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Testing Hypotheses about Language Learning Using Structural Equation Modeling

Published online by Cambridge University Press:  22 December 2014

Paula Winke
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Abstract

In this chapter, I review a statistical method for hypothesis or theory testing called structural equation modeling (SEM). First, I describe what a model of second language acquisition (SLA) is. I do this so anyone, even those new to the field of applied linguistics, can understand the basic concepts underlying SEM; that is, SEM researchers first articulate a model of SLA, then get empirical data from the real world that operationalize the variables in the model. Researchers use an SEM program to test the model on the data (to see if the model fits the data; if the model is plausible in relation to the learning context of the people from whom the data were collected). After explaining the basics of SEM, I provide a review of 39 applied linguistics studies that have been published in the last five years (between 2008 and 2013) and that present at least one SEM analysis as part of the results. I discuss four problematic areas related to the use of SEM that I believe these 39 studies highlighted: (a) sample size, (b) model presentation, (c) reliability, and (d) the number of Likert-scale points. I conclude with possible solutions for the four problem areas and outline future directions.

Type
Research Article
Information
Annual Review of Applied Linguistics , Volume 34 , March 2014 , pp. 102 - 122
Copyright
Copyright © Cambridge University Press 2014 

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References

ANNOTATED BIBLIOGRAPHY

Kieffer, M. J., & Lesaux, N. K. (2012). Direct and indirect roles of morphological awareness in the English reading comprehension of native English, Spanish, Filipino, and Vietnamese speakers. Language Learning, 62, 1170–1204. doi:10.1111/j.1467–9922.2012.00722.x

Kieffer and Lesaux investigated how derivational morphological awareness impacts English reading comprehension in sixth-grade students (n = 952) in southern California. The students came from different language backgrounds: native English, Spanish-speaking language minority, and Filipino-speaking language minority. The data were collected from the students over the course of two testing periods during their sixth-grade year. The authors tested their proposed model on all four language-background groups. The writing is clear, and the figures and tables in which the data are presented are well crafted and easy to understand. These points in combination with excellent, multimodel theory-testing make this article a standout among the recent SLA SEM articles.

Miglietta, A., & Tartaglia, S. (2009). The influence of length of stay, linguistic competence, and media exposure in immigrants’ adaptation. Cross-Cultural Research, 43, 46–61. doi:10.1177/1069397108326289

Miglietta and Tartaglia studied 576 immigrants in Italy (196 from Romania, 179 from North Africa, and 201 from Latin America) to better understand what made them emotionally attached (acculturated) to life in Italy and what did not. The authors surveyed the individuals to find out the following information about them: how long they had been in Italy (i.e., their length of residency); their proficiency in Italian; how much they used Italian with friends and family; how much mass Italian media they consumed, and how much they knew about satellite TV programs from their homelands. The writing is this article is straightforward, and the data are well presented. Both of these help render this an exemplary SLA SEM study.

Rivers, D. J. (2010). National identification and intercultural relations in foreign language learning. Language and Intercultural Communication, 10, 318–336. doi:10.1080/14708477.2010.502234

Rivers investigated Japanese university students’ attitudes toward learning English. He did this by surveying 377 of them regarding their levels of internationalism, patriotism, and Japanese nationalism. He also surveyed them in terms of how vital they considered English-speaking nations and whether they believed English speakers have intercultural appeal. This article is reader friendly and interesting. Rivers's work represents well how researchers in SLA using SEM should go about describing and reporting their research.

