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Ali Soyoof; Barry Lee Reynolds; Kan Kan Chan; Wen-Ta Tseng; Kate McLay – Computer Assisted Language Learning, 2025
Research has shown that massively multiplayer online role-playing games (MMORPGs) have the potential to offer language learning opportunities. However, there is a dearth of research exploring student attitudes about the potential of these games for language learning. We used the language learning principles framework proposed by Brown and Lee…
Descriptors: Foreign Countries, Computer Games, English (Second Language), Second Language Learning
Jacqueline Zammit – Computer Assisted Language Learning, 2024
With the advancement of educational technologies, computer-assisted language learning (CALL) tools, like online dictionaries, are essential for acquiring a second language, especially new vocabulary. There has been no empirical focus on the usage of "Gabra" online dictionary in learning Maltese, with a specific focus on international…
Descriptors: Dictionaries, Computer Assisted Instruction, Language Acquisition, Second Language Learning
Nina Bergdahl – Computer Assisted Language Learning, 2025
Current approaches to assessing digital competence in education may be too broad to support teachers in developing their online learning designs in specific subjects. During the pandemic, studies have identified that the development of teaching practices (and subsequently their learning designs) has taken a leap. However, because digital cultures…
Descriptors: Second Language Learning, Electronic Learning, Instructional Design, Second Language Instruction
Michal B. Paradowski; Magdalena Jelinska – Computer Assisted Language Learning, 2024
Learning a foreign language is a long-term process requiring persistence and a willingness to engage in activities that will help develop communicative competence. An important role on the way to achieving linguistic proficiency is played by L2 grit. However, foreign language learners differ in the intensity of this trait. We identify the most…
Descriptors: Second Language Learning, Electronic Learning, Online Courses, Predictor Variables
Matt Kessler; Shawn Loewen; Talip Gönülal – Computer Assisted Language Learning, 2025
Despite the influx of research examining various aspects of mobile-assisted language learning (MALL) applications (apps) over the past two decades, there have been no head-to-head studies that have investigated the comparative effectiveness of different mobile apps. The current study addresses this gap by directly comparing two of the most…
Descriptors: Handheld Devices, Telecommunications, Technology Uses in Education, Second Language Learning
Engwall, Olov; Lopes, José – Computer Assisted Language Learning, 2022
This article analyses how robot-learner interaction in robot-assisted language learning (RALL) is influenced by the interaction behaviour of the robot. Since the robot behaviour is to a large extent determined by the combination of teaching strategy, robot role and robot type, previous studies in RALL are first summarised with respect to which…
Descriptors: Second Language Learning, Adults, Swedish, Robotics
Nishioka, Hiromi – Computer Assisted Language Learning, 2023
Developments in the affordances of the Internet provide language learners with easy access to learning resources as well as interactions with native speakers. This emerging learning landscape thus creates favourable conditions to learners who want to engage in self-directed language learning. This in-depth single case study reports on the…
Descriptors: Korean, Social Media, Video Technology, Educational Technology
Marjan Ebadijalal; Nouroddin Yousofi – Computer Assisted Language Learning, 2024
The current mixed-methods study aimed at incorporating a virtual reality (VR) tool (i.e. Google Expeditions) into the writing process of Iranian English as a foreign language (EFL) learners, examining its impact on their writing motivation and performance. To that end, 42 EFL learners were randomly assigned to experimental and control groups,…
Descriptors: Computer Software, Maps, Geography, English (Second Language)
Ali Khodi; Hossein Khezerlou; Hassan Sahraei – Computer Assisted Language Learning, 2024
Regarding the whispered use of technology in instruction and assessment of language skills, the present study investigates the effect of e-portfolio assessment on EFL learners' speaking proficiency. To this end, 60 intermediate students were randomly selected and homogenized to participate in the study. Samples of the IELTS speaking tests were…
Descriptors: Reliability, Portfolio Assessment, Electronic Publishing, Student Evaluation
Evers, Katerina; Chen, Sufen – Computer Assisted Language Learning, 2022
This study examined the difference in adults' pronunciation performance with peer feedback and individual practice when using an automatic speech recognition (ASR) system. The same ASR software was used in both the comparison (n = 31) and the experimental group (n = 33) for 12 weeks. The participants were working adults in Taiwan. During the…
Descriptors: Automation, Computer Assisted Instruction, Speech Communication, Peer Evaluation
Lenkaitis, Chesla Ann – Computer Assisted Language Learning, 2020
This study qualitatively and quantitatively investigated synchronous (real-time) computer-mediated communication (SCMC), via Zoom (https://zoom.us) videoconferencing, to explore second language (L2) learning and learner autonomy. Twenty-five L2 Spanish participants (n = 25) from the same university utilized SCMC over a 6-week implementation…
Descriptors: Technology Integration, Videoconferencing, Second Language Learning, Personal Autonomy
Aryadoust, Vahid; Ang, Bee Hoon – Computer Assisted Language Learning, 2021
Eye tracking technology has become an increasingly popular methodology in language studies. Using data from 27 journals in language sciences indexed in the Social Science Citation Index and/or Scopus, we conducted an in-depth scientometric analysis of 341 research publications together with their 14,866 references between 1994 and 2018. We…
Descriptors: Eye Movements, Sex Stereotypes, Research Reports, Trend Analysis
Ghorbani, Mohammad Reza; Golparvar, Seyyed Ehsan – Computer Assisted Language Learning, 2020
The purpose of this research is to model the link between language learners' socioeconomic status (SES), their self-directed, technology-enhanced language learning, and their language achievement. The participants of this study are 382 university students taking part in a survey related to their perceptions of their self-directed,…
Descriptors: Socioeconomic Status, Technology Integration, Second Language Learning, English (Second Language)
Bueno-Alastuey, M. Camino; Nemeth, Katalin – Computer Assisted Language Learning, 2022
To date, several studies have investigated the potential benefits of using Quizlet and podcasts for vocabulary development. However, they have mainly focused on the use of available material, and its effects on receptive vocabulary acquisition and students' motivation. In contrast, relatively little has been done to study the effects of…
Descriptors: Vocabulary Development, Audio Equipment, Receptive Language, Expressive Language
Shadiev, Rustam; Huang, Yueh-Min – Computer Assisted Language Learning, 2020
In this study, we applied speech-enabled language translation (SELT) during lectures in a foreign language. The SELT program received input from the instructor's speech and generated translated texts that were shown to students during lectures. We tested the feasibility of our approach specifically with regard to how it facilitates student…
Descriptors: Attention, Cognitive Processes, Difficulty Level, Metacognition