Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-11-29T11:07:59.651Z Has data issue: false hasContentIssue false
  • English
  • Français

THE ROLE OF PROCEDURAL LEARNING ABILITY IN AUTOMATIZATION OF L2 MORPHOLOGY UNDER DIFFERENT LEARNING SCHEDULES

AN EXPLORATORY STUDY

Published online by Cambridge University Press:  10 August 2017

Yuichi Suzuki
Yuichi Suzuki*
Affiliation:
Kanagawa University
*
*Correspondence concerning this article should be addressed to Yuichi Suzuki, Faculty of Foreign Languages, Kanagawa University, 3-27-1, Rokkakubashi, Kanagawa-ku, Yokohama-shi, Kanagawa, 221-8686, Japan. E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

This paper reports on the reanalysis of Suzuki’s (2017) experiment and investigated the extent to which learning schedules influence automatization of second language (L2) morphology. Sixty participants were separated into two groups, which studied morphological rules for oral production under short-spacing (3.3-day intervals) and long-spacing learning conditions (7-day intervals). Their oral production test performance resulted in two measures of automatization: reaction time (RT) as an index of speedup and coefficient of variance (CV) as an index of stability/restructuring. The results showed that, while RT of both groups declined significantly after the training, the 3.3-day group exhibited greater propensity for restructuring than the 7-day group. Furthermore, procedural learning ability measured by the Tower of London task was significantly associated with RT, but not with CV, in the 3.3-day group only. These findings suggest that learning schedules and procedural learning ability influence different stages of automatization of L2 morphological learning.

Type
Research Report
Information
Studies in Second Language Acquisition , Volume 40 , Issue 4 , December 2018 , pp. 923 - 937
Copyright
Copyright © Cambridge University Press 2017 

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.)

Footnotes

This study was supported by Grant-in-Aid for Scientific Research (KAKENHI) from Japan Society for the Promotion of Science (JSPS). I am grateful to my RAs, Naoko Miyauchi, Yuki Aizawa, Misaki Kuratsubo, Yuka Oishi, and Aya Mizuno for their assistance in data collection and coding. I would like to express my gratitude to Kara Morgan-Short for allowing me to use the TOL task.

