Hostname: page-component-848d4c4894-sjtt6 Total loading time: 0 Render date: 2024-06-19T02:23:56.415Z Has data issue: false hasContentIssue false

L2-L1 noncognate masked translation priming as a task-specific phenomenon

Published online by Cambridge University Press:  14 December 2020

Mark J. McPhedran*
Affiliation:
Department of Psychology, Grenfell Campus, Memorial University of Newfoundland
Stephen J. Lupker
Affiliation:
Department of Psychology, University of Western Ontario
*
Address for correspondence: Mark McPhedran, Department of Psychology, Grenfell Campus, Memorial University of Newfoundland, 20 University Drive, Corner Brook, Newfoundland and Labrador, Canada, A2H 5G5, E-mail: mmcphedran@grenfell.mun.ca.

Abstract

The masked translation priming effect was examined in Chinese–English bilinguals using lexical decision and semantic categorization tasks in an effort to understand why the two tasks seem to produce different patterns of results. A machine-learning approach was used to assess the participant-based factors that contribute to the sizes of translation priming effects in these tasks. As expected, the participant-based factors that predicted translation priming effects did vary across tasks. Priming effects in lexical decision were associated with higher self-rated listening, reading, and writing abilities in English. Priming effects in semantic categorization were associated with more frequent use of English in daily life, spoken English proficiency, and self-rated listening proficiency in English. These results are discussed within the framework of Multilink, the logic of which is then expanded in an attempt to account for these task differences.

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

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.)

