How do textual features of L2 argumentative essays differ across proficiency levels? A multidimensional cross-sectional study
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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.
KeywordsCorpus linguistics Cross-sectional research Mixed-effects model Multidimensional analysis Argumentative writing Second language writing
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5A2A03926788).
- Becker, A. (2010). Distinguishing linguistic and discourse features in ESL students’ written performance. Modern Journal of Applied Linguistics, 2, 406–424.Google Scholar
- 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
- 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
- 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.
- 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.
- Nation, I. S. P., & Beglar, D. (2007). A vocabulary size test. The Language Teacher, 31(7), 9–13.Google Scholar
- Nini, A. (2015). Multidimensional analysis tagger (version 1.3). Retrieved from http://sites.google.com/site/multidimensionaltagger. Accessed 27 Mar 2019.
- Rosenthal, R., & Rosnow, R. L. (1984). Essentials of behavioral research: Methods and data analysis. New York, NY: McGraw-Hill.Google Scholar
- 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.
- 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