Hostname: page-component-cb9f654ff-hn9fh Total loading time: 0 Render date: 2025-07-31T09:15:41.689Z Has data issue: false hasContentIssue false
  • English
  • Français

THE ROLE OF INPUT VARIABILITY AND LEARNER AGE IN SECOND LANGUAGE VOCABULARY LEARNING

Published online by Cambridge University Press:  20 June 2019

Ruta Sinkeviciute ,
Helen Brown ,
Gwen Brekelmans  and
Elizabeth Wonnacott
Ruta Sinkeviciute
Affiliation:
University College London
Helen Brown
Affiliation:
Nottingham Trent University
Gwen Brekelmans
Affiliation:
University College London
Elizabeth Wonnacott*
Affiliation:
University College London
*
*Correspondence concerning this article should be addressed to Elizabeth Wonnacott, Psychology and Language Sciences, University College London, Gower Street, London, WC1E 6BT, UK. E-mail: e.wonnacott@ucl.ac.uk
Get access Rights & Permissions [Opens in a new window]

Abstract

Input variability is key in many aspects of linguistic learning, yet variability increases input complexity, which may cause difficulty in some learning contexts. The current work investigates this trade-off by comparing speaker variability effects on L2 vocabulary learning in different age groups. Existing literature suggests that speaker variability benefits L2 vocabulary learning in adults, but this may not be the case for younger learners. In this study native English-speaking adults, 7- to 8-year-olds, and 10- to 11-year-olds learned six novel Lithuanian words from a single speaker, and six from eight speakers. In line with previous research, adults showed better production of the multispeaker items at test. No such benefit was found for either group of children, either in production or comprehension. Children also had greater difficulties in processing multiple-speaker cues during training. We conclude that age-related capacity limitations may constrain the ability to utilize speaker variability when learning words in a new language.

Information

Type
Research Article
Information
Studies in Second Language Acquisition , Volume 41 , Issue 4 , September 2019 , pp. 795 - 820
Open Practices
Open materials
Copyright
Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

Footnotes

This research was supported by the Economic and Social Research Council (grant number: ES/K013637/1, awarded to EW and HB). We would like to thank the Lithuanian speakers who agreed to lend their voices for the stimuli preparation as well as Agne Sinkeviciute for pilot testing.

The experiment in this article earned an Open Data badge for transparent practices. The materials are available at https://osf.io/2vec3/.