References

Akaike, H (1973) Information theory and an extension of the maximum likelihood principle. In Petrov, BN & Csaki, F (Eds.), 2nd International Symposium on Information Theory (pp. 267281). Budapest, Hungary: Akadémiai Kiadó.Google Scholar
Baayen, RH, Piepenbrock, R and Gulikers, L (1995) The CELEX lexical database [CD-ROM]. Philadelphia: University of Pennsylvania, Linguistic Data Consortium.Google Scholar
Baayen, RH, Davidson, DJ and Bates, DM (2008) Mixed-effects modeling with crossed random effects for subjects and items. Journal of Memory and Language 59(4), 390412. DOI: 10.1016/j.jml.2007.12.005CrossRefGoogle Scholar
Bates, D, Maechler, M, Bolker, B and Walker, S (2015) Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67(1), 148. DOI: 10.18637/jss.v067.i01CrossRefGoogle Scholar
Brown, JA, Fishco, VV and Hanna, G (1993) Nelson-Denny reading test: Manual for scoring and interpretation, Forms G & H. Rolling Meadows, IL: Riverside Publishing.Google Scholar
Chen, B, Zhou, H, Gao, Y and Dunlap, S (2014) Cross-language translation priming asymmetry with Chinese–English bilinguals: A test of the sense model. Journal of Psycholinguistic Research 43(3), 225240. DOI: 10.1007/s10936-013-9249-3CrossRefGoogle ScholarPubMed
de Groot, AMB and Nas, GLJ (1991) Lexical representation of cognates and noncognates in compound bilinguals. Journal of Memory and Language 30(1), 90123. DOI: 10.1016/0749-596X(91)90012-9CrossRefGoogle Scholar
De Rosario-Martinez, H (2015) phia: Post-hoc interaction analysis. R package version 0.2-1.Google Scholar
Dietterich, TG (2000) Ensemble methods in machine learning. In International workshop on multiple classifier systems (pp. 115). Springer, Berlin, Heidelberg.Google Scholar
Dijkstra, T, Hilberink-Schulpen, B and van Heuven, WJB (2010) Repetition and masked form priming within and between languages using word and nonword neighbors. Bilingualism: Language and Cognition 13(3), 341357. DOI: 10.1017/S1366728909990575CrossRefGoogle Scholar
Dijkstra, T, Miwa, K, Brummelhuis, B, Sappelli, M and Baayen, H (2010) How cross-language similarity and task demands affect cognate recognition. Journal of Memory and Language 62, 284301.CrossRefGoogle Scholar
Dijkstra, T and van Heuven, WJB (2002) The architecture of the bilingual word recognition system. From identification to decision. Bilingualism: Language and Cognition 5(3), 175197. DOI: 10.1017/S1366728902003012CrossRefGoogle Scholar
Dijkstra, T, Wahl, A, Buytenhuijs, F, Van Halem, N, Al-Jibouri, Z, De Korte, M and Rekké, S (2019) Multilink: A computational model for bilingual word recognition and word translation. Bilingualism: Language and Cognition 22(4), 657679.CrossRefGoogle Scholar
Dimitropoulou, M, Duñabeitia, JA and Carreiras, M (2011) Masked translation priming effects with low proficient bilinguals. Memory & Cognition 39, 260275. DOI: 10.3758/s13421-010-0004-9CrossRefGoogle ScholarPubMed
Duzan, H and Shariff, NSBM (2015) Ridge regression for solving the multicollinearity problem: Review of methods and models. Journal of Applied Sciences 15, 392404. DOI: 10.3923/jas.2015.392.404CrossRefGoogle Scholar
Finkbeiner, M, Forster, K, Nicol, J and Nakamura, K (2004) The role of polysemy in masked semantic and translation priming. Journal of Memory and Language 51(1), 122. DOI: 10.1016/j.jml.2004.01.004CrossRefGoogle Scholar
Forster, KI and Forster, JC (2003) DMDX: A Windows display program with millisecond accuracy. Behavior Research Methods, Instruments, & Computers 35(1), 116124. DOI: 10.3758/BF03195503CrossRefGoogle ScholarPubMed
Géron, A (2017) Hands-on machine learning with scikit-learn & TensorFlow: Concepts, tools, and techniques to build intelligent systems. Sevastopol, CA: O'Reilly.Google Scholar
Gollan, TH, Forster, KI and Frost, R (1997) Translation priming with different scripts: Masked priming with cognates and noncognates in Hebrew-English bilinguals. Journal of Experimental Psychology: Learning, Memory, and Cognition 23(5), 11221139. DOI: 10.1037/0278-7393.23.5.1122Google ScholarPubMed
Grainger, J and Frenck-Mestre, C (1998) Masked priming by translation equivalents in proficient bilinguals. Language and Cognitive Processes 13(6), 601623. DOI: 10.1080/016909698386393CrossRefGoogle Scholar
Hoerl, AE and Kennard, RW (1970) Ridge regression: Biased estimation for nonorthogonal problems. Technometrics 12(1), 5567. DOI: 10.2307/1267351CrossRefGoogle Scholar
Jiang, N (1999) Testing processing explanations for the asymmetry in masked cross-language priming. Bilingualism: Language and Cognition 2(1), 5975.CrossRefGoogle Scholar
Jiang, N and Forster, KI (2001) Cross-language priming asymmetries in lexical decision and episodic recognition. Journal of Memory and Language 44(1), 3251. DOI: 10.1006/jmla.2000.2737CrossRefGoogle Scholar
Kenward, MG and Roger, JH (1997) Small sample inference for fixed effects from restricted maximum likelihood. Biometrics 53(3), 983997. DOI: 10.2307/2533558CrossRefGoogle ScholarPubMed
