The Korean Association for the Study of English Language and Linguistics
[ Article ]
Korea Journal of English Language and Linguistics - Vol. 22, No. 0, pp.1078-1100
ISSN: 1598-1398 (Print) 2586-7474 (Online)
Print publication date 31 Jan 2022
Received 02 Sep 2022 Revised 10 Oct 2022 Accepted 30 Oct 2022
DOI: https://doi.org/10.15738/kjell.22..202210.1078

The Use of Cohesive Devices in Korean EFL Writing across Different Proficiency Levels

Jungyeon Kim
Postdoctoral Researcher, Department of English Language and Literature, Yonsei University, Tel: 02) 2123-2329 jungyeonkim@yonsei.ac.kr


© 2022 KASELL All rights reserved
This is an open-access article distributed under the terms of the Creative Commons License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium provided the original work is properly cited.

Abstract

This study examines cohesive devices in the essays written by Korean EFL college learners across four common reference levels (CEFR) in the International Corpus Network of Asian Learners of English (ICNALE). The methodology used to analyze all cohesion features in this learner corpus is the assessment of cohesion using the Tool for the Automatic Analysis of Cohesion (TAACO). In order to see whether cohesion would vary across different proficiency levels in Korean EFL writing, this study examined fine-grained indices of four different kinds of components related to cohesive elements, i.e., lexical overlap, connectives, semantic overlap, and givenness. The statistical results suggest that the variable of lexical overlap (i.e., binary adjacent sentence overlap content lemmas) is a stronger predictor of EFL writing performance than the other variables of text cohesion. These findings expand previous corpus-based results regarding the evaluation of EFL writing quality, cohesive features in particular. The current study will bring about the expansion of new research that can investigate the role of cohesion analyses in accounting for foreign language writing proficiency.

Keywords:

