Publication Date
| In 2026 | 0 |
| Since 2025 | 4 |
| Since 2022 (last 5 years) | 17 |
| Since 2017 (last 10 years) | 29 |
| Since 2007 (last 20 years) | 59 |
Descriptor
Source
| Computer Assisted Language… | 61 |
Author
Publication Type
| Journal Articles | 61 |
| Reports - Research | 46 |
| Tests/Questionnaires | 10 |
| Reports - Descriptive | 9 |
| Information Analyses | 3 |
| Reports - Evaluative | 3 |
| Opinion Papers | 2 |
Education Level
| Higher Education | 40 |
| Postsecondary Education | 33 |
| Secondary Education | 2 |
| Adult Education | 1 |
| Elementary Secondary Education | 1 |
| High Schools | 1 |
Audience
| Researchers | 1 |
| Teachers | 1 |
Location
| Taiwan | 12 |
| China | 8 |
| Iran | 4 |
| South Korea | 4 |
| Hong Kong | 3 |
| United Kingdom | 3 |
| Asia | 2 |
| Australia | 2 |
| Saudi Arabia | 2 |
| California (San Francisco) | 1 |
| Canada | 1 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| Dale Chall Readability Formula | 1 |
| Flesch Kincaid Grade Level… | 1 |
| Flesch Reading Ease Formula | 1 |
| SAT (College Admission Test) | 1 |
| Test of English for… | 1 |
What Works Clearinghouse Rating
Chung, Eun Seon; Ahn, Soojin – Computer Assisted Language Learning, 2022
Many studies that have investigated the educational value of online machine translation (MT) in second language (L2) writing generally report significant improvements after MT use, but no study as of yet has comprehensively analyzed the effectiveness of MT use in terms of various measures in syntactic complexity, accuracy, lexical complexity, and…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
Chen, Hao-Jan Howard; Lai, Shu-Li; Lee, Ken-Yi; Yang, Christine Ting-Yu – Computer Assisted Language Learning, 2023
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.…
Descriptors: Academic Language, English for Academic Purposes, Phrase Structure, Computational Linguistics
Guo, Qian; Feng, Ruiling; Hua, Yuanfang – Computer Assisted Language Learning, 2022
AWCF can facilitate academic writing development, especially for novice writers of English as a foreign language (EFL). Existing AWCF studies mainly focus on teacher and learner perceptions; fewer have investigated the error-correction effect of AWCF and factors related to the effect. Especially lacking is research on how successfully students can…
Descriptors: Error Correction, Feedback (Response), English (Second Language), Second Language Learning
Vakili, Shokoufeh; Ebadi, Saman – Computer Assisted Language Learning, 2022
Theoretically grounded in Vygotsky's sociocultural theory of mind, Dynamic Assessment (DA) provides researchers with the opportunity to investigate different aspects of learners' developmental trajectory, including the ways they overcome their errors. As a qualitative inquiry into the nature of errors reflecting learners' development in academic…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Assisted Testing
Tsai, Kuei-Ju – Computer Assisted Language Learning, 2019
Corpora are well-known for the affordance to make linguistic regularities salient. Since the coinage of the term 'data-driven learning' (DDL) in the 1990s, much has been done to investigate the effects of DDL on learning vocabulary, most notably lexico-grammatical patterns. However, less researched is how learners construct vocabulary knowledge…
Descriptors: Dictionaries, Computational Linguistics, Second Language Learning, Second Language Instruction
Yang, Juan; Thomas, Michael S. C.; Qi, Xiaofei; Liu, Xuan – Computer Assisted Language Learning, 2019
From a psycholinguistic perspective of view, there are many cognitive differences that matter to individuals' second-language acquisition (SLA). Although many computer-assisted tools have been developed to capture and narrow the differences among learners, the use of these strategies may be highly risky because changing the environments or the…
Descriptors: Foreign Countries, Cognitive Ability, Phonological Awareness, English Teachers
Goh, Tiong-Thye; Sun, Hui; Yang, Bing – Computer Assisted Language Learning, 2020
This study investigates the extent to which microfeatures -- such as basic text features, readability, cohesion, and lexical diversity based on specific word lists -- affect Chinese EFL writing quality. Data analysis was conducted using natural language processing, correlation analysis and stepwise multiple regression analysis on a corpus of 268…
