Developing and Evaluating an Academic Collocations and Phrases Search Engine for Academic Writers

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Autor/inn/en	Chen, Hao-Jan Howard; Lai, Shu-Li; Lee, Ken-Yi; Yang, Christine Ting-Yu
Titel	Developing and Evaluating an Academic Collocations and Phrases Search Engine for Academic Writers
Quelle	In: Computer Assisted Language Learning, 36 (2023) 4, S.641-668 (28 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Chen, Hao-Jan Howard) ORCID (Lai, Shu-Li) ORCID (Lee, Ken-Yi) ORCID (Yang, Christine Ting-Yu)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0958-8221
DOI	10.1080/09588221.2021.1937229
Schlagwörter	Academic Language; English for Academic Purposes; Phrase Structure; Computational Linguistics; Second Language Instruction; Second Language Learning; Interdisciplinary Approach; Search Engines; Periodicals; Databases; Comparative Analysis; Student Attitudes; Language Tests; Student Improvement; Writing Instruction; Foreign Countries; Majors (Students); English (Second Language); Graduate Students; Undergraduate Students; Likert Scales; North American English; Instructional Effectiveness; Taiwan + Suchen Sie Ihr Suchwort? Academic; Language; Languages; Akademiker; Sprache; Wissenschaftssprache; Phrasenstruktur; Linguistics; Computerlinguistik; Fremdsprachenunterricht; Zweitsprachenerwerb; Fächerübergreifender Unterricht; Fächerverbindender Unterricht; Interdisziplinarität; Suchmaschine; Periodical; Journal; Zeitschrift; Fachzeitschrift; Periodikum; Datenbank; Schülerverhalten; Language test; Sprachtest; Schreibunterricht; Ausland; English as second language; English; Second Language; Englisch als Zweitsprache; Graduate Study; Student; Students; Aufbaustudium; Graduiertenstudium; Hauptstudium; Studentin; Likert-Skala; Amerikanisches Englisch; Unterrichtserfolg
Abstract	Knowledge of collocations is essential for English academic writing. However, there are few academic collocation referencing tools available and there is a pressing need to develop more. In this paper, we will introduce the ACOP (Academic Collocations and Phrases Search Engine), a newly developed corpus-based tool to search large academic corpora. Using the AntCorGen corpus crawling tool, 100,000 articles from 10 academic areas were downloaded from the PLOS One journal database. A multidisciplinary 500-million-word academic corpus was thus created. Our team further developed the ACOP to allow users to search for collocations and phrases in the academic corpus that we compiled. Additionally, this new tool will allow learners to search for not only bigrams but also for three- to five-word strings. Learners can further search using parts of speech. To validate whether the new tool can assist EFL learners in finding appropriate academic collocations, we compared this tool with BYU's state-of-the-art COCA corpus search tool. The 35 students who participated in the study were randomly divided into two groups. One group used BYU's COCA tool and the other used the ACOP tool. Both groups were asked to identify suitable collocates for 25 gap-fill questions. Paired t-tests and independent t-tests were used to analyze the data. The results indicated that both groups showed a significant improvement in the posttest when they had access to the collocation retrieval systems. However, statistically, the results showed no significant difference between the two tools, as they were equally useful in helping the students find appropriate collocates. According to the users' surveys, compared with the COCA group, the participants in the ACOP group found the ACOP easier to use and the interface was clearer and simpler. The Mann-Whitney U tests of the two groups showed significant differences in the aspect of the interface. The preliminary results indicated that the ACOP can assist EFL learners in finding suitable academic collocations and phrases, and the users' surveys showed positive results. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01