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Using Concordance Software to Generate Academic Words in Applied Linguistics Weningtyas Parama Iswari; Bibit Suhatmady; Yuni Utami Asih; Ida Wardani; Adrianto Ramadhan; Dynda Anastasya
Educational Studies: Conference Series Vol 1 No 1 (2021)
Publisher : Faculty of Teacher Training and Education, Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/escs.v1i1.882

Abstract

Academic words include words that are not commonly encountered in formal circumstances and specific to particular fields of study. Undergraduate students of the English Department are required to acquire academic words in applied linguistics for academic reading and writing research articles. This paper reports on generating the academic word list for the students of the English Department by using AntConc, a concordance software application. In this study, corpus linguistic research was adopted, in particular the corpus-based analysis category. Data were gathered from approximately one thousand credible Applied Linguistics journal articles published from 2008 to 2021. AntConc software played a significant role in processing these data to get the intended corpus, which was then classified and categorized based on the frequency of occurrences. The results include an academic word list and its word family. These clusters of academic words are intended for undergraduate students of the English Department in the first up to fourth academic semesters to prepare them to participate in international academic discourse, such as writing and publishing research articles. This list can also be used as a basis for further research related to academic vocabulary. Academic words include words that are not commonly encountered in formal circumstances and specific to particular fields of study. Undergraduate students of the English Department are required to acquire academic words in applied linguistics for academic reading and writing research articles. This paper reports on generating the academic word list for the students of the English Department by using AntConc, a concordance software application. In this study, corpus linguistic research was adopted, in particular the corpus-based analysis category. Data were gathered from approximately one thousand credible Applied Linguistics journal articles published from 2008 to 2021. AntConc software played a significant role in processing these data to get the intended corpus, which was then classified and categorized based on the frequency of occurrences. The results include an academic word list and its word family. These clusters of academic words are intended for undergraduate students of the English Department in the first up to fourth academic semesters to prepare them to participate in international academic discourse, such as writing and publishing research articles. This list can also be used as a basis for further research related to academic vocabulary.
A Corpus-Based Study On The Use Of Reporting Verbs In Applied Linguistics Journal Articles Published From 2020-2024 Adrianto Ramadhan; Weningtyas Parama Iswari; Aridah
E3L: Journal of English Language Teaching, Linguistics, and Literature Vol. 8 No. 1 (2025): March
Publisher : English Department, Faculty of Teacher Training and Education, Mulawarman University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/e3l.v8i1.5242

Abstract

Reporting verbs are essential in academic writing because they help convey the writer's stance, attitude, and relationship with the reader, as highlighted in corpus-based research. This research was a corpus-based study that investigated the use of reporting verbs in applied linguistics journal articles published between 2020 and 2024. The main objectives were to identify the categories of reporting verbs used in the articles and determine the most frequently used categories within this period. This research applied a corpus linguistic technique, which used quantitative methods. The study specifically focuses on the frequency of reporting verbs in journal articles published within the selected time period. A corpus of 316 articles from the Indonesian Journal of Applied Linguistics was used as a data for the analysis. The data was processed using the software tool AntConc 4.2.0, which allowed for a detailed examination of the reporting verb frequencies and their categorization. The results revealed that Discourse Acts were the most frequently used reporting verbs, followed by Research Acts and Cognition Acts. Within the Discourse Acts category, the "certainty" subcategory emerged as the most prevalent.