References

REFERENCES

Alloway, T. P., Gathercole, S. E., & Pickering, S. J. (2006). Verbal and visuo-spatial short-term and working memory in children: Are they separable? Child Development, 77, 1698–1716. https://doi.org/10.1111/j.1467-8624.2006.00968.x.CrossRefGoogle Scholar
Apfelbaum, K. S., & McMurray, B. (2011). Using variability to guide dimensional weighting: Associative mechanisms in early word learning. Cognitive Science, 35, 1105–1138. https://doi.rog/10.1111/j.1551-6709.2011.01181.x.CrossRefGoogle Scholar
Baayen, R. H., Davidson, D. J., & Bates, D. M. (2008). Mixed-effects modelling with crossed random effects for subjects and items. Journal of Memory and Language, 59, 390–412. https://doi.org/10.1016/j.jml.2007.12.005.CrossRefGoogle Scholar
Barcroft, J. (2001). Acoustic variation and lexical acquisition. Language Learning, 51, 563–590. https://doi.org/10.1111/0023-8333.00168.CrossRefGoogle Scholar
Barcroft, J., & Sommers, M. S. (2005). Effects of acoustic variability on second language vocabulary learning. Studies in Second Language Acquisition, 27, 387–414. https://doi.org/10.1017/s0272263105050175.CrossRefGoogle Scholar
Barcroft, J., & Sommers, M. S. (2014). Effects of variability in fundamental frequency on L2 vocabulary learning. Studies in Second Language Acquisition, 36, 423–449. https://doi.org/10.1017/s0272263113000582.CrossRefGoogle Scholar
Barr, D. J., Levy, R., Scheepers, C., & Tily, H. J. (2013). Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language, 44, 255–278. https://doi.org/10.1016/j.jml.2012.11.001.CrossRefGoogle Scholar
Bates, D., Maechler, M., & Bolker, B. (2013). lme4: Linear mixed-effects models using S4 classes. R package version 0.999999-0.Google Scholar
Boersma, P., & Weenink, D. (2017). Praat: Doing phonetics by computer [Computer software]. Version 6.0.36. Retrieved from http://www.praat.org/.Google Scholar
Bradlow, A. R., Akahane-Yamada, R., Pisoni, D. B., & Tohkura, Y. (1999). Training Japanese listeners to identify English /r/ and /l/: Long-term retention of learning in perception and production. Perception and Psychophysics, 61, 977–985. https://doi.org/10.3758/bf03206911.CrossRefGoogle Scholar
Brooks, P. J., Kempe, V., & Sionov, A. (2006). The role of learner and input variables in learning inflectional morphology. Applied Psycholinguistics, 27, 185–209. https://doi.org/10.1017/S0142716406060243.CrossRefGoogle Scholar
Bybee, J. (1995). Regular morphology and the lexicon. Language and Cognitive Processes, 10, 425–455. https://doi.org/10.1080/01690969508407111.CrossRefGoogle Scholar
Case, R., Kurland, D. M., & Goldberg, J. (1982). Operational efficiency and the growth of short-term memory span. Journal of Experimental Child Psychology, 33, 386–404. doi:10.1016/0022-0965(82)90054-6.CrossRefGoogle Scholar
Children’s Printed Word Database. (2002). Retrieved from http://www.essex.ac.uk/psychology/cpwd/.Google Scholar
Clopper, C. G., & Pisoni, D. B. (2004). Effects of talker variability on perceptual learning of dialects. Language and Speech, 47, 207–239. https://doi.org/10.1177/00238309040470030101.CrossRefGoogle Scholar
Creel, S. C., & Bregman, M. R. (2011). How talker identity relates to language processing. Language and Linguistics Compass, 5, 190–204. https://doi.org/10.1111/j.1749-818X.2011.00276.x.CrossRefGoogle Scholar
Dienes, Z. (2008). Understanding psychology as a science: An introduction to scientific and statistical inference. Basingstoke, UK: Palgrave Macmillan.Google Scholar
Dienes, Z. (2014). Using Bayes to get the most out of non-significant results. Frontiers in Psychology, 5, 781. doi: 10.3389/fpsyg.2014.00781.CrossRefGoogle Scholar
Dienes, Z. (2015). How Bayesian statistics are needed to determine whether mental states are unconscious. In Overgaard, M. (Ed.), Behavioural methods in consciousness research (pp. 199–220). Oxford, UK: Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199688890.003.0012.CrossRefGoogle Scholar
Galle, M., Apfelbaum, K., & McMurray, B. (2015). The role of single talker acoustic variation in early word learning. Language Learning and Development, 11, 66–79. https://doi.org/10.1080/15475441.2014.895249.CrossRefGoogle Scholar