cohesion, ICNALE, TAACO, Korean EFL writing

References

  • Akaike, H. 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716-723. [https://doi.org/10.1109/TAC.1974.1100705]
  • Bestgen, Y. and N. Vincze. 2012. Checking and boostrapping lexical norms by means of word similarity indexes. Behavior Research Methods 44, 998-1006. [https://doi.org/10.3758/s13428-012-0195-z]
  • Bird, S., K. Klein and E. Loper. 2009. Natural Language Processing with Python. Beijing, China: O’Reilly.
  • Cohen, J. 1988. Statistical Power Analysis for the Behavioral Sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum.
  • Connor, U. 1990. Linguistic/rhetorical measures for international persuasive student writing. Research in the Teaching of English 24, 67-87.
  • Cree, G. S. and B. C. Armstrong. 2012. Computational models of semantic memory. In M. Spivey, K. McRae and M. Joanisse, eds., The Cambridge Handbook of Psycholinguistics, 259-282. New York, NY: Cambridge University Press. [https://doi.org/10.1017/CBO9781139029377.014]
  • Crossley, S. A., K. Kyle and M. Dascalu. 2019. The tool for the automatic analysis of cohesion 2.0: Integrating semantic similarity and text overlap. Behavior Research Methods 51, 14-27. [https://doi.org/10.3758/s13428-018-1142-4]
  • Crossley, S. A., K. Kyle and D. S. McNamara. 2016. The development and use of cohesive devices in L2 writing and their relations to judgments of essay quality. Journal of Second Language Writing 32(2), 1-16. [https://doi.org/10.1016/j.jslw.2016.01.003]
  • Crossley, S. A. and D. S. McNamara. 2012. Predicting second language writing proficiency: The roles of cohesion and linguistic sophistication. Journal of Research in Reading 35, 115-135. [https://doi.org/10.1111/j.1467-9817.2010.01449.x]
  • Ferris, D. 1994. Lexical and syntactic features of ESL writing by students at different levels of L2 proficiency. TESOL Quarterly 28, 414-420. [https://doi.org/10.2307/3587446]
  • Foltz, P. W. 2007. Discourse coherence and LSA. In T. K. Landauer, D. S. McNamara, S. Dennis and W. Kintsch, eds., Handbook of Latent Semantic Analysis, 167-184. Mahwah, NJ: Erlbaum.
  • Frase, L., J. Faletti, A. Ginther and L. Grant. 1997. Computer Analysis of the TOEFL Test of Written English (TOEFL Research Rep. No. 64). Princeton, NJ: Educational Testing Service. [https://doi.org/10.1002/j.2333-8504.1998.tb01791.x]
  • Goss-Sampson, M. A. 2020. Statistical Analysis in JASP 0.14. https://jasp-stats.org/wp-content/uploads/2020/11/Statistical-Analysis-in-JASP-A-Students-Guide-v14-Nov2020.pdf
  • Grant, L. and A. Ginther. 2000. Using computer-tagged linguistic features to describe L2 writing differences. Journal of Second Language Writing 9, 123-145. [https://doi.org/10.1016/S1060-3743(00)00019-9]
  • Graesser, A. C., D. S. McNamara, M. M. Louwerse and Z. Cai. 2004. Coh-Metrix: Analysis of text on cohesion and language. Behavior Research Methods, Instruments, and Computers 36, 193-202. [https://doi.org/10.3758/BF03195564]
  • Guo, L., S. Crossley and D. S. McNamara. 2013. Predicting human judgments of essay quality in both integrated and independent second language writing samples: A comparison study. Assessing Writing 18, 218-238. [https://doi.org/10.1016/j.asw.2013.05.002]
  • Halliday, M. A. K. and R. Hasan. 1976. Cohesion in English. London, UK: Longman.
  • Halliday, M. A. K. and C. M. I. Matthiessen. 2004. An Introduction to Functional Grammar. London: Routledge.
  • Ishikawa, S. 2013. The ICNALE and sophisticated contrastive interlanguage analysis of Asian learners of English. In S. Ishikawa, ed., Learner Corpus Studies in Asia and the World 1, 91-118. Kobe, Japan: Kobe University.
  • Jafarpur, A. 1991. Cohesiveness as a basis for evaluating compositions. Systems 19, 459-465. [https://doi.org/10.1016/0346-251X(91)90026-L]
  • JASP Team. 2022. JASP (Version 0.16.3), Computer software.
  • Jin, W. 2001. A quantitative study of cohesion in Chinese graduate students’ writing: Variations across genres and proficiency levels. (ERIC document reproduction service no. ED 452 726).
  • Landauer, T. K., D. Laham and P. W. Foltz. 2000. The intelligent essay assessor. IEEE Intelligent Systems 15, 27-31.
  • Lee, Y.-J. 2021. The relationship between text cohesion features and English proficiency for Korean college students. Korean Journal of English Language and Linguistics 21, 435-449.
  • Liu, M. and G. Braine. 2005. Cohesive features in argumentative writing produced by Chinese undergraduates. System 33, 623-636. [https://doi.org/10.1016/j.system.2005.02.002]
  • McNamara, D. S. and W. Kintsch. 1996. Learning from texts: Effects of prior knowledge and text coherence. Discourse Processes 22, 247-288. [https://doi.org/10.1080/01638539609544975]
  • McNamara, D. S., E. Kintsch, N. B. Songer and W. Kintsch. 1996. Are good texts always better? Interactions of text coherence, background knowledge, and levels of understanding in learning from text. Cognition and Instruction 14, 1-43. [https://doi.org/10.1207/s1532690xci1401_1]
  • McNamara, D. S. and A. Graesser. 2012. Coh-Metrix: An automated tool for theoretical and applied natural language processing. In P. M. McCarthy and C. Boonthum, eds., Applied Natural Language Processing and Content Analysis: Identification, Investigation, and Resolution, 188-205. Hershey, PA: IGI Global. [https://doi.org/10.4018/978-1-60960-741-8.ch011]
  • Meara, P. and J. Milton. 2003. X_Lex, the Swansea Levels Test. Newbury, UK: Express Publishing.
  • Mikolov, T., I. Sutskever, K. Chen, G. Corrado and J. Dean. 2013. Distributed Representations of Words and Phrases and Their Compositionality. arXiv: 1310.4546, [cs.CL]
  • Miller, G. A. 1995. WordNet: A lexical database for English. Communications of the ACM 38, 39-41. [https://doi.org/10.1145/219717.219748]
  • Milton, J. 2010. The development of vocabulary breadth across the CEFR levels. In I. Bartning, M. Martin and J. Vedder, eds., Second Language Acquisition and Testing in Europe, 211-232. Online: Eurosla.
  • Nation, P. and D. Beglar. 2007. A vocabulary size test. The Language Teacher 31(7), 9-13.
  • Papageorgiou, S., J. T. Richard, B. Bridgeman and Y. Cho. 2015. The Association between TOEFL iBT Test Scores and the Common European Framework of Reference (CEFR) Levels (ETS Research Memorandum RM-15-06). Princeton, NJ: Educational Testing Service.
  • Project Gutenberg. (n.d.). Retrieved February 21, 2016, from www.gutenberg.org, .
  • Reid, J. 1990. Responding to different topic types: A quantitative analysis from a contrastive rhetoric perspective. In B. Kroll, ed., Second Language Writing: Research Insights for the Classroom, 191-210. Cambridge: Cambridge University Press. [https://doi.org/10.1017/CBO9781139524551.017]
  • Reppen, R. 1994. Variation in Elementary Student Language: A Multi-dimensional Pperspective. Unpublished doctoral dissertation, Northern Arizona University, Flagstaff.
  • Shapiro, S. S. and M. B. Wilk. 1965. An analysis of variance test for normality (complete samples). Biometrika 52(3-4), 591-611. [https://doi.org/10.1093/biomet/52.3-4.591]
  • Silva, T. 1993. Toward an understanding of the distinct nature of L2 writing: The ESL research and its implications. TESOL Quarterly 27(4), 657-675. [https://doi.org/10.2307/3587400]
  • Tabachnick, B. G. and L. S. Fidell. 2014. Using Multivariate Statistics. Harlow, UK: Pearson Education.
  • Whitten, I. A. and E. Frank. 2005. Data Mining. San Francisco, CA: Elsevier.
  • Witte, S. P. and L. Faigley. 1981. Coherence, cohesion and writing quality. College Composition and Communication 22, 189-204. [https://doi.org/10.2307/356693]
  • Yang, W. and Y. Sun. 2012. The use of cohesive devices in argumentative writing by Chinese EFL learners at different proficiency levels. Linguistics and Education 23, 31-48. [https://doi.org/10.1016/j.linged.2011.09.004]