REFERENCES

Aidinlou, N. A., & Ghobadi, S. (2012). Examination of relationships between factors affecting on oral participation of ELT students and language development: A structural equation modeling approach. International Journal of English Linguistics, 2, 131–141.CrossRefGoogle Scholar
Andringa, S., Olsthoorn, N., van Beuningen, C., Schoonen, R., & Hulstijn, J. (2012). Determinants of success in native and non-native listening comprehension: An individual differences approach. Language Learning, 62, 49–78.CrossRefGoogle Scholar
Aryadoust, V. (2010). Investigating writing sub-skills in testing English as a foreign language: A structural equation modeling study. TESL-EJ: Teaching English as a Second or Foreign Language, 13, 1–20.Google Scholar
Betts, L., & Hartley, J. (2012). The effects of changes in the order of verbal labels and numerical values on children's scores on attitude and rating scales. British Educational Research Journal, 38, 319–331. doi:10.1080/01411926.2010.544712Google Scholar
Bollen, K. A., & Hoyle, R. H. (2012). Latent variables in structural equation modeling. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 56–67). New York, NY: Guilford Press.Google Scholar
Byrne, B. M. (2010). Structural equation modeling with AMOS: Basic concepts, applications, and programming (2nd ed.). New York, NY: Routledge.Google Scholar
Byrne, B. M. (2012). Choosing structural equation modeling computer software: Snapshots of LISREL, EQS, Amos, and Mplus. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 307–324). New York, NY: Guilford Press.Google Scholar
Cochran, J. L., McCallum, R. S., & Mee Bell, S. (2010). Three A's: How do attributions, attitudes, and aptitude contribute to foreign language learning? Foreign Language Annals, 43, 566–582.CrossRefGoogle Scholar
Cook, C., Heath, F., Thompson, R. L., & Thompson, B. (2001). Score reliability in web- or Internet-based surveys: Unnumbered graphic rating scales versus Likert-type scales. Educational and Psychological Measurement, 61, 697–706. doi:10.1177/00131640121971356Google Scholar
Csizér, K., & Dörnyei, Z. (2005). The internal structure of language learning motivation and its relationship with language choice and learning effort. The Modern Language Journal, 89, 19–36.CrossRefGoogle Scholar
Csizér, K., & Kontra, E. H. (2012). ELF, ESP, ENL and their effect on students’ aims and beliefs: A structural equation model. System, 40, 1–10.CrossRefGoogle Scholar
Csizér, K., & Kormos, J. (2008). The role of intercultural contact in learning German in Hungary: A structural equation modelling approach. Zeitschrift für Interkulturellen Fremdsprachenunterricht, 13, 1–12.Google Scholar
Csizér, K., & Kormos, J. (2009). Modelling the role of inter-cultural contact in the motivation of learning English as a foreign language. Applied Linguistics, 30, 166–185.CrossRefGoogle Scholar
Dale, P. S., Harlaar, N., & Plomin, R. (2012). Nature and nurture in school-based second language achievement. Language Learning, 62, 28–48.Google Scholar
Dooly, M. (2007). Joining forces: Promoting metalinguistic awareness through computer-supported collaborative learning. Language Awareness, 16, 57–74.CrossRefGoogle Scholar
Dooly, M. (2011). Divergent perceptions of telecollaborative language learning tasks: Task-as-workplan vs. task-as-process. Language Learning & Technology, 15, 69–91.Google Scholar
Dörnyei, Z. (2009). The psychology of the second language learner. Oxford, UK: Oxford University Press.Google Scholar
Dörnyei, Z., & Taguchi, T. (2009). Questionnaires in second language research: Construction, administration, and processing (2nd ed.). New York, NY: Routledge.Google Scholar
Du, H. (2013). The development of Chinese fluency during study abroad in China. The Modern Language Journal, 97, 131–143.CrossRefGoogle Scholar
Fushino, K. (2010). Causal relationships between communication confidence, beliefs about group work, and willingness to communicate in foreign language group work. TESOL Quarterly, 44, 700–724.Google Scholar
