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COGNITIVE APTITUDES AND L2 SPEAKING PROFICIENCY

LINKS BETWEEN LLAMA AND HI-LAB

Published online by Cambridge University Press:  09 November 2018

Gisela Granena*
Affiliation:
Universitat Oberta de Catalunya
*
*Correspondence concerning this article should be addressed to Gisela Granena, Universitat Oberta de Catalunya, Av. Tibidabo 39-43 08035 Barcelona, Spain. E-mail: ggranena@uoc.edu

Abstract

This study investigated the underlying structure of a set of eight cognitive tests from the two most recent language aptitude test batteries: the LLAMA (Meara, 2005) and the Hi-LAB (Linck et al., 2013) to see whether they had any underlying constructs in common. The study also examined whether any of the observed constructs could predict L2 speaking proficiency in terms of complexity, accuracy, or fluency. Participants were 135 college-level students learning Spanish as an L2 in the United States. Results showed that the LLAMA and the Hi-LAB include tests that tap the same constructs. Specifically, the tests from the two batteries loaded onto three different factors, interpreted as “Explicit Aptitude,” “Implicit Memory Ability,” and “Implicit Learning Ability.” The results further showed that Implicit Memory Ability was a significant predictor of L2 speed fluency and interacted with Implicit Learning Ability as a predictor of lexical complexity. This finding suggested that L2 learners with greater Implicit Memory Ability may be better at accessing and retrieving previously learned or known information effortlessly. In the case of lexical complexity, the effect of Implicit Memory Ability depended on the level of Implicit Learning Ability.

Type
Research Article
Copyright
Copyright © Cambridge University Press 2018 

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Footnotes

This work was supported by a Spencer Foundation Small Research Grant #201500053 to Gisela Granena and Yucel Yilmaz. The authors would like to thank the Center for Advanced Study of Language (CASL) for providing us with web-delivered versions of the Hi-LAB tests and for scoring and sending us the data, blind of any specific hypothesis about the results.