Descriptors: Essays, Writing Tests, English (Second Language), Second Language Learning
Kennedy, Claire; Miceli, Tiziana – Computer Assisted Language Learning, 2017
While there is widespread agreement on the expected benefits of hands-on access to corpora for language learners, reports abound of the difficulties involved in realising those benefits in practice. A particular focus of discussion is the challenge of transferring the skills of the corpus linguist to learners, so that they can explore this type of…
Descriptors: Computational Linguistics, Teaching Methods, Second Language Learning, Second Language Instruction
Harvey-Scholes, Calum – Computer Assisted Language Learning, 2018
Software can facilitate English as a Foreign Language (EFL) students' self-correction of their free-form writing by detecting errors; this article examines the proportion of errors which software can detect. A corpus of 13,644 words of written English was created, comprising 90 compositions written by Spanish-speaking students at levels A2-B2…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Error Correction
Lee, Sangmin-Michelle – Computer Assisted Language Learning, 2020
Although it remains controversial, machine translation (MT) has gained popularity both inside and outside of the classroom. Despite the growing number of students using MT, little is known about its use as a pedagogical tool in the EFL classroom. The present study investigated the role of MT as a CALL tool in EFL writing. Most studies on MT as a…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
Tsai, Shu-Chiao – Computer Assisted Language Learning, 2019
This study investigates the impact on extemporaneous English-language first drafts by using Google Translate (GT) in three different tasks assigned to Chinese sophomore, junior, and senior students of English as a Foreign Language (EFL) majoring in English. Students wrote first in Chinese (Step 1), then drafted corresponding texts in English (Step…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Software
Ballance, Oliver James – Computer Assisted Language Learning, 2017
One of the most promising avenues of research in computer-assisted language learning is the potential for language learners to make use of language corpora. However, using a corpus requires use of a corpus tool as an interface, typically a concordancer. How such a tool can be made most accessible to learners is an important issue. Specifically,…
Descriptors: Teaching Methods, Indexes, Multivariate Analysis, Classification
Ranalli, Jim – Computer Assisted Language Learning, 2018
Automated written corrective feedback (AWCF) has qualities that distinguish it from teacher-provided WCF and potentially undermine claims about its value for L2 student writers, including disparities in the amounts of useful information it provides across error types and the fact that inaccuracies in error-flagging must be anticipated. It remains…
Descriptors: Error Correction, Feedback (Response), Computer Assisted Instruction, Second Language Learning
Crosthwaite, Peter – Computer Assisted Language Learning, 2017
An increasing number of studies have looked at the value of corpus-based data-driven learning (DDL) for second language (L2) written error correction, with generally positive results. However, a potential conundrum for language teachers involved in the process is how to provide feedback on students' written production for DDL. The study looks at…
Descriptors: Feedback (Response), Error Correction, Morphology (Languages), Syntax
Yu, Ping; Pan, Yingxin; Li, Chen; Zhang, Zengxiu; Shi, Qin; Chu, Wenpei; Liu, Mingzhuo; Zhu, Zhiting – Computer Assisted Language Learning, 2016
Oral production is an important part in English learning. Lack of a language environment with efficient instruction and feedback is a big issue for non-native speakers' English spoken skill improvement. A computer-assisted language learning system can provide many potential benefits to language learners. It allows adequate instructions and instant…
Descriptors: English (Second Language), Foreign Countries, Second Language Instruction, Computer Assisted Instruction

Peer reviewed
Direct link
