Research Article

A Scientometric Review of Syntactic Complexity in L2 writing based on Web of Science (2010-2022)

Authors

  • Ruimin Song College of Foreign Languages, Ocean University of China, Qingdao, China

Abstract

As an important construct in the field of second language teaching and assessment, syntactic complexity is closely related to the language proficiency and language development process of L2 learners. Using the visualization software of CiteSpace, this study conducts an in-depth scientometric analysis of 140 articles on written syntactic complexity published over the past 10 years (2010-2022), thus uncovering the current development and challenges faced by relevant studies. Specifically, a frequency analysis was firstly administrated to describe the overall development in written syntactic complexity research. Furthermore, the current study conducted a Document Co-Citation Analysis (DCA), which enables researchers to conduct a network of co-cited references to identify the underlying research hotpots and future trends. The results indicate that the study concerning automatic essay scoring is the most prominent cluster active from 2010 to 2021. In addition, Norris & Ortega (2009) is the most cited paper, followed by Ortega (2003) and Biber et al. (2011). Meanwhile, the bursts of detected papers demonstrate that McNamara et al. (2012) and Grant & Ginther (2000) generated the strongest citation burst with a burst strength of 3.14 and 3.09, respectively. The findings of the study would have implications for subsequent research on written syntactic complexity in the field of language teaching and language learning.

Article information

Journal

International Journal of Linguistics, Literature and Translation

Volume (Issue)

5 (1)

Pages

18-27

Published

2022-01-05

How to Cite

Song, R. (2022). A Scientometric Review of Syntactic Complexity in L2 writing based on Web of Science (2010-2022). International Journal of Linguistics, Literature and Translation, 5(1), 18–27. https://doi.org/10.32996/ijllt.2022.5.1.3

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Keywords:

Scientometric Review