Publication Date
| In 2026 | 0 |
| Since 2025 | 9 |
| Since 2022 (last 5 years) | 60 |
| Since 2017 (last 10 years) | 124 |
| Since 2007 (last 20 years) | 211 |
Descriptor
| Computer Assisted Instruction | 221 |
| English (Second Language) | 221 |
| Feedback (Response) | 205 |
| Second Language Learning | 183 |
| Second Language Instruction | 166 |
| Foreign Countries | 139 |
| Teaching Methods | 101 |
| Student Attitudes | 70 |
| Instructional Effectiveness | 63 |
| College Students | 59 |
| Computer Software | 55 |
| More ▼ | |
Source
Author
Publication Type
Education Level
Audience
| Teachers | 6 |
| Researchers | 1 |
| Students | 1 |
Location
| China | 22 |
| Taiwan | 19 |
| Japan | 11 |
| Turkey | 11 |
| South Korea | 10 |
| Hong Kong | 9 |
| Iran | 8 |
| Germany | 7 |
| Ireland | 6 |
| Saudi Arabia | 6 |
| Spain | 6 |
| More ▼ | |
Laws, Policies, & Programs
Assessments and Surveys
| International English… | 5 |
| Test of English as a Foreign… | 4 |
| Test of English for… | 3 |
| Dynamic Indicators of Basic… | 2 |
| Test of Word Reading… | 1 |
What Works Clearinghouse Rating
| Meets WWC Standards without Reservations | 1 |
| Meets WWC Standards with or without Reservations | 1 |
Rui Li – British Journal of Educational Technology, 2025
Despite the proliferation of help options for computer-based second language (L2) listening comprehension, little attention has been given to a comprehensive understanding of the pedagogical effects. To gain a thorough understanding of the overall and moderator effects, drawing on the activity theory (AT), this study conducted a meta-analysis of…
Descriptors: Computer Assisted Instruction, Second Language Instruction, English (Second Language), Listening Comprehension
Chen, Binbin; Bao, Lina; Zhang, Rui; Zhang, Jingyu; Liu, Feng; Wang, Shuai; Li, Mingjiang – Journal of Educational Computing Research, 2024
Language learning has increasingly benefited from Computer-Assisted Language Learning (CALL) technologies, especially with Artificial Intelligence involved in recent years. CALL in writing learning acknowledged as the core of language learning is being realized by technologies like Automated Writing Evaluation (AWE), and Automated Essay Scoring…
Descriptors: Computer Assisted Instruction, English (Second Language), Second Language Learning, Writing Instruction
Yen-Jung Chen; Liwei Hsu; Shao-wei Lu – Computer Assisted Language Learning, 2024
It is well known that teachers' feedback plays an important role in students' learning, as it enhances learners' cognitive development; yet there has been little research on how positive feedback given in the form of emojis works in computer-assisted language learning (CALL) courses. In this study, an experiment was designed to clarify how English…
Descriptors: Visual Aids, English (Second Language), Second Language Learning, Feedback (Response)
Conijn, Rianne; Cook, Christine; van Zaanen, Menno; Van Waes, Luuk – International Journal of Artificial Intelligence in Education, 2022
Feedback is important to improve writing quality; however, to provide timely and personalized feedback is a time-intensive task. Currently, most literature focuses on providing (human or machine) support on product characteristics, especially after a draft is submitted. However, this does not assist students who struggle "during" the…
Descriptors: Writing Skills, Teacher Response, Writing (Composition), Writing Evaluation
Quantifying the Impact of ASR-Based Instruction: What Does the "iSpraak" Platform Learner Data Show?