Giannakopoulou, A., Brown, H., Clayards, M., & Wonnacott, E. (2017). High or low? Comparing high- and low-variability phonetic training in adult and child second language learners. PeerJ, 5, e3209. https://doi.org/10.7717/peerj.3209.CrossRefGoogle Scholar
Goldinger, S. D., Pisoni, D. B., & Logan, J. S. (1991). On the nature of talker variability effects on recall of spoken word lists. Journal of Experimental Psychology: Learning, Memory and Cognition, 17, 152–162. doi.org/10.1037//0278-7393.17.1.152.Google Scholar
Gomez, R. L. (2002). Variability and detection of invariant structure. Psychological Science, 13, 431–436. https://doi.org/10.1111/1467-9280.00476.CrossRefGoogle Scholar
Henderson, L. M., Weighall, A., Brown, H., & Gaskell, M. G. (2013). On-line lexical competition during spoken word recognition and word learning in children and adults. Child Development, 84, 1668–1685. https://doi.org/10.1111/cdev.12067.CrossRefGoogle Scholar
Iverson, P., Pinet, M., & Evans, B. G. (2012). Auditory training for experienced and inexperienced second-language learners: Native French speakers learning English vowels. Applied Psycholinguistics, 33, 145–160. https://doi.org/10.1017/S0142716411000300.CrossRefGoogle Scholar
Jaeger, T. F. (2008). Categorical data analysis: Away from ANOVAs (transformation or not) and towards logit mixed models. Journal of Memory and Language, 59, 434–446. https://doi.org/10.1016/j.jml.2007.11.007.CrossRefGoogle Scholar
Kuperman, V., Stadthagen-Gonzalez, H., & Brysbaert, M. (2012). Age-of-acquisition ratings for 30,000 English words. Behavior Research Methods, 44, 978–990. https://doi.org/10.3758/s13428-012-0210-4.CrossRefGoogle Scholar
Lively, S. E., Logan, J. S., & Pisoni, D. B. (1993). Training Japanese listeners to identify English /r/ and /l/. II: The role of phonetic environment and talker variability in learning new perceptual categories. Journal of the Acoustical Society of America, 94, 1242–1255. https://doi.org/10.1121/1.408177.CrossRefGoogle Scholar
Logan, J. S., Lively, S. E., & Pisoni, D. B. (1991). Training Japanese listeners to identify English /r/ and /l/: A first report. Journal of the Acoustical Society of America, 89, 874–886. https://doi.org/10.1121/1.1894649.CrossRefGoogle Scholar
Martin, C. S., Mullennix, J. W., Pisoni, D. B., & Summers, W. V. (1989). Effects of talker variability on recall of spoken word lists. Journal of Experimental Psychology: Learning, Memory and Cognition, 15, 676–684. https://doi.org/10.1037//0278-7393.15.4.676.Google Scholar
Matuschek, H., Kliegl, R., Vasishth, S., Baayen, H., & Bates, D. (2017). Balancing type I error and power in linear mixed models. Journal of Memory and Language, 94, 305–315. https://doi.org/10.1016/j.jml.2017.01.001.CrossRefGoogle Scholar
Morey, R. D. (2008). Confidence intervals from normalized data: A correction to Cousineau (2005). Tutorial in Quantitative Methods for Psychology, 4, 61–64. https://doi.org/10.20982/tqmp.04.2.p061.CrossRefGoogle Scholar
Mullennix, J. W., Pisoni, D. B., & Martin, C. S. (1989). Some effects of talker variability on spoken word recognition. Journal of the Acoustical Society of America, 85, 365–378. https://doi.org/10.1121/1.397688.CrossRefGoogle Scholar
Newman, R. S. (2008). The level of detail in infants’ word learning. Current Directions in Psychological Science, 17, 229–232. https://doi.org/10.1111%2Fj.1467-8721.2008.00580.x.CrossRefGoogle Scholar
Nusbaum, H. C., & Morin, T. M. (1992). Paying attention to differences among talkers. In Tohkura, Y., Sagisaka, Y., & Vatikiotis-Bateson, E. (Eds.), Speech perception, speech production, and linguistic structure (pp. 113–134). Tokyo, Japan: OHM.Google Scholar
Plunkett, K., & Marchman, V. (1991). U-shaped learning and frequency effects in a multi-layered perceptron: Implications for child language acquisition. Cognition, 38, 43–102. https://doi.org/10.1016/0010-0277(91)90022-V.CrossRefGoogle Scholar
Pruitt, J. S. (1993). Comments on ‘Training Japanese listeners to identify /r/ and /l/: A first report’ [Logan, J. S., Lively, S. E., and Pisoni, D. B., Journal of the Acoustical Society of America, 89, 874–886 (1991)]. Journal of the Acoustical Society of America, 94, 1146–1147. https://doi.org/10.1121/1.406962.Google Scholar