Gallagher, H. C. (2013). Willingness to communicate and cross-cultural adaptation: L2 communication and acculturative stress as transaction. Applied Linguistics, 34, 53–73.Google Scholar
Gardner, R. C., Tremblay, P. F., & Masgoret, A.-M. (1997). Towards a full model of second language learning: An empirical investigation. The Modern Language Journal, 81, 344–362.Google Scholar
Ghonsooly, B., Khajavy, G. H., & Asadpour, S. F. (2012). Willingness to communicate in English among Iranian non-English major university students. Journal of Language and Social Psychology, 31, 197–211. doi:10.1177/0261927´12438538CrossRefGoogle Scholar
Godwin-Jones, R. (2011). Autonomous language learning. Language Learning & Technology, 15, 4–11.Google Scholar
Gorsuch, R. L. (1997). Exploratory factor analysis: Its role in item analysis. Journal of Personality Assessment, 68, 532–560. doi:10.1207/s15327752jpa6803_5Google Scholar
Guo, Y., & Roehrig, A. D. (2011). Roles of general versus second language (L2) knowledge in L2 reading comprehension. Reading in a Foreign Language, 23, 42–64.Google Scholar
Hartley, J., & Betts, L. R. (2010). Four layouts and a finding: The effects of changes in the order of the verbal labels and numerical values on Likert-type scales. International Journal of Social Research Methodology, 13, 17–27. doi:10.1080/13645570802648077Google Scholar
Henry, A., & Cliffordson, C. (2013). Motivation, gender, and possible selves. Language Learning, 63, 271–295. doi:10.1111/lang.12009Google Scholar
Hershberger, S. L. (2003). The growth of structural equation modeling: 1994–2001. Structural Equation Modeling, 10, 53–46.Google Scholar
Hiromori, T. (2009). A process model of L2 learners’ motivation: From the perspectives of general tendency and individual differences. System, 37, 313–321.Google Scholar
Ho, M. R., Stark, S., & Chernyshenko, O. (2012). Graphical representation of structural equation models using path diagrams. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 43–55). New York, NY: Guilford Press.Google Scholar
Hoyle, R. H. (Ed.): (2012a). Handbook of structural equation modeling. New York, NY: Guilford Press.Google Scholar
Hoyle, R. H. (2012b). Model specification in structural equation modeling. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 126–144). New York, NY: Guilford Press.Google Scholar
Hu, L., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6, 1–55. doi:10.1080/10705519909540118CrossRefGoogle Scholar
In’nami, Y. (2006). The effects of test anxiety on listening test performance. System, 34, 317–340.Google Scholar
In’nami, Y., & Koizumi, R. (2011). Structural equation modeling in language testing and learning research: A review. Language Assessment Quarterly, 8, 250–276.Google Scholar
Isemonger, I. M. (2007). Operational definitions of explicit and implicit knowledge: Response to R. Ellis (2005) and some recommendations for future research in this area. Studies in Second Language Acquisition, 29, 101–118.CrossRefGoogle Scholar
Jones, W. P., & Loe, S. A. (2013). Optimal number of questionnaire response categories: More may not be better. SAGE Open, April-June, 1–10. doi:10.1177/2158244013489691Google Scholar
Kieffer, M. J. (2011). Converging trajectories: Reading growth in language minority learners and their classmates, kindergarten to grade 8. American Educational Research Journal, 48, 1187–1225. doi:10.3102/0002831211419490CrossRefGoogle Scholar
Kieffer, M. J., & Lesaux, N. K. (2012). Direct and indirect roles of morphological awareness in the English reading comprehension of native English, Spanish, Filipino, and Vietnamese speakers. Language Learning, 62, 1170–1204. doi:10.1111/j.1467-9922.2012.00722.xGoogle Scholar
Kinginger, C. (2009) Language learning and study abroad: A critical reading of research. New York, NY: Palgrave Macmillan.Google Scholar
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford Press.Google Scholar
Kline, R. B. (2012). Assumptions in structural equation modeling. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 111–125). New York, NY: Guilford Press.Google Scholar