References

REFERENCES

Abrahamsson, N., & Hyltenstam, K. (2008). The robustness of aptitude effects in near-native second language acquisition. Studies in Second Language Acquisition, 30, 481509.CrossRefGoogle Scholar
Aron, A., & Aron, E. (1999). Statistics for psychology (2nd ed.). Upper Saddle River, NJ: Prentice-Hall.Google Scholar
Boersma, P., & Weenink, D. (2014). Praat: Doing phonetics by computer (Version 5.3.76). [Computer software]. Retrieved from http://www.praat.org/.Google Scholar
Brill-Schuetz, K. A., & Morgan-Short, K. (2014). The role of procedural memory in adult second language acquisition. In Bello, P., Guarini, M., McShane, M., & Scassellati, B. (Eds.), Proceedings of the 36th Annual Conference of the Cognitive Science Society (pp. 260265). Quebec City, QC: Cognitive Science Society.Google Scholar
Buchner, A., & Wippich, W. (1998). Differences and commonalties between implicit learning and implicit memory. In Stadler, M. A. & Frensch, P. A. (Eds.), Handbook of implicit learning (pp. 346). Thousand Oaks, CA: Sage Publications.Google Scholar
Bulté, B., & Housen, A. (2012). Defining and operationalizing L2 complexity. In Housen, A., Kuiken, F., & Vedder, I. (Eds.), Dimensions of L2 performance and proficiency: Investigating complexity, accuracy and fluency in SLA (pp. 2146). Amsterdam, The Netherlands, and Philadelphia, PA: Benjamins.CrossRefGoogle Scholar
Carroll, J. B. (1962). The prediction of success in intensive foreign language training. In Glaser, R. (Ed.), Training research and education (pp. 87136). Pittsburgh, PA: University of Pittsburgh Press.Google Scholar
Carroll, J. B. (1963). A model of school learning. Teachers College Record, 64, 723733.Google Scholar
Carroll, J. B. (1969). What does the Pennsylvania foreign language research project tell us? Foreign Language Annals, 3, 214236.CrossRefGoogle Scholar
Carroll, J. B. (1981). Twenty-five years of research in foreign language aptitude. In Diller, K. (Ed.), Individual differences and universals in language learning aptitude (pp. 83118). Rowley, MA: Newbury House.Google Scholar
Carroll, J. B., & Maxwell, S. E. (1979). Individual differences in cognitive abilities. Annual Review of Psychology, 30, 603640.CrossRefGoogle ScholarPubMed
Carroll, J. B., & Sapon, S. (1959). Modern language aptitude test: Form A. New York, NY: Psychological Corporation.Google Scholar
Carroll, J. B., & Sapon, S. (2002). Manual for the MLAT. Bethesda, MD: Second Language Testing.Google Scholar
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.Google Scholar
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155159.CrossRefGoogle ScholarPubMed
Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates Publishers.Google Scholar
Defense Language Institute Foreign Language Center. (2009). Defense language proficiency testing system 5 framework. Retrieved from http://www.dliflc.edu/file.ashx?path=archive/documents/Framework_Document_Sep_10_09.pdf.Google Scholar
Dienes, Z. (1992). Connectionist and memory-array models of artificial grammar learning. Cognitive Science, 16, 4179.CrossRefGoogle Scholar
Doughty, C., Campbell, S., Bunting, M., Mislevy, M., Bowles, A., & Koeth, J. (2010). Predicting near-native L2 ability: The factor structure and reliability of Hi-LAB. In Prior, M. T., Watanabe, Y., & Lee, S.-K. (Eds.), Selected proceedings of the 2008 Second Language Research Forum: Exploring SLA perspectives, positions, and practices (pp. 1031). Somerville, MA: Cascadilla Proceedings Project.Google Scholar
Ehrman, M. E., & Oxford, R. L. (1995). Cognition plus: Correlates of language learning success. Modern Language Journal, 79, 6789.CrossRefGoogle Scholar
Faretta-Stutenberg, M., & Morgan-Short, K. (2018). The interplay of individual differences and context of learning in behavioral and neurocognitive second language development. Second Language Research, 34, 67101.CrossRefGoogle Scholar
Foster, P., & Skehan, P. (1996). The influence of planning and task type on second language performance. Studies in Second Language Acquisition, 18, 299323.CrossRefGoogle Scholar
Foster, P., Tonkyn, A., & Wigglesworth, G. (2000). Measuring spoken language: A unit for all reasons. Applied Linguistics, 21, 354375.CrossRefGoogle Scholar
Freed, B. (2000). Is fluency, like beauty, in the eyes (and ears) of the beholder? In Riggenbach, H. (Ed.), Perspectives on fluency (pp. 243265). Ann Arbor, MI: University of Michigan Press.Google Scholar
