An Assistive Environment for EAL Academic Writing Using Formulaic Sequences Classification

Autor/inn/en	Abbas, Muhammad Azeem; Hammad, Shiza; Hwang, Gwo-Jen; Khan, Sharifullah; Gilani, Syed Mushhad Mustuzhar
Titel	An Assistive Environment for EAL Academic Writing Using Formulaic Sequences Classification
Quelle	In: Interactive Learning Environments, 31 (2023) 1, S.407-421 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Abbas, Muhammad Azeem) ORCID (Hwang, Gwo-Jen)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2020.1789670
Schlagwörter	English (Second Language); Second Language Instruction; Writing Strategies; Writing Instruction; Writing Improvement; Academic Language; Instructional Effectiveness; Graduate Students; Phrase Structure; Artificial Intelligence; Classification; Technology Uses in Education; Journal Articles + Suchen Sie Ihr Suchwort? English as second language; English; Second Language; Englisch als Zweitsprache; Fremdsprachenunterricht; Schreibtechnik; Schreibunterricht; Academic; Language; Languages; Akademiker; Sprache; Wissenschaftssprache; Unterrichtserfolg; Graduate Study; Student; Students; Aufbaustudium; Graduiertenstudium; Hauptstudium; Studentin; Phrasenstruktur; Künstliche Intelligenz; Classification system; Klassifikation; Klassifikationssystem; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Journal article; Zeitschriftenaufsatz
Abstract	Writing an English research article for novice English as an additional language (EAL) writers is a challenging task that requires experience and training at both the sentence and meaning levels. One strategy that EAL writers employ when writing a research article is the use of formulaic sequences (FSs). However, available FS corpora are general purpose and are very limited in size. Previous studies have reported the effectiveness of FS usage in writing using a small set of FSs. The present work proposes an assistive environment for academic writing improvement through the use of domain-specific FSs. FSs are extracted from published articles and are classified under rhetoric categories using a machine learning technique. The user can then search for and add new FSs of his/her choice from any research article using proposed prototypes. The effectiveness of the proposed approach was evaluated in a real environment. The results show a positive impact of the proposal in terms of academic writing improvement. Novice writers who worked with the proposed prototype reported a significantly higher degree of perceived usefulness than those who worked with the traditional phrasebank approach. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01