Kunnan, A. J. (1998). An introduction to structural equation modelling for language assessment research. Language Testing, 15, 295–332.Google Scholar
Kunnan, A. J. (1999). Recent developments in language testing. Annual Review of Applied Linguistics, 19, 235–253.Google Scholar
Kunnan, A. J. (2010). Statistical analyses for test fairness. Revue française de linguistique appliquée, 15, 39–48.CrossRefGoogle Scholar
Lewis, M. B., & Vladeanu, M. (2006). What do we know about psycholinguistic effects? The Quarterly Journal of Experimental Psychology, 59, 977–986.Google Scholar
Li, S. (2013). The interactions between the effects of implicit and explicit feedback and individual differences in language analytic ability and working memory. The Modern Language Journal, 97, 634–654. doi:10.1111/j.1540-4781.2013.12030.xGoogle Scholar
Little, T. D. (2013). Longitudinal structural equation modeling. New York, NY: Guilford Press.Google Scholar
MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 200–226. doi:10.1146/annurev.psych.51.1.201Google Scholar
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological Methods, 1, 130–149.Google Scholar
MacIntyre, P. D., Dörnyei, Z., Clément, R., & Noels, K. A. (1998). Conceptualizing willingness to communicate in a L2: A situational model of L2 confidence and affiliation. The Modern Language Journal, 82, 545–562.Google Scholar
MacIntyre, P. D., MacMaster, K., & Baker, S. C. (2001). The convergence of multiple models of motivation for second language learning: Gardner, Pintrich, Kuhl, and McCroskey. In Schmidt, R. (Ed.), Motivation and second language acquisition (pp. 461–492). Honolulu, HI: University of Hawai’i Press.Google Scholar
Mancilla-Martinez, J., & Lesaux, N. K. (2010). Predictors of reading comprehension for struggling readers: The case of Spanish-speaking language minority learners. Journal of Educational Psychology, 102, 701–711.Google Scholar
Marx, A., & Roick, T. (2012). Determinants of listening comprehension in German L1 and L2 students. Zeitschrift für Pädagogische Psychologie, 26, 121–134.Google Scholar
Matsumura, S. (2003). Modelling the relationships among interlanguage pragmatic development: L2 proficiency and exposure to L2. Applied Linguistics, 24, 465–491.Google Scholar
McDonald, R. P., & Ho, M.-H. R. (2002). Principles and practice in reporting structural equation analyses. Psychological Methods, 7, 64–82.CrossRefGoogle ScholarPubMed
Mererdith, R. A. (2010). Acquiring cultural perceptions during study abroad: The influence of youthful associates. Hispania, 93, 686–702.CrossRefGoogle Scholar
Miglietta, A., & Tartaglia, S. (2009). The influence of length of stay, linguistic competence, and media exposure in immigrants’ adaptation. Cross-Cultural Research, 43, 46–61. doi:10.1177/1069397108326289Google Scholar
Neuman, L. (2010). Social research methods: Qualitative and quantitative approaches (7th ed.). Harlow, UK: Pearson Education.Google Scholar
Oxford, R. L. (1990). Language learning strategies: What every teacher should know. Boston, MA: Heinle & Heinle.Google Scholar
Papi, M. (2010). The L2 motivational self system, L2 anxiety, and motivated behavior: A structural equation modeling approach. System, 38, 467–479.Google Scholar
Pasquarella, A., Chen, X., Lam, K., Luo, Y. C., & Ramirez, G. (2011). Cross-language transfer of morphological awareness in Chinese-English bilinguals. Journal of Research in Reading, 34, 23–42.Google Scholar
Pearl, J. (2012). The causal foundations of structural equation modeling. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 68–91). New York, NY: Guilford Press.Google Scholar
Peng, J.-E., & Woodrow, L. (2010). Willingness to communicate in English: A model in the Chinese EFL classroom context. Language Learning, 60, 834–876. doi:10.1111/j.1467-9922.2010.00576.xGoogle Scholar
Perfetti, C. A., & Lesgold, A. M. (1977). Discourse comprehension and sources of individual differences. In Just, M. A. & Carpenter, P. A. (Eds.), Cognitive processes in comprehension (pp. 141–183). Hillsdale, NJ: Erlbaum.Google Scholar