George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference (4th ed.). Boston, MA: Allyn & Bacon.Google Scholar
Granena, G. (2013a). Cognitive aptitudes for second language learning and the LLAMA language aptitude test. In Granena, G. & Long, M. H. (Eds.), Sensitive periods, language aptitude, and ultimate L2 attainment (pp. 105129). Amsterdam, The Netherlands: John Benjamins.CrossRefGoogle Scholar
Granena, G. (2013b). Individual differences in sequence learning ability and SLA in early childhood and adulthood. Language Learning, 63, 665703.CrossRefGoogle Scholar
Granena, G., & Long, M. H. (2013). Age of onset, length of residence, aptitude and ultimate L2 attainment in three linguistic domains. Second Language Research, 29, 311343.CrossRefGoogle Scholar
Grigorenko, E., Sternberg, R., & Ehrman, M. (2000). A theory-based approach to the measurement of foreign language learning ability: The Canal-F theory and test. The Modern Language Journal, 84, 390405.CrossRefGoogle Scholar
Guiraud, P. (1954). Les charactères statistiques du vocabulaire. Essai de méthodologie. Paris: Presses Universitaires de France.Google Scholar
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006). Multivariate data analysis (6th ed.). Upper Saddle River, NJ: Pearson, Prentice Hall.Google Scholar
Ishikawa, T. (2008). The effects of task demands of intentional reasoning on L2 speech performance. The Journal of Asia TEFL, 5, 2963.Google Scholar
Jacoby, L. L. (1991). A process dissociation framework: Separating automatic from intentional uses of memory. Journal of Memory and Language, 30, 513541.CrossRefGoogle Scholar
Jiménez, L. (2002). Attention in probabilistic sequence learning. In Jiménez, L. (Ed.), Attention and implicit learning (pp. 4367). Amsterdam, The Netherlands: John Benjamins.Google Scholar
Kane, M. J., & Engle, R. W. (2002). The role of prefrontal cortex in working memory capacity, executive attention, and general fluid intelligence: An individual difference perspective. Psychonomic Bulletin and Review, 9, 637667.CrossRefGoogle Scholar
Kaufman, S. B., DeYoung, C. G., Gray, J. R., Jimenez, L., Brown, J., & Mackintosh, N. (2010). Implicit learning as an ability. Cognition, 116, 321340.CrossRefGoogle ScholarPubMed
Li, S. (2015). The associations between language aptitude and second language grammar acquisition: A meta-analytic review of five decades of research. Applied Linguistics, 36, 385408.CrossRefGoogle Scholar
Li, S. (2016). The construct validity of language aptitude. A meta-analysis. Studies in Second Language Acquisition, 38, 801842.CrossRefGoogle Scholar
Linck, J., Hughes, M., Campbell, S., Silbert, N., Tare, M., Jackson, S., et al. (2013). Hi-LAB: A new measure of aptitude for high-level language proficiency. Language Learning, 63, 530566.CrossRefGoogle Scholar
Long, M. H., & Doughty, C. (2009). The handbook of language teaching. Malden, MA: Wiley-Blackwell.CrossRefGoogle Scholar
Markessinis, J. (1968). Summary of Dr. John B. Carroll’s “The foreign language attainments of language majors in the senior year”.Washington, DC: Peace Corps.Google Scholar
Meara, P. (2005). LLAMA language aptitude tests. Swansea, UK: Lognostics.Google Scholar
Michel, M., Kuiken, F., & Vedder, I. (2007). The influence of complexity in monologic versus dialogic tasks in Dutch L2. International Review of Applied Linguistics, 45, 241259.CrossRefGoogle Scholar
Morgan-Short, K., Faretta-Stutenberg, M., Brill-Schuetz, K., Carpenter, H., & Wong, P. C. M. (2014). Declarative and procedural memory as individual differences in second language acquisition. Bilingualism: Language and Cognition, 17, 5672.CrossRefGoogle Scholar
Nissen, M. J., & Bullemer, P. (1987). Attentional requirements of learning: Evidence from performance measures. Cognitive Psychology, 19, 132.CrossRefGoogle Scholar
Nunnally, J. C. (1967). Psychometric theory. New York, NY: McGraw-Hill.Google Scholar
Petersen, C., & Al-Haik, A. (1976). The development of the Defense Language Aptitude Battery (DLAB). Educational and Psychological Measurement, 36, 369380.CrossRefGoogle Scholar
Pimsleur, P. (1966). Pimsleur Language Aptitude Battery (PLAB). New York, NY: Psychological Corporation.Google Scholar
Plonsky, L., & Derrick, D. J. (2016). A meta-analysis of reliability coefficients in second language research. Modern Language Journal, 100, 538553.CrossRefGoogle Scholar
