Article published In: Journal of English for Research Publication Purposes
Vol. 4:2 (2023) ► pp.109–139
Japanese scientists’ English for research publication purposes
An empirical error analysis
Published online: 19 December 2023
https://doi.org/10.1075/jerpp.22007.mcd
https://doi.org/10.1075/jerpp.22007.mcd
Abstract
Error Analysis was developed by early Second Language Acquisition (SLA) researchers as a way to investigate
interlanguage and better understand the second-language learning processes. While it is no longer an active branch of research in
SLA, it remains a useful tool for those concerned with accuracy in language use. Given the elevated importance of accuracy in
English for Research and Publication Purposes (ERPP), this may be one area where Error Analysis may continue to inform research
and praxis. The high degree of language precision demanded in ERPP contexts can be a source of frustration for many engaged in
scholarly publication, especially those for whom English is an additional language, such as the Japanese scientists studied in
this paper. For Japanese scientists and possibly others, an empirical profile of their most frequent error patterns may help them
to better deal with accuracy in research writing. With this motivation, this study applies a corpus-assisted error analysis
framework to quantify sentence-level grammar errors and identify the most frequent error patterns in the research article
manuscripts of Japanese scientists. A corpus of 53 research article manuscripts with 4,495 errors comprises the primary data.
Additionally, two raters and a comparison of errors from scientists from six different L1 backgrounds are employed to triangulate
the data and investigate the reliability and generalizability of the findings. Findings reveal that the top ten most frequent
errors comprise 52.9%, or half of all errors in the corpus, and are dominated by errors with determiners and prepositions.
Article outline
- 1.Introduction
- 1.1Accuracy in research writing
- 1.2Error analysis
- 1.3The study
- 2.Procedure
- 2.1Participants
- 2.2Corpus preparation
- 2.3Error analysis
- 2.4Reliability and generalizability
- 3.Findings
- 3.1Overview of corpus
- 3.2Profile of most frequent error patterns
- 4.Conclusions
- Acknowledgements
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