Phakiti, A. (2008a). Construct validation of Bachman and Palmer's (1996) strategic competence model over time in EFL reading tests. Language Testing, 25, 237–272.Google Scholar
Phakiti, A. (2008b). Strategic competence as a fourth-order factor model: A structural equation modeling approach. Language Assessment Quarterly, 5, 20–42.Google Scholar
Plonsky, L. (2013). Study quality in SLA: An assessment of designs, analyses, and reporting practices in quantitative L2 research. Studies in Second Language Acquisition, 35, 655–687.Google Scholar
Proctor, C. P., August, D., Snow, C., & Barr, C. D. (2010). The interdependence continuum: A perspective on the nature of Spanish-English bilingual reading comprehension. Bilingual Research Journal, 33, 5–20.Google Scholar
Pulido, D., & Hambrick, D. Z. (2008). The virtuous circle: Modeling individual differences in L2 reading and vocabulary development. Reading in a Foreign Language, 20, 164–190.Google Scholar
Purpura, J. (1998). Investigating the effects of strategy use and second language test performance with high and low ability test takers: A structural equational modeling approach. Language Testing, 15, 333–379.Google Scholar
Raykov, T. (2012). Scale construction and development using structural equation modeling. In Hoyle, R. H. (Ed.), Handbook of structural equation modeling (pp. 472–492). New York, NY: Guilford Press.Google Scholar
Raykov, T., Dimitrov, D. M., & Asparouhov, T. (2010). Evaluation of scale reliability with binary measures using latent variable modeling. Structural Equation Modeling: A Multidisciplinary Journal, 17, 265–279. doi:10.1080/10705511003659417Google Scholar
Raykov, T., & Marcoulides, G. A. (2006). A first course in structural equation modeling (2nd ed.). Mahwah, NJ: Erlbaum.Google Scholar
Raykov, T., & Marcoulides, G. A. (2013). Meta-analysis of scale reliability using latent variable modeling. Structural Equation Modeling: A Multidisciplinary Journal, 20, 338–353. doi:10.1080/10705511.2013.769396Google Scholar
Razagifard, P., & Rahimpour, M. (2010). The effect of computer-mediated corrective feedback on the development of second language learners’ grammar. International Journal of Instructional Technology & Distance Learning, 7. Retrieved from http://itdl.org/Journal/May_2010/article2002.htmGoogle Scholar
Rivers, D. J. (2010). National identification and intercultural relations in foreign language learning. Language and Intercultural Communication, 10, 318–336. doi:10.1080/14708477.2010.502234Google Scholar
Robinson, J. P., Rivers, W. P., & Brecht, R. D. (2006). Demographic and sociopolitical predictors of American attitudes toward foreign language policy. Language Policy, 5, 419–440. doi:10.1007/s10993-006-9033-4Google Scholar
Sasaki, M. (1993). Relationships among second language proficiency, foreign language aptitude, and intelligence: A structural equation modeling approach. Language Learning, 43, 313–344.Google Scholar
Schoonen, R. (2005). Generalizability of writing scores: An application of structural equation modeling. Language Testing, 22, 1–30.Google Scholar
Schoonen, R., Van Gelderen, A., De Glopper, K., Hulstijn, J., Simis, A., Snelling, P., & Stevenson, M. (2003). First language and second language writing: The role of linguistic knowledge, speed of processing and metacognitive knowledge. Language Learning, 53, 165–202.Google Scholar
Schoonen, R., van Gelderen, A., Stoel, R. D., Hulstijn, J., & de Glopper, K. (2011). Modeling the development of L1 and EFL writing proficiency of secondary school students. Language Learning, 61, 31–79. doi:10.1111/j.1467–9922.2010.00590.xGoogle Scholar
Schumacker, R. E., & Lomax, R. G. (2010). A beginner's guide to structural equation modeling (3rd ed.). New York, NY: Routledge.Google Scholar
Segalowitz, N., & Freed, B. F. (2004). Context, contact, and cognition in oral fluency acquisition: Learning Spanish in at home and study abroad contexts. Studies in Second Language Acquisition, 26, 173–199.Google Scholar