References

REFERENCES

Antoniou, M., Ettlinger, M., & Wong, P. C. M. (2016). Complexity, training paradigm design, and the contribution of memory subsystems to grammar learning. PLoS ONE, 11, e0158812.CrossRefGoogle ScholarPubMed
Bender, R., & Lange, S. (2001). Adjusting for multiple testing—When and how? Journal of Clinical Epidemiology, 54(4), 343–349.CrossRefGoogle Scholar
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.Google Scholar
Bird, S. (2010). Effects of distributed practice on the acquisition of second language English syntax. Applied Psycholinguistics, 31, 635–650.CrossRefGoogle Scholar
Brill-Schuetz, K. A., & Morgan-Short, K. (2014). The role of procedural memory in adult second language acquisition. Paper presented at the 36th Annual Meeting of the Cognitive Science Society (COGSCI 2014), Quebec City, Canada.Google Scholar
DeKeyser, R. M. (2015). Skill acquisition theory. In VanPatten, B. & Williams, J. (Eds.), Theories in second language acquisition: An introduction (2nd ed., pp. 94–112). New York, NY: Routledge.Google Scholar
Ettlinger, M., Bradlow, A. R., & Wong, P. C. M. (2014). Variability in the learning of complex morphophonology. Applied Psycholinguistics, 35, 807–831.CrossRefGoogle Scholar
Forster, K. I., & Forster, J. C. (2003). DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers, 35, 116–124.CrossRefGoogle ScholarPubMed
Hamrick, P. (2015). Declarative and procedural memory abilities as individual differences in incidental language learning. Learning and Individual Differences, 44, 9–15.CrossRefGoogle Scholar
Hulstijn, J. H., Van Gelderen, A., & Schoonen, R. (2009). Automatization in second language acquisition: What does the coefficient of variation tell us? Applied Psycholinguistics, 30, 555–582.CrossRefGoogle Scholar
Kaller, C. P., Rahm, B., Köstering, L., & Unterrainer, J. M. (2011). Reviewing the impact of problem structure on planning: A software tool for analyzing tower tasks. Behavioural Brain Research, 216, 1–8.CrossRefGoogle ScholarPubMed
Lim, H., & Godfroid, A. (2015). Automatization in second language sentence processing: A partial, conceptual replication of Hulstijn, Van Gelderen, and Schoonen’s 2009 study. Applied Psycholinguistics, 36, 1247–1282.CrossRefGoogle Scholar
Morgan-Short, K., Faretta-Stutenberg, M., Brill-Schuetz, K. A., Carpenter, H., & Wong, P. C. M. (2014). Declarative and procedural memory as individual differences in second language acquisition. Bilingualism: Language and Cognition, 17, 56–72.CrossRefGoogle Scholar
Nissen, M. J., & Bullemer, P. (1987). Attentional requirements of learning: Evidence from performance measures. Cognitive Psychology, 19, 1–32.CrossRefGoogle Scholar
Paradis, M. (2009). Declarative and procedural determinants of second languages. Philadelphia, PA: John Benjamins Publishing Company.CrossRefGoogle Scholar
Plonsky, L., & Oswald, F. L. (2014). How big is “big”? Interpreting effect sizes in L2 research. Language Learning, 64, 878–912.CrossRefGoogle Scholar
Robinson, P. (2007). Aptitudes, abilities, contexts, and practice. In DeKeyser, R. M. (Ed.), Practice in a second language: Perspectives from applied linguistics and cognitive psychology (pp. 256–286). New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Rodgers, D. M. (2011). The automatization of verbal morphology in instructed second language acquisition. IRAL-International Review of Applied Linguistics in Language Teaching, 49, 295–319.CrossRefGoogle Scholar
Rogers, J. (2015). Learning second language syntax under massed and distributed conditions. TESOL Quarterly, 49, 857–866.CrossRefGoogle Scholar
Segalowitz, N. S. (2003). Automaticity and second languages. In Doughty, C. J. & Long, H. M. (Eds.), The handbook of second language acquisition (pp. 382–408). Oxford, UK: Blackwell Publishers.CrossRefGoogle Scholar
Segalowitz, N. S., & Segalowitz, S. J. (1993). Skilled performance, practice, and the differentiation of speed-up from automatization effects: Evidence from second language word recognition. Applied Psycholinguistics, 14, 369.CrossRefGoogle Scholar
Squire, L. R. (2004). Memory systems of the brain: A brief history and current perspective. Neurobiology of Learning and Memory, 82, 171–177.CrossRefGoogle ScholarPubMed
Suzuki, Y. (2017). The optimal distribution of practice for the acquisition of L2 morphology: A conceptual replication and extension. Language Learning. doi: 10.1111/lang.12236.CrossRefGoogle Scholar
Suzuki, Y., & DeKeyser, R. M. (2017a). Effects of distributed practice on the proceduralization of morphology. Language Teaching Research, 21, 166–188.CrossRefGoogle Scholar
Suzuki, Y., & DeKeyser, R. M. (2017b). Exploratory research on L2 practice distribution: An aptitude-by-treatment interaction. Applied Psycholinguistics, 38, 27–56.CrossRefGoogle Scholar
Suzuki, Y., & Sunada, M. (2016). Automatization in second language sentence processing: Relationship between elicited imitation and maze tasks. Bilingualism: Language and Cognition, 1–15. doi: 10.1017/S1366728916000857Google Scholar
Tagarelli, K., Ruiz Hernandez, S., Moreno Vega, J., & Rebuschat, P. E. (2016). Variability in second language learning: The roles of individual differences, learning conditions, and linguistic complexity. Studies in Second Language Acquisition, 38, 293–316.CrossRefGoogle Scholar
Ullman, M. T. (2015). The declarative/procedural model: A neurobiologically-motivated theory of first and second language. In VanPatten, B. & Williams, J. (Eds.), Theories in second language acquisition: An introduction (2nd ed., pp. 135–158). New York, NY: Routledge.Google Scholar
Ullman, M. T., & Lovelett, J. T. (2016). Implications of the declarative/procedural model for improving second language learning: The role of memory enhancement techniques. Second Language Research. doi: 10.1177/0267658316675195Google Scholar
Unterrainer, J. M., Rahm, B., Kaller, C. P., Leonhart, R., Quiske, K., Hoppe-Seyler, K., et al. . (2004). Planning abilities and the Tower of London: Is this task measuring a discrete cognitive function? Journal of Clinical and Experimental Neuropsychology, 26, 846–856.CrossRefGoogle Scholar
Supplementary material: File

Suzuki supplementary material

Appendices S1-S12

Download Suzuki supplementary material(File)
File 278.5 KB