Dan Nickolai – The EUROCALL Review, 2024
Computer-assisted Pronunciation Training (CAPT) tools have become increasingly dependent on Automatic Speech Recognition (ASR) technology to provide automated corrective pronunciation feedback to learners. The extent to which ASR-based tools measurably improve second language (L2) pronunciation is of great interest to language educators globally,…
Descriptors: Computer Assisted Instruction, Pronunciation, Technology Uses in Education, Second Language Learning
Alif Silpachai; Reza Neiriz; MacKenzie Novotny; Ricardo Gutierrez-Osuna; John M. Levis; Evgeny Chukharev – Language Learning & Technology, 2024
It is unclear whether corrective feedback (CF) provided by L2 computer-assisted pronunciation training (CAPT) tools must be 100% accurate to promote an acceptable level of improvement in pronunciation. Using a web-based interface, 30 native speakers of Chinese completed a pretest, a computer-based training session to produce nine sound contrasts…
Descriptors: College Students, Foreign Students, English (Second Language), Second Language Instruction
Karim Ibrahim; Robert Kirkpatrick – International Review of Research in Open and Distributed Learning, 2024
The release of ChatGPT has marked the dawn of a new information revolution that will transform how people communicate and make meaning. However, to date, little is known about the implications of ChatGPT for L2 composition instruction. To address this gap, the present study uses a systematic review design to synthesize available research on the…
Descriptors: Artificial Intelligence, Computer Software, Synchronous Communication, English (Second Language)
Qiufang Zheng – Educational Technology Research and Development, 2025
In the context of process-oriented writing instruction, the significance of engaging students in draft revision is widely acknowledged (McGarrell and Verbeem, ELT Journal 61:228-236, 2007). Nevertheless, L2 learners often exhibit limited motivation for writing, leading to inadequate revision efforts. This quasi-experimental study investigates the…
Descriptors: Technology Uses in Education, Computer Assisted Instruction, Writing Instruction, Writing Evaluation
Made Aryawan Adijaya; I. Ketut Armawan; Maria Goreti Rini Kristiantari – International Journal of Language Education, 2023
Learning activities need to facilitate vocational students in learning independently. It certainly has an impact on students' low understanding and skills. This research aims to develop Mobile-Assisted Language Learning (MALL) for Vocational Education. This type of research is development research. The development model used is the ADDIE model.…
Descriptors: Vocational Education, Computer Assisted Instruction, Telecommunications, Handheld Devices
Salbas, Hanife; Ekmekçi, Emrah – Journal on English Language Teaching, 2022
Computer-Assisted Language Learning (CALL) has evolved into an integral part of today's classrooms as a direct result of technological advancements. One of the most remarkable outcomes of CALL is the widespread use of Computer-Mediated Feedback (CMF) in classrooms. Notwithstanding that the previous studies have offered an insight into CMF, it has…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Assisted Instruction
Gao, Jianwu; Ma, Shuang – Language Teaching Research, 2022
This study investigated the intensity and efficacy of automated corrective feedback (CF) in a tutorial CALL (computer-assisted language learning) environment during form-focused drills as compared with those of instructor CF on free writing in the classroom. The English simple past tense, a previously learned target structure, was selected as the…
Descriptors: Feedback (Response), Writing (Composition), Computer Assisted Instruction, Second Language Learning
Muzakki Bashori; Roeland van Hout; Helmer Strik; Catia Cucchiarini – Computer Assisted Language Learning, 2024
Speaking skills generally receive little attention in traditional English as a Foreign Language (EFL) classrooms, and this is especially the case in secondary education in Indonesia. A vocabulary deficit and poor pronunciation skills hinder learners in their efforts to improve speaking proficiency. In the present study, we investigated the effects…
Descriptors: Computer Assisted Instruction, Teaching Methods, Audio Equipment, Video Technology
Jingjing Zhu; Xi Zhang; Jian Li – Computer Assisted Language Learning, 2024
Traditional L2 pronunciation teaching puts too much emphasis on explicit phonological knowledge ('knowing that') rather than on procedural knowledge ('knowing how'). The advancement of mobile-assisted language learning (MALL) offers new opportunities for L2 learners to proceduralize their declarative articulatory knowledge into production skills…
Descriptors: Artificial Intelligence, Technology Uses in Education, Pronunciation Instruction, Second Language Instruction
Danh Thanh Ly – International Society for Technology, Education, and Science, 2024
In an era of rapid technological growth in education, both teachers and students alike must adapt to up-to-date learning and teaching paradigms. Liveworksheets is advantageous in offering students a compilation of interactive sheets that provide instant online feedback. Nevertheless, whether utilizing Liveworksheets in self-study is efficient has…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Worksheets
Wang, Cong; Zhu, Sida; Zhang, Haijing – Journal of Computer Assisted Learning, 2023
Background: Since the outbreak of COVID-19, universities in Hong Kong have implemented online and hybrid teaching modes, making computer-assisted language learning (CALL) a primary way for English learning. Research on English learning motivation and self-regulation has seldom considered learners' emotions (satisfaction and preparedness) and the…
Descriptors: Foreign Countries, Student Motivation, Online Courses, English (Second Language)

Peer reviewed
Direct link