Skehan, P. (2002). Theorising and updating aptitude. In Robinson, P. (Ed.), Individual differences and instructed language learning (pp. 69–93). Philadelphia, PA: John Benjamins.Google Scholar
Song, M.-Y. (2008). Do divisible subskills exist in second language (L2) comprehension? A structural equation modeling approach. Language Testing, 25, 435–464.Google Scholar
Song, M.-Y. (2012). Note-taking quality and performance on an L2 academic listening test. Language Testing, 29, 67–89. doi:10.1177/0265532211415379Google Scholar
Stracke, E. (2007). A road to understanding: A qualitative study into why learners drop out of a blended language learning (BLL) environment. ReCALL, 19, 57–78.Google Scholar
Tseng, W.-T., & Schmitt, N. (2008). Toward a model of motivated vocabulary learning: A structural equation modeling approach. Language Learning, 58, 357–400.Google Scholar
Tseng, Y.-C., & Liou, H.-C. (2006). The effects of online conjunction materials on college EFL students’ writing. System, 34, 270–283.Google Scholar
Tremblay, P. F., & Gardner, R. C. (1995). Expanding the motivation construct in language learning. The Modern Language Journal, 79, 505–518.Google Scholar
Tremblay, P. F., & Gardner, R. C. (1996). On the growth of structural equation modeling in psychological journals. Structural Equation Modeling, 3, 93–104.Google Scholar
Turner, C. E. (1989). The underlying factor structure of L2 close test performance in Francophone, university-level students: Causal modelling as an approach to construct validation. Language Testing, 6, 172–197. doi:10.1177/026553228900600205Google Scholar
Ushioda, E., & Dörnyei, Z. (2012). Motivation. In Gass, S. M. & Mackey, A. (Eds.), The Routledge handbook of second language acquisition (pp. 396–409). New York, NY: Routledge.Google Scholar
Vandewaetere, M., Desmet, P., & Leuven, K. U. (2010). The influence of learners’ attitudes to and perceptions of CALL: A methodological approach. ITL—International Journal of Applied Linguistics, 160, 1–23.CrossRefGoogle Scholar
Verhoeven, L. (2007). Early bilingualism, language transfer, and phonological awareness. Applied Psycholinguistics, 28, 425–439. doi:10.1017/S0142716407070233Google Scholar
Winke, P. (2013). An investigation into second language aptitude for advanced Chinese language learning. The Modern Language Journal, 97, 109–130. doi:10.1111/j.1540-4781.2013.01428.xGoogle Scholar
Wolfgramm, C., Rau, M., Zander-Musić, L., Neuhaus, J., & Hannover, B. (2010). On the connection between collective self-worth and the motivation to learn German: A study of students with a migration background in Germany and Switzerland. Zeitschrift für Pädagogik, 56, 59–77.Google Scholar
Woodrow, L. J. (2006). A model of adaptive language learning. The Modern Language Journal, 90, 297–319.Google Scholar
Xie, Q., & Andrews, S. (2013). Do test design and uses influence test preparation? Testing a model of washback with structural equation modeling. Language Testing, 30, 49–70.Google Scholar
Yaghoub Zadeh, Z., Farnia, F., & Geva, E. (2012). Toward modeling reading comprehension and reading fluency in English language learners. Reading and Writing, 25, 163–187.CrossRefGoogle Scholar
Yang, H.-C. (2012). Modeling the relationships between test-taking strategies and test performance on a graph-writing task: Implications for EAP. English for Specific Purposes, 31, 174–187.Google Scholar
Yashima, T. (2002). Willingness to communicate in a second language: The Japanese EFL context. The Modern Language Journal, 86, 54–66.Google Scholar
Yu, B. (2010). Learning Chinese abroad: The role of language attitudes and motivation in the adaptation of international students in China. Journal of Multilingual and Multicultural Development, 31, 301–321.Google Scholar
Zhang, D. (2012). Vocabulary and grammar knowledge in second language reading comprehension: A structural equation modeling study. The Modern Language Journal, 96, 558–575.Google Scholar