimbrough D.; Yoo, Hyun-Joo

doi:10.1016/j.infbeh.2021.101528

Cited by 11 publications

(6 citation statements)

References 37 publications

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“…Speech input from adult caregivers predicts children's lexical processing speed (Weisleder & Fernald 2013), syntactic complexity (Huttenlocher, Vasilyeva, Cymerman, & Levine 2002), expressive and receptive vocabulary sizes (Hoff 2003;Mahr and Edwards 2018), and phonological development (Cristia 2011, Ferjan Ramírez, Lytle, Fish, & Kuhl 2019, Garcia-Sierra, Ramírez-Esparza, & Kuhl 2016, Liu et al 2003. Infants and young children are capable of tracking statistical patterns from their input, such as phoneme or word co-occurrences, and reflecting those patterns during phoneme discrimination and word segmentation tasks (Maye, Werker, & Gerken 2002, Pelucchi, Hay, & Saffran 2009, consonant production (Edwards & Beckman 2008, Zamuner 2009, and early, pre-lexical vocalizations (de Boysson-Bardies, Vihman, & de Boysson-Bardies 1991, Ha, Johnson, Oller, & Yoo 2021.…”

Section: Environmental Effects In Language Developmentmentioning

confidence: 99%

Language exposure predicts children’s phonetic patterning: Evidence from language shift

Cychosz¹

2022

Language

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Although understanding the role of the environment is central to language acquisition theory, rarely has this been studied for children's phonetic development; and receptive and expressive language experiences in the environment are not distinguished. This last distinction may be crucial for child speech production in particular because production requires coordination of low-level speech-motor planning with high-level linguistic knowledge. In this study, the role of the environment is evaluated in a novel way-by studying phonetic development in a bilingual community undergoing rapid language shift. This sociolinguistic context provides a naturalistic gradient of the amount of children's exposure to two languages and the ratio of expressive to receptive experiences. A largescale child language corpus encompassing over 500 hours of naturalistic South Bolivian Quechua and Spanish speech was efficiently annotated for children's and their caregivers' bilingual language use. These estimates were correlated with children's patterns in a series of speech production tasks. The role of the environment varied by outcome: children's expressive language experience best predicted their performance on a coarticulation-morphology measure while their receptive experience predicted performance on a lower-level measure of vowel variability. Overall these bilingual exposure effects suggest a pathway for children's role in language change whereby language shift can result in different learning outcomes within a single speech community. Appropriate ways to model language exposure in development are discussed.

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Section: Environmental Effects In Language Developmentmentioning

confidence: 99%

Language exposure predicts children’s phonetic patterning: Evidence from language shift

Cychosz¹

2022

Language

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“…The quantity and quality of speech input from adult caregivers predicts children's lexical processing speed (Weisleder & Fernald, 2013), syntactic complexity (Huttenlocher, Vasilyeva, Cymerman, & Levine, 2002), expressive and receptive vocabulary sizes (Hoff 2003;Mahr and Edwards 2017), babbling complexity (Ferjan Ramírez, Lytle, Fish, and Kuhl 2019;Ramírez-Esparza, García-Sierra, and Kuhl 2014), and speech perception (Cristia, 2011;Garcia-Sierra, Ramírez-Esparza, & Kuhl, 2016;Liu et al, 2003). Infants and young children are capable of tracking statistical patterns from their input, such as phoneme or word co-occurrences, and reflecting those patterns during phoneme discrimination and word segmentation tasks (Maye, Werker, & Gerken, 2002;Pelucchi, Hay, & Saffran, 2009), consonant production (Edwards & Beckman, 2008;Zamuner, 2009), and early, pre-lexical vocalizations (de Boysson-Bardies, Vihman, & de Boysson-Bardies, 1991;Ha, Johnson, Oller, & Yoo, 2021).…”

Section: Environmental Effects In Language Developmentmentioning

confidence: 99%

Language exposure predicts children’s phonetic patterning: Evidence from language shift

Cychosz¹

2021

Preprint

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Although understanding the role of the environment is central to language acquisition theory, rarely has this been studied for children’s phonetic development; and receptive and expressive language experiences in the environment are not distinguished. This last distinction may be crucial for child speech production in particular because production requires coordination of low-level speech-motor planning with high-level linguistic knowledge. In this study, the role of the environment is evaluated in a novel way—by studying phonetic development in a bilingual community undergoing rapid language shift. This sociolinguistic context provides a naturalistic gradient of the amount of children’s exposure to two languages and the ratio of expressive to receptive experiences. A largescale child language corpus encompassing over 500 hours of naturalistic South Bolivian Quechua and Spanish speech was efficiently annotated for children’s and their caregivers’ bilingual language use. These estimates were correlated with children’s patterns in a series of speech production tasks. The role of the environment varied by outcome: children’s expressive language experience best predicted their performance on a coarticulation-morphology measure while their receptive experience predicted performance on a lower-level measure of vowel variability. Overall these bilingual exposure effects suggest a pathway for children’s role in language change whereby language shift can result in different learning outcomes within a single speech community. Appropriate ways to model language exposure in development are discussed.

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“…A study has been conducted on the Education 4.0 chatbots (a bot designed to converse with human beings) to improve English grammar skills in Korea [ 36 ]. The study’s objective was to find out the impact of the Education 4.0 chatbot in improving foreign language learning of university learners.…”

Section: Introductionmentioning

confidence: 99%

Impact of Education 4.0 among engineering students for learning English language

et al. 2022

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Education 4.0 is considered a significant technology for teaching and learning. The present study aims to explore the impact and the importance of Education 4.0 for improving English language learning in the perception of students in India, especially Hyderabad City. Moreover, Education 4.0 has bloomed as an important need to move along with the fast-growing education system of the world. But, it is a fact that many Indian students have complications and difficulties in learning English due to many reasons. The traditional methods of teaching are one of those reasons. Students learn only through the conventional methods, and they may find it boring and not effective. The education and mode of teaching have changed a lot, and it has attained a newer form of using the technology. Moreover, in the current era, where work from home and online teaching has become a new normal throughout the world, the technology used for teaching is inseparable. Hence, the authors are motivated to study the impact of Education 4.0 on improving English learning from Hyderabad, India. The methodology of the study has applied quantitative research. The study has employed pre-tested, close-ended questionnaires and post-assessment to gather data from the respondents to understand students’ performance in English language learning after implying Education 4.0. The five-point Likert scale has been used to analyse the collected data and to get mean values of responses. The total number of respondents is 145 students who pursue their engineering degrees in the select region. Among the collected data, most of them were from urban. The data obtained from the respondents proved that there is a direct correlation between the students’ perception and implementation of Education 4.0 in learning the English language. This study indicated that the respondents upheld Education 4.0 to improve English language learning in Hyderabad, India.

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Cross-linguistic comparison of utterance shapes in Korean- and English-learning children: An ambient language effect

Cited by 11 publications

References 37 publications

Language exposure predicts children’s phonetic patterning: Evidence from language shift

Language exposure predicts children’s phonetic patterning: Evidence from language shift

Language exposure predicts children’s phonetic patterning: Evidence from language shift

Impact of Education 4.0 among engineering students for learning English language

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