Publication Date
In 2025 | 1 |
Since 2024 | 5 |
Since 2021 (last 5 years) | 10 |
Since 2016 (last 10 years) | 11 |
Since 2006 (last 20 years) | 14 |
Descriptor
Source
Computer Assisted Language… | 15 |
Author
Amrate, Moustafa | 1 |
Anastasia Pattemore | 1 |
Carmen Muñoz | 1 |
Catia Cucchiarini | 1 |
Chun, Dorothy | 1 |
Daniela Avello | 1 |
Dunham, Richard Erick | 1 |
Galip Kartal | 1 |
Gerosa, Matteo | 1 |
Giuliani, Diego | 1 |
Helmer Strik | 1 |
More ▼ |
Publication Type
Journal Articles | 15 |
Reports - Research | 14 |
Tests/Questionnaires | 5 |
Opinion Papers | 1 |
Audience
Laws, Policies, & Programs
Assessments and Surveys
Test of English as a Foreign… | 1 |
What Works Clearinghouse Rating
Xue, Xiaojiao; Dunham, Richard Erick – Computer Assisted Language Learning, 2023
As a concept established on MOOC, SPOC has been used by many instructors in universities. Although SPOC-based flipped classroom instructional modes have been applied in many disciplines including English learning in China, no empirical study has tried to disentangle the application of the modes in teaching English pronunciation. This study reports…
Descriptors: MOOCs, Flipped Classroom, Teaching Methods, English (Second Language)
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
Kruk, Mariusz; Pawlak, Miroslaw – Computer Assisted Language Learning, 2023
The paper presents the results of a quasi-experimental study which was conducted with a view to determining the effect of an intervention in the form of the application of teacher-designed Internet-based resources (i.e., websites, podcasts, movie clips) that students could use autonomously on the development of pronunciation of the English regular…
Descriptors: Pronunciation Instruction, Second Language Learning, Second Language Instruction, English (Second Language)
Wen-Min Hsieh; Hui-Chin Yeh; Nian-Shing Chen – Computer Assisted Language Learning, 2025
Research on how the use of social robots helps improve English as Foreign Language (EFL) young learners' pronunciation and willingness to communicate (WTC) is understudied. This study developed a robot and tangible objects (R&T) learning system and examined its impact on elementary EFL learner's English pronunciation and WTC. The R&T…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Task Analysis
Galip Kartal – Computer Assisted Language Learning, 2024
The overarching goal of this design-based research was to explore WhatsApp's potential for facilitating and supporting speaking and pronunciation instruction in an EFL large-class speaking course. More specifically, this paper explored the perceived learning outcomes of WhatsApp-supported pedagogy in large English-speaking classes. Ninety-nine…
Descriptors: Computer Software, English (Second Language), Second Language Instruction, Second Language Learning
Yenkimaleki, Mahmood; van Heuven, Vincent J.; Moradimokhles, Hossein – Computer Assisted Language Learning, 2023
In the present study, three groups of interpreter trainees were formed, two experimental groups, i.e., blended prosody instruction (BPI) and computer-assisted prosody training (CAPT), and one control group (CON). In this experiment the participants took part in a four-week teaching program for 16 sessions (60 minutes per session), i.e., 16 hours…
Descriptors: Intonation, Suprasegmentals, Computer Software, Pronunciation Instruction
Amrate, Moustafa – Computer Assisted Language Learning, 2022
This study explores collaborative and individual computer-assisted prosody training (CAPT) through a quasi-experimental design. Eighteen adult Algerian EFL learners were recruited and randomly assigned into a control group receiving no treatment and two experimental groups, a collaborative CAPT group where the participants practiced in pairs, and…
Descriptors: Foreign Countries, Intonation, Suprasegmentals, Pronunciation Instruction
Carmen Muñoz; Anastasia Pattemore; Daniela Avello – Computer Assisted Language Learning, 2024
Repeated viewing of the same video is a common strategy among autonomous language learners as well as a much used pedagogical strategy among foreign language (FL) teachers. Learners may watch the same video more than once, to increase global comprehension of the target language or to focus their attention on linguistic aspects, such as new…
Descriptors: Captions, Vocabulary Development, Second Language Learning, Second Language Instruction
Jiang, Yan; Chun, Dorothy – Computer Assisted Language Learning, 2023
This paper examines whether a web-based training on English discourse intonation leads to better spontaneous speech quality for Mandarin Chinese speakers who reside in the U.S. and in China. The four-week fully online training consisted of meta-instruction videos as well as listening and speaking activities, including instant visual pitch contour…
Descriptors: Oral Language, Second Language Learning, Second Language Instruction, English (Second Language)
Hsu, Liwei – Computer Assisted Language Learning, 2016
This study aims to explore the structural relationships among the variables of EFL (English as a foreign language) learners' perceptual learning styles and Technology Acceptance Model (TAM). Three hundred and forty-one (n = 341) EFL learners were invited to join a self-regulated English pronunciation training program through automatic speech…
Descriptors: Pronunciation, Pronunciation Instruction, Cognitive Style, Statistical Analysis
Quintana-Lara, Marcela – Computer Assisted Language Learning, 2014
This study investigates the effects of Acoustic Spectrographic Instruction on the production of the English phonological contrast /i/ and / I /. Acoustic Spectrographic Instruction is based on the assumption that physical representations of speech sounds and spectrography allow learners to objectively see and modify those non-accurate features in…
Descriptors: Acoustics, Experimental Groups, Pronunciation Instruction, Teaching Methods
Wu, Chung-Hsien; Su, Hung-Yu; Liu, Chao-Hong – Computer Assisted Language Learning, 2013
This study presents an efficient approach to personalized mispronunciation detection of Taiwanese-accented English. The main goal of this study was to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed approach quickly identifies personalized…
Descriptors: Pronunciation, Pronunciation Instruction, English (Second Language), Second Language Instruction
Neri, Ambra; Mich, Ornella; Gerosa, Matteo; Giuliani, Diego – Computer Assisted Language Learning, 2008
This study investigates whether a computer assisted pronunciation training (CAPT) system can help young learners improve word-level pronunciation skills in English as a foreign language at a level comparable to that achieved through traditional teacher-led training. The pronunciation improvement of a group of learners of 11 years of age receiving…
Descriptors: Second Language Instruction, Second Language Learning, Pronunciation Instruction, Computer Assisted Instruction

Lambacher, Stephen – Computer Assisted Language Learning, 1999
Explains the use of a computer-assisted language-learning tool that utilizes acoustic data in real time to help Japanese second-language learners improve their perception and production of English consonants. The basic features of the speech-learning software that runs on a networked workstation and is used for pronunciation training are…
Descriptors: Acoustic Phonetics, Articulation (Speech), Computer Assisted Instruction, Computer Software