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Sri Yuliani; Khulaifiyah; Andi Idayani – Pegem Journal of Education and Instruction, 2024
The Objective of the study was to ascertain how Rosetta Stone in English class affected students' ability to pronounce English. This methodology employed a quasi-experimental pretest-posttest design with 30 samples split into two groups. The technique used was non-probability sampling. Pronunciation test technique was employed for data collecting.…
Descriptors: Computer Software, Computer Assisted Instruction, Teaching Methods, Pronunciation Instruction
Asma Almusharraf; Hassan Saleh Mahdi; Haifa Al-Nofaie; Amal Aljasser – Journal of Computer Assisted Learning, 2024
Background study: Computer-assisted pronunciation training (CAPT) has emerged as an important resource for second language (L2) pronunciation learning. CAPT offers diverse opportunities for learners to master L2 pronunciation with the help of authentic learning activities in multiple contexts. Objectives: This study presents a comprehensive…
Descriptors: Computer Assisted Instruction, Pronunciation Instruction, Second Language Learning, Second Language Instruction
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
María de los Ángeles Gómez González; Alfonso Lago Ferreiro – Language Learning & Technology, 2024
Previous research has established that phonetics has been marginalized within language teaching, proving to be particularly challenging for learners in EFL contexts. This paper presents EPSSML (https://www.usc.gal/multimlab/), an e-learning platform designed within Mayer's (2008, 2009) Cognitive Theory of Multimedia Learning to instruct English…
Descriptors: Computer Assisted Instruction, Pronunciation, Electronic Learning, Phonetics
Rastislav Metruk – Education and Information Technologies, 2024
In recent years, learners worldwide have expressed increasing interest in mobile learning and the utilization of mobile devices for language learning purposes. However, few research synthesis studies have focused on pronunciation development in relation to employing MALL (mobile-assisted language learning). This review article contributes to the…
Descriptors: Pronunciation Instruction, Teaching Methods, Telecommunications, Handheld Devices
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
Agata Guskaroska – ProQuest LLC, 2024
Improving pronunciation in second language (L2) learning requires timely and personalized feedback but educators have limited time to dedicate in the classroom. While there are many educational tools available, educators are still struggling to integrate technology in their practices. To address this challenge, this study explores repurposing a…
Descriptors: Pronunciation, Adoption (Ideas), Second Language Learning, Technology Uses in Education
Mengtian Chen – Computer Assisted Language Learning, 2024
This article discusses whether digital visual and audio feedback in learners' own voices improves their perception and production of lexical tones in Chinese as a foreign language. Forty-four beginners participated in a four-week training focused on the pronunciation of Mandarin Chinese tones at the word level. Half received digital feedback…
Descriptors: Feedback (Response), Computer Assisted Instruction, Pronunciation Instruction, Mandarin Chinese
Marina Ivanova – The EUROCALL Review, 2024
Word stress is frequently afforded secondary importance in English teaching as stress placement rules are complex and because stress can be learnt along with each new word. However, training learners to pay more attention to word stress cues can support them in predicting the stress patterns of new vocabulary. Also, for speakers of fixed stress…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Pronunciation Instruction
Elsayed Issa; Gus Hahn-Powell – Language Learning & Technology, 2025
This study investigates the effectiveness of a computer-assisted pronunciation training (CAPT) system on second language learners' acquisition of three grammatical features. It presents a CAPT system on top of a phoneme-based, fine-tuned speech recognition model, and is intended to deliver explicit, corrective feedback on the pronunciation of the…
Descriptors: Grammar, Computer Assisted Instruction, Arabic, Second Language Instruction
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
Okim Kang; Maria Kostromitina; Xun Yan; Ron I. Thomson; Talia Isaacs – Language Assessment Quarterly, 2025
There has been much debate in assessment research about the inclusion of Global English accents in high-stakes listening tests. This study explored test-takers' attitudes toward the inclusion of different English accents in the Duolingo English Test (DET) 2021 test version and their associations with listening test scores. One hundred sixty…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Software
Marwa F. Hafour – Computer Assisted Language Learning, 2024
Owing to the plethora of user-friendly audio/video creation and editing applications as well as free full-featured hosting platforms, videoing and sharing has become a lifestyle of today's students. Utilizing these spontaneous practices, the current study examined the effects of digital media assignments (DMAs) and accompanying asynchronous…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Video Technology
Linh Phung, Editor; Hayo Reinders, Editor; Vu Phi Ho Pham, Editor – New Language Learning and Teaching Environments, 2024
This book investigates the ways in which new developments in areas of language teaching practice, such as policy-making, planning, methodology and the use of educational technology are locally adopted, adapted, initiated, and implemented in Vietnam and Cambodia. The region is responding to a large number of significant challenges, including…
Descriptors: Second Language Learning, Second Language Instruction, Foreign Countries, Teaching Methods