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Fariba Foroutan Far; Mahboubeh Taghizadeh – Computer Assisted Language Learning, 2024
This study investigated the effects of digital and non-digital gamification on EFL learners' learning collocations, satisfaction, perceptions, and sense of flow. The participants divided into three groups of digitally gamified, non-digitally gamified, and non-gamified classes were 75 Iranian EFL students at B1 level. In each class, students were…
Descriptors: Gamification, Technology Uses in Education, English (Second Language), Second Language Learning
Tanjun Liu; Dana Gablasova – Computer Assisted Language Learning, 2025
Collocations, a crucial component of language competence, remain a challenge for L2 learners across all proficiency levels. While the data-driven learning (DDL) approach has shown great potential for collocation learning from a shorter-term perspective, this study investigates its effectiveness in the long term, examining both linguistic gains and…
Descriptors: Phrase Structure, Learning Analytics, English (Second Language), Second Language Instruction
Huang, Ping-Yu; Tsao, Nai-Lung – Computer Assisted Language Learning, 2021
In this article, we describe an online English collocation explorer developed to help English L2 learners produce correct and appropriate collocations. Our tool, which is able to visually represent relevant correct/incorrect collocations on a single webpage, was designed based on the notions of collocation clusters and intercollocability proposed…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Error Correction
Guoyuhui Huang; Khe Foon Hew – Computer Assisted Language Learning, 2024
Over the past two decades, the Involvement Load Hypothesis (ILH) has become a popular buzzword in the field of Second Language Acquisition (SLA). Although applications of the ILH can improve students' learning of productive vocabulary, this effect appears to be transitory. Students' learning of productive vocabulary often fades over time, as shown…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Vocabulary Development
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
Shadiev, Rustam; Yang, Meng-ke; Reynolds, Barry Lee; Hwang, Wu-Yuin – Computer Assisted Language Learning, 2022
In this study, the participants learned English as a foreign language (EFL) in the classroom and then worked on five learning tasks to apply their newly learned knowledge to unfamiliar environments. The participants took photos of people, objects, situations or scenarios and described them in detail using a mobile learning system. Familiarization…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Vocabulary Development
Lin, Vivien; Barrett, Neil E.; Liu, Gi-Zen; Chen, Nian-Shing; Jong, Morris Siu-Yung – Computer Assisted Language Learning, 2023
The field of language education has experienced a rise in using virtual reality (VR) to support interactive, contextualized, and collaborative language learning in recent years. The current study investigates the effects of auditory, visual, and textual input on speaking and writing in English for Tourism Purposes (ETP) through immersive,…
Descriptors: Tourism, English for Special Purposes, Undergraduate Students, Computer Simulation
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
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
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
Chen, Howard Hao-Jan; Wu, Jian-Cheng; Yang, Christine Ting-Yu; Pan, Iting – Computer Assisted Language Learning, 2016
The development of collocational knowledge is important for foreign language learners; unfortunately, learners often have difficulties producing proper collocations in the target language. Among the various ways of collocation learning, the DDL (data-driven learning) approach encourages the independent learning of collocations and allows learners…
Descriptors: Chinese, Phrase Structure, Second Language Learning, Computational Linguistics
Daskalovska, Nina – Computer Assisted Language Learning, 2015
One of the aspects of knowing a word is the knowledge of which words it is usually used with. Since knowledge of collocations is essential for appropriate and fluent use of language, learning collocations should have a central place in the study of vocabulary. There are different opinions about the best ways of learning collocations. This study…
Descriptors: Computational Linguistics, Phrase Structure, Verbs, Form Classes (Languages)
Rezaee, Abbas Ali; Marefat, Hamideh; Saeedakhtar, Afsaneh – Computer Assisted Language Learning, 2015
Collocational competence is recognized to be integral to native-like L2 performance, and concordancing can be of assistance in gaining this competence. This study reports on an investigation into the effect of symmetrical and asymmetrical scaffolding on the collocational competence of Iranian intermediate learners of English in the context of…
Descriptors: Computational Linguistics, Phrase Structure, Scaffolding (Teaching Technique), Foreign Countries
Kiliçkaya, Ferit – Computer Assisted Language Learning, 2015
This study aims to find out whether there are any statistically significant differences in participants' achievements on three different types of instruction: computer-based instruction, teacher-driven instruction, and teacher-driven grammar supported by computer-based instruction. Each type of instruction follows the deductive approach. The…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Grammar
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