Research Articles

With the global spread of English as the lingua franca for academic publishing, non-native researchers and university students are constantly facing linguistic barriers including insufficient vocabulary knowledge in writing for publication. This persistent need motivated the development of a good number of corpus-based word lists for frequently used academic and technical words in research articles across disciplines. Nevertheless, despite its importance in corpus-based study of language for word list development, replication research has received far less attention in this line of inquiry. The current study aimed to address this gap and replicated two published studies that investigated the use of academic vocabulary in applied linguistics research articles. To this end, research articles published from 2010 to 2020 in 20 well-known journals in the field were collected, and a corpus with around 48 million words was compiled and analyzed. The findings indicated that academic vocabulary accounted for 11.46% of the corpus, which is similar and close to the reported coverage of the AWL in replicated studies. However, regarding the frequently occurring academic and non-academic content words, the findings showed considerable variation with respect to the results reported earlier. In light of these findings, the study highlighted the importance of replication research to test the reliability of corpus-based vocabulary studies that developed field-specific academic word lists. Finally, the study developed an updated version for applied linguistics academic word list, that might be regarded as a resource and guide for the vocabulary learning component of the relevant EAP programs in the field.

Although researchers have analyzed the formal, syntactic, and functional behavior of cleft sentences in the English language across various genres, their distributional frequencies have received very little attention in academic research genres. Therefore, drawing on a 20,389,297-word corpus including 1,521 research articles (RAs), 116 PhD dissertations, and 48 textbooks, in applied linguistics, this study followed Biber et al.’s (1999) and Collins’ (2002) models to identify and analyze four major types of cleft structures in our corpus. Using a corpus-based research design, we drew on concordances to extract the target cleft structures. The computer program AntConc was used to identify instances of cleft sentences, and the statistical significance of the findings was evaluated through separate chi-square tests. The results of frequency analysis showed varying degrees of these grammatical structures across the three research genres, with textbooks including the highest number of clefts, followed by dissertations, and RAs. The results promise pedagogical implications for non-native English student writers to familiarize themselves with conventions in academic research genre writing for publication purposes. The findings suggest that academic research genre writing affects the frequency and use of these complex grammatical structures.