Kroll, JF and Stewart, E (1994) Category interference in translation and picture naming: Evidence for asymmetric connection between bilingual memory representations. Journal of Memory and Language 33(2), 149174. DOI: 10.1006/jmla.1994.1008CrossRefGoogle Scholar
Kroll, JF and Tokowicz, N (2001) The development of conceptual representation for words in a second language. In Nicol, JL (Ed.), One mind, two languages: Bilingual language processing (pp. 4971). Malden, MA: Blackwell.Google Scholar
Lemhofer, K and Broersma, M (2012) Introducing LexTALE: A quick and valid lexical test for advanced learners of English. Behavioral Research Methods 44(2), 325343. DOI: 10.3758/s13428-011-0146-0CrossRefGoogle ScholarPubMed
Luke, SG (2017) Evaluating significance in linear mixed-effects models in R. Behavior Research Methods 49, 14941502. DOI: 10.3758/s13428-016-0809-yCrossRefGoogle ScholarPubMed
Luo, X, Cheung, H, Bel, D, Li, L, Chen, L and Mo, L (2013) The roles of semantic sense and form-meaning connection in translation priming. The Psychological Record 63(1), 193208. DOI: 10.11133/j.tpr.2013.63.1.015CrossRefGoogle Scholar
Mahalanobis, PC (1936) On the generalised distance in statistics. Proceedings of the National Institute of Sciences of India 2(1), 4955.Google Scholar
Malt, BC and Sloman, SA (2003) Linguistic diversity and object naming by non-native speakers of English. Bilingualism: Language and Cognition 6(1), 4767. DOI: 10.1017/S1366728903001020CrossRefGoogle Scholar
Marian, V, Blumenfeld, HK and Kaushanskaya, M (2007) The language experience and proficiency questionnaire (LEAP-Q): Assessing language profiles in bilinguals and multilinguals. Journal of Speech, Language, and Hearing Research 50(4), 940967. DOI: 10.1044/1092-4388(2007/067)CrossRefGoogle ScholarPubMed
Muhammad, I, Maria, J and Muhammad, AR (2013) Comparison of shrinkable regression for remedy of multicollinearity problem. Middle East Journal of Scientific Research 14(4), 570579. DOI: 10.5829/idosi.mejsr.2013.14.4.488Google Scholar
Nakayama, M, Ida, K and Lupker, SJ (2016) Cross-script L2-L1 noncognate translation priming in lexical decision depends on L2 proficiency: Evidence from Japanese–English bilinguals. Bilingualism: Language and Cognition 19(5), 10011022. DOI: 10.1017/S1366728915000462CrossRefGoogle Scholar
Nakayama, M, Sears, CR, Hino, Y and Lupker, SJ (2013) Masked translation priming with Japanese–English bilinguals: Interactions between cognate status, target frequency, and L2 proficiency. Journal of Cognitive Psychology 25, 949981. DOI: 10.1080/20445911.2013.839560CrossRefGoogle Scholar
Oyeyemi, GM, Ogunjobi, EO and Folorunsho, AI (2015) On performance of shrinkage methods: A Monte Carlo study. International Journal of Statistics and Applications 5(2), 7276. DOI: 10.5923/j.statistics.20150502.04Google Scholar
Powell, MJD (2009) The BOBYQA algorithm for bound constrained optimization without derivatives. Cambridge NA Report NA2009/0, University of Cambridge, Cambridge, 26–46.Google Scholar
R Core Team (2017) R: A language and environment for statistical computing. Vienna, Austria. http://www.R-project.org/Google Scholar
Roelofs, A (2008) Tracing attention and the activation flow in spoken word planning using eye movements. Journal of Experimental Psychology: Learning, Memory, and Cognition 34(2), 353368. DOI: 10.1037/0278-7393.34.2.353Google ScholarPubMed
Schoonbaert, S, Holcomb, PJ, Grainger, J and Hartsuiker, RJ (2011) Testing asymmetries in noncognate translation priming: Evidence from RTs and ERPs. Psychophysiology 48(1), 7481. DOI: 10.1111/j.1469-8986.2010.01048.xCrossRefGoogle ScholarPubMed
Tibshirani, R (1996) Regression shrinkage and selection via the lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58(1), 267288.CrossRefGoogle Scholar
Tikhonov, AN (1963) Solution of incorrectly formulated problems and the regularization method. Soviet Mathematics 4, 10351038.Google Scholar
Tse, CS, Yap, MJ, Chan, YL, Sze, WP, Shaoul, C and Lin, D (2017) The Chinese Lexicon Project: A megastudy of lexical decision performance for 25,000+ traditional Chinese two-character compound words. Behavior Research Methods 49(4), 15031519. DOI: 10.3758/s13428-016-0810-5CrossRefGoogle ScholarPubMed
Wang, X and Forster, KI (2010) Masked translation priming with semantic categorization: Testing the Sense Model. Bilingualism and Cognition 13(3), 327340. DOI: 10.1017/S1366728909990502CrossRefGoogle Scholar
Wen, Y and van Heuven, WJB (2017a) Chinese translation norms for 1,429 English words. Behavior Research Methods 49(3), 10061019. DOI: 10.3758/s13428-016-0761-xCrossRefGoogle Scholar
Wen, Y and van Heuven, WJB (2017b) Non-cognate translation priming in masked priming lexical decisions: A meta-analysis. Psychonomic Bulletin & Review 24(3), 879886. DOI: 10.3758/s13423-016-1151-1CrossRefGoogle Scholar
Xia, V and Andrews, S (2015) Masked translation priming asymmetry in Chinese–English bilinguals: Making sense of the Sense Model. The Quarterly Journal of Experimental Psychology 68(2), 294325. DOI: 10.1080/17470218.2014.944195CrossRefGoogle ScholarPubMed
Zou, H and Hastie, T (2005) Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society, Series B 67, 301320.CrossRefGoogle Scholar