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How do textual features of L2 argumentative essays differ across proficiency levels? A multidimensional cross-sectional study

  • Jeong-eun KimEmail author
  • Hosung NamEmail author
Article
  • 33 Downloads

Abstract

Using Biber’s (1988) multidimensional analysis, this study investigates textual variation in second language (L2) learners’ writing at different proficiency levels, and attempts to identify any developmental progression. The study used a corpus of 5200 argumentative essays written by 2600 students learning English as an L2. The results indicate that advanced L2 writing is fundamentally different from less advanced L2 writing: Advanced learners’ writing is closer to native speakers’ written discourse, while less advanced learners’ writing is closer to native speakers’ spoken discourse. The patterns of development vary across different sets of textual features. Informational (as opposed to involved) production and impersonal (as opposed to nonimpersonal) style showed gradual development as the learners’ proficiency increases. Nonnarrative (as opposed to narrative) production, elaborated (as opposed to situation-dependent) reference, and overt expression of persuasion did not show significant differences across the proficiency levels. The article offers pedagogical implications for practices of L2 writing instruction.

Keywords

Corpus linguistics Cross-sectional research Mixed-effects model Multidimensional analysis Argumentative writing Second language writing 

Notes

Acknowledgements

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5A2A03926788).

References

  1. Ai, H., & Lu, X. (2013). A corpus-based comparison of syntactic complexity in NNS and NS university students’ writing. In A. Díaz-Negrillo, N. Ballier, & P. Thompson (Eds.), Automatic treatment and analysis of learner corpus data (pp. 249–264). Amsterdam: John Benjamins.CrossRefGoogle Scholar
  2. Baayen, R. H. (2008). Analyzing linguistic data: A practical introduction to statistics using R. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  3. Becker, A. (2010). Distinguishing linguistic and discourse features in ESL students’ written performance. Modern Journal of Applied Linguistics, 2, 406–424.Google Scholar
  4. Biber, D. (1988). Variation across speech and writing. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  5. Biber, D., Conrad, S., Reppen, R., Byrd, P., & Helt, M. (2002). Speaking and writing in the university: A multidimensional comparison. TESOL Quarterly, 36, 9–48.CrossRefGoogle Scholar
  6. Biber, D., & Gray, B. (2013). Discourse characteristics of writing and speaking task types on the TOEFL iBT test: A lexico-grammatical analysis (TOEFL iBT research report 19). Princeton, NJ: Educational Testing Service.Google Scholar
  7. Biber, D., Gray, B., & Poonpon, K. (2011). Should we use characteristics of conversation to measure grammatical complexity in L2 writing development? TESOL Quarterly, 45, 5–35.CrossRefGoogle Scholar
  8. Biber, D., Gray, B., & Staples, S. (2016). Predicting patterns of grammatical complexity across language exam task types and proficiency levels. Applied Linguistics, 37, 639–668.CrossRefGoogle Scholar
  9. Crosthwaite, P. (2016). A longitudinal multidimensional analysis of EAP writing: Determining EAP course effectiveness. Journal of English for Academic Purposes, 22, 166–178.CrossRefGoogle Scholar
  10. Ferris, D. R. (1994). Lexical and syntactic features of ESL writing by students at different levels of L2 proficiency. TESOL Quarterly, 28, 414–420.CrossRefGoogle Scholar
  11. Frase, L. T., Faletti, A., Ginther, A., & Grant, L. (1999). Computer analysis of the TOEFL test of written English. Princeton, NJ: Educational Testing Service.Google Scholar
  12. Friginal, E., & Hardy, J. A. (2014). Conducting Biber’s corpus-based multi-dimensional analysis using SPSS. In T. Berber-Sardinha & M. Veirano-Pinto (Eds.), Multi-dimensional analysis, 25 years on: A tribute to Douglas Biber (pp. 297–316). Philadelphia, PA: John Benjamins.CrossRefGoogle Scholar
  13. Friginal, E., & Weigle, S. (2014). Exploring multiple profiles of L2 writing using multi-dimensional analysis. Journal of Second Language Writing, 26, 80–95.CrossRefGoogle Scholar
  14. Grace-Martin, K. (2019). Specifying fixed and random factors in mixed models. Retrieved from https://www.theanalysisfactor.com/specifying-fixed-and-random-factors-in-mixed-models/. Accessed 27 Mar 2019.
  15. Grant, L., & Ginther, A. (2000). Using computer-tagged linguistic features to describe L2 writing differences. Journal of Second Language Writing, 9(2), 123–145.CrossRefGoogle Scholar
  16. Ishikawa, S. (2019). The ICNALE: The international corpus network of Asian learners of English. Retrieved from http://language.sakura.ne.jp/icnale/. Accessed 27 Mar 2019.
  17. Jarvis, S., Grant, L., Bikowski, D., & Ferris, D. (2003). Exploring multiple profiles of highly rated learner compositions. Journal of Second Language Writing, 12, 377–403.CrossRefGoogle Scholar
  18. Lu, X. (2011). A corpus-based evaluation of syntactic complexity measures as indices of college-level ESL writers’ language development. TESOL Quarterly, 45, 36–62.CrossRefGoogle Scholar
  19. Nation, I. S. P., & Beglar, D. (2007). A vocabulary size test. The Language Teacher, 31(7), 9–13.Google Scholar
  20. Nini, A. (2015). Multidimensional analysis tagger (version 1.3). Retrieved from http://sites.google.com/site/multidimensionaltagger. Accessed 27 Mar 2019.
  21. Ortega, L. (2003). Syntactic complexity measures and their relationship to L2 proficiency: A research synthesis of college-level L2 writing. Applied Linguistics, 24, 492–518.CrossRefGoogle Scholar
  22. Rosenthal, R., & Rosnow, R. L. (1984). Essentials of behavioral research: Methods and data analysis. New York, NY: McGraw-Hill.Google Scholar
  23. Shaw, P., & Liu, E. T. (1998). What develops in the development of second-language writing? Applied Linguistics, 19, 225–254.CrossRefGoogle Scholar
  24. Staples, S., Biber, D., & Reppen, R. (2018). Using corpus-based register analysis to explore the authenticity of high-stakes language exams: A register comparison of TOEFL iBT and disciplinary writing tasks. The Modern Language Journal, 102, 310–332.CrossRefGoogle Scholar
  25. Taguchi, N., Crawford, W., & Wetzel, D. Z. (2013). What linguistic features are indicative of writing quality? A case of argumentative essays in a college composition program. TESOL Quarterly, 47, 420–430.CrossRefGoogle Scholar
  26. Weigle, S. C., & Friginal, E. (2015). Linguistic dimensions of impromptu test essays compared with successful student disciplinary writing: Effects of language background, topic, and L2 proficiency. Journal of English for Academic Purposes, 18, 25–39.CrossRefGoogle Scholar
  27. Winter, B. (2013). A very basic tutorial for performing linear mixed effects analyses (Tutorial 2). Retrieved from www.bodowinter.com/tutorial/bw_LME_tutorial2.pdf. Accessed 27 Mar 2019.
  28. Wolfe-Quintero, K., Inagaki, S., & Kim, H. Y. (1998). Second language development in writing: Measures of fluency, accuracy, and complexity (report no. 17). Honolulu: University of Hawaii Press.Google Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of English Language and LiteratureChonbuk National UniversityJeonju-siRepublic of Korea
  2. 2.Department of English Language and LiteratureKorea UniversitySeoulRepublic of Korea
  3. 3.Haskins LaboratoriesNew HavenUSA

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