Psychology Software Tools. (2011). E-Prime™ [Computer software]. Pittsburgh, PA: Psychology Software Tools.Google Scholar
Read, J. (2000). Assessing vocabulary. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Reber, A. S. (1993). Implicit learning and tacit knowledge: An essay on the cognitive unconscious. London, UK: Oxford University Press.Google Scholar
Reber, A. S., Walkenfeld, F., & Hernstadt, R. (1991). Implicit and explicit learning: Individual differences and IQ. Journal of Experimental Psychology: Learning, Memory, and Cognition, 17, 888896.Google ScholarPubMed
Reber, P. J. (2013). The neural basis of implicit learning and memory: A review of neuropsychological and neuroimaging research. Neuropsychologia, 51, 20262042.CrossRefGoogle ScholarPubMed
Robinson, P. (1997). Individual differences and the fundamental similarity of implicit and explicit adult second language learning. Language Learning, 47, 4599.CrossRefGoogle Scholar
Robinson, P. (2002). Individual differences in intelligence, aptitude and working memory during adult incidental second language learning: A replication and extension of Reber, Walkenfeld, and Hernstadt (1991). In Robinson, P. (Ed.), Individual differences and instructed language learning (pp. 211266). Amsterdam, The Netherlands: Benjamins.CrossRefGoogle Scholar
Rogers, V. E., Meara, P., Aspinall, R., Fallon, L., Goss, T., Keey, E., & Thomas, R. (2016). Testing aptitude. EUROSLA Yearbook, 16, 179210.CrossRefGoogle Scholar
Rogers, V. E., Meara, P., Barnett-Legh, T., Curry, C., & Davie, E. (2017). Examining the LLAMA aptitude tests. JESLA, 1, 4960.CrossRefGoogle Scholar
Seger, C. A. (1994). Implicit learning. Psychological Bulletin, 115, 163196.CrossRefGoogle ScholarPubMed
Shanks, D. R., & St. John, M. F. (1994). Characteristics of dissociable human learning systems. Behavioral & Brain Sciences, 17, 367447.CrossRefGoogle Scholar
Skehan, P. (2002). Theorising and updating aptitude. In Robinson, P. (Ed.), Individual differences and instructed language learning (pp. 6993). Amsterdam, The Netherlands: John Benjamins.CrossRefGoogle Scholar
Skehan, P. (2003). Task-based instruction. Language Teaching, 36, 114.CrossRefGoogle Scholar
Skehan, P. (2009). Modelling second language performance: Integrating complexity, accuracy, fluency, and lexis. Applied Linguistics, 30, 510532.CrossRefGoogle Scholar
Sparks, R. L., Ganschow, L., & Patton, J. (1995). Prediction of performance in first year foreign language courses. Journal of Educational Psychology, 87, 638655.CrossRefGoogle Scholar
Tavakoli, P., & Skehan, P. (2005). Strategic planning, task structure, and performance testing. In Ellis, R. (Ed.), Planning and task performance in a second language (pp. 239277). Amsterdam, The Netherlands: Benjamins.CrossRefGoogle Scholar
Tulving, E., & Schacter, D. L. (1990). Priming and human memory systems. Science, 247, 301306.CrossRefGoogle ScholarPubMed
Ullman, M. T. (2004). Contributions of memory circuits to language: The declarative/procedural model. Cognition, 92, 231270.CrossRefGoogle ScholarPubMed
Van der Linden, M., Collette, F., Salmon, E., Delfiore, G., Degueldre, C., Luxen, A., & Franck, G. (1999). The neural correlates of updating information in verbal working memory. Memory, 7, 549560.CrossRefGoogle ScholarPubMed
Vermeer, A. (2000). Coming to grips with lexical richness in spontaneous speech data. Language Testing, 17, 6583.CrossRefGoogle Scholar
Wang, W. C., & Yonelinas, A. P. (2012). Familiarity is related to conceptual implicit memory: An examination of individual differences. Psychonomic Bulletin & Review, 19, 11541164.CrossRefGoogle ScholarPubMed
Was, C. A., & Woltz, D. J. (2007). Reexamining the relationship between working memory and comprehension: The role of available long-term memory. Journal of Memory and Language, 56, 86102.CrossRefGoogle Scholar
Willingham, D. B., Nissen, M. J., & Bullemer, P. (1989). On the development of procedural knowledge. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 10471060.Google ScholarPubMed
Woltz, D. J. (2003). Implicit cognitive processes as aptitudes for learning. Educational Psychologist, 38, 95104.CrossRefGoogle Scholar
Yonelinas, A. P. (2002). The nature of recollection and familiarity: A review of 30 years of research. Journal of Memory and Language, 46, 441517.CrossRefGoogle Scholar