Quené, H., & van den Bergh, H. (2008). Examples of mixed-effects modelling with crossed random effects and with binomial data. Journal of Memory and Language, 59, 413–425. https://doi.org/10.1016/j.jml.2008.02.002.CrossRefGoogle Scholar
Ramscar, M., & Baayen, R. H. (2013). Production, comprehension, and synthesis: A communicative perspective on language. Frontiers in Language Sciences, 4. https://doi.org/10.3389/fpsyg.2013.00233.Google Scholar
Ramscar, M., Yarlett, D., Dye, M., Denny, K., & Thorpe, K. (2010). The effects of feature label-order and their implications for symbolic learning. Cognitive Science, 34, 909–957. https://doi.org/10.1111/j.1551-6709.2009.01092.x.CrossRefGoogle Scholar
R Core Team. (2016). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing. Retrieved from https://www.R-project.org/.Google Scholar
Richtsmeier, P. T., Gerken, L., Goffman, L., & Hogan, T. (2009). Statistical frequency in perception affects children’s lexical production. Cognition, 111, 372–377. https://doi.org/10.1016/j.cognition.2009.02.009.CrossRefGoogle Scholar
Rost, G. C., & McMurray, B. (2009). Speaker variability augments phonological processing in early word learning. Developmental Science, 12, 339–349. https://doi.org/10.1111/j.1467-7687.2008.00786.x.CrossRefGoogle Scholar
Rost, G. C., & McMurray, B. (2010). Finding the signal by adding noise: The role of noncontrastive phonetic variability in early word learning. Infancy, 15, 608–635. https://doi.org/10.1111/j.1532-7078.2010.00033.x.CrossRefGoogle Scholar
Ryalls, B. O., & Pisoni, D. B. (1997). The effect of talker variability on word recognition in preschool children. Developmental Psychology, 33, 441–452. doi.org/10.1037//0012-1649.33.3.441.CrossRefGoogle Scholar
Sadakata, M., & McQueen, J. (2013). High stimulus variability in non-native speech learning supports formation of abstract categories: Evidence from Japanese geminates. Journal of Acoustical Society of America, 134, 1324–1335. https://doi.org/10.1121/1.4812767.CrossRefGoogle Scholar
Sommers, M. S., & Barcroft, J. (2007). An integrated account of the effects of acoustic variability in first language and second language: Evidence from amplitude, fundamental frequency, and speaking rate variability. Applied Psycholinguistics, 28, 231–249. https://doi.org/10.1017/s0142716407070129.CrossRefGoogle Scholar
Sommers, M. S., & Barcroft, J. (2011). Indexical information, encoding difficulty, and second language vocabulary learning. Evidence from amplitude, fundamental frequency, and speaking rate variability. Applied Psycholinguistics, 32, 417–434. https://doi.org/10.1017/s0142716410000469.CrossRefGoogle Scholar
Stager, C. L., & Werker, J. F. (1997). Infants listen for more phonetic detail in speech perception than in word-learning tasks. Nature, 388, 381–382. https://doi.org/10.1038/41102.CrossRefGoogle Scholar
Statistical Office of the European Communities [Eurostat]. (2015). EUROSTAT: Regional statistics: Foreign language learning. Luxembourg: Eurostat.Google Scholar
Strange, W., & Dittmann, S. (1984). Effects of discrimination training on the perception of /r-l/ by Japanese adults learning English. Perception and Psychophysics, 36, 131–145. https://doi.org/10.3758/bf03202673.CrossRefGoogle Scholar
Wells, J. C. (1997). SAMPA computer readable phonetic alphabet. In Gibbon, D., Moore, R., and Winski, R. (Eds.), Handbook of standards and resources for spoken language systems (Vol. 4; pp. 60–108). Berlin, Germany, and New York, NY: Mouton de Gruyter.Google Scholar
Werker, J. F., & Curtin, S. (2005). PRIMIR: A developmental framework of infant speech processing. Language Learning and Development, 1, 197–234. https://doi.org/10.1080/15475441.2005.9684216.CrossRefGoogle Scholar
Wonnacott, E., Boyd, J. K., Thomson, J., & Goldberg, A. E. (2012). Input effects on the acquisition of a novel phrasal construction in 5 year olds. Journal of Memory and Language, 66, 458–478. https://doi.org/10.1016/j.jml.2011.11.004.CrossRefGoogle Scholar