Informal digital learning of English (IDLE) is a promising way of learning English that has received growing attention in recent years. It has positive effects on English as a foreign language (EFL) learners and also creates valuable opportunities for EFL teachers to improve their teaching skills. However, there has been a lack of a valid and reliable scale to measure IDLE among teachers in EFL contexts. To address this lacuna, this study aims to develop and validate a scale to measure IDLE for EFL teachers in Iran. For this purpose, a nine-step rigorous validation procedure was undertaken: administering pilot interviews; creating the first item pool; running expert judgment; running interviews and think-aloud protocol; running the pilot study; performing exploratory factor analysis, Cronbach’s alpha, and confirmatory factor analysis; creating the second item pool; conducting expert reviews; and performing translation and translation quality check. Findings yielded a 41-item scale with six subscales: IDLE-enhanced benefits (12 items), IDLE practice (five items), support from others (nine items), authentic L2 experience (three items), resources and cognition (four items), and frequency and device (eight items). The scale demonstrated satisfactory psychometric properties such that it can be used for research and educational purposes in future.

This study explores the integration of generative artificial intelligence (GenAI) in informal digital learning of English (IDLE) practices, focusing on its potential to enhance language learning outcomes and addressing the technological challenges language teachers face in utilising AI-based tools to facilitate second language acquisition. Based on the research context of IDLE and holistic learning ecology and drawing on the theoretical frameworks of technological pedagogical and content knowledge and social cognitive theory, we performed a mixed-methods investigation with an empirical experiment to assess the effectiveness of GenAI followed by semi-structured interviews. The results suggest that the GenAI-mediated IDLE practices effectively improve college students’ oral proficiency in English from both technological and humanistic perspectives. However, results also indicate that the GenAI conversational partner alone is not adequate to provoke continuous extramural GenAI-mediated IDLE practices. We discuss the theoretical and pragmatic significance of GenAI-mediated IDLE in educational equity and reformation.

This study explored how collaborative writing, an often-used instructional strategy in second language (L2) learning, intersects with large-group dynamics, and investigated their potential impact on the quality of writing outcomes in an online distance learning course. Using a mixed-methods approach, the research scrutinized intra-group interaction processes in two large groups undertaking a computer-assisted language learning writing assignment and evaluated the impact of these interaction processes on their writing products. Data from discussions in both a public online forum and a private social communication platform (WeChat) were collected, systematically coded, and analysed quantitatively and qualitatively based on language functions. Data collection also included an assessment of the written products and follow-up group interviews. The findings indicate distinct interaction patterns between high-performing and low-performing groups, characterised by an expert/participant pattern and a dominant/passive pattern, respectively. Additionally, insights from the interviews shed light on these interaction patterns and the potential impact on student learning outcomes. The study suggests practical implications, highlighting the importance of task design in promoting high levels of collaborative knowledge construction to enhance students’ writing skills and L2 language learning in large-group settings.

This study creates a virtual space for language learning using a user-customizable metaverse platform and explores its potential for EFL learning. To this end, a virtual learning space, grounded in constructivist learning principles – contextualized learning, active learning, and collaborative learning – was created on a 2D metaverse platform. The metaverse was designed as a simulated deserted island for enjoyable and playful learning, allowing the students to actively explore, discover, and interact as they look for clues to escape the island. For educational application, 29 Korean middle school students participated in a two-hour activity. Data included screen recordings of student activities, student surveys, and interviews with the students and teachers. The findings showed that, as an EFL learning space of playful constructivism, the metaverse had great potential to embed contextualized learning and served as a medium for active learning that positively affected student interest and motivation. The results confirmed that the team-based approach combined with a game-like metaverse fostered student collaboration. Overall, the study showcased how language instructors can make use of a customizable metaverse for L2 learning and how a virtual space may serve as an arena for learner-centered instruction.

The aim of this study was to contribute to the field of computer-assisted language learning (CALL) by investigating the individualization of intentional vocabulary learning. A total of 118 Japanese-speaking university students studied 20 low-frequency English words using flashcard software over two learning sessions. The participants practiced retrieval of vocabulary under different learning schedules, with short or long time intervals between encounters of the same word in each learning session: Short–Short, Short–Long, Long–Short, and Long–Long. Two individual difference measures – learning efficiency and language aptitude – were examined as predictors of long-term second language (L2) vocabulary retention. Learning efficiency was operationalized as the number of trials needed to reach a learning criterion in each session, whereas a component of aptitude (rote memory ability) was measured by a subtest of Language Aptitude Battery for the Japanese. Multiple regression and dominance analyses were conducted to evaluate the relative importance of learning efficiency and language aptitude in predicting delayed vocabulary posttest scores. The results revealed that learning efficiency in the second learning session was the strongest predictor of vocabulary retention. Language aptitude, however, did not significantly predict vocabulary retention. Moreover, the predictive power of learning efficiency increased when the data were analyzed within each learning schedule, underscoring the need to assess learners’ abilities under specific learning conditions for optimizing their computer-assisted learning performance. These findings not only inform the development of more effective, individualized CALL systems for L2 acquisition but also emphasize the importance of gauging individuals’ abilities such as learning efficiency in a more flexible, context-sensitive manner.

This systematic review maps the trends of computer-assisted pronunciation training (CAPT) research based on the pedagogy of second language (L2) pronunciation instruction and assessment. The review was limited to empirical studies investigating the effects of CAPT on healthy L2 learners’ pronunciation. Thirty peer-reviewed journal articles published between 1999 and 2022 were selected based on specific inclusion and exclusion criteria. Data were collected about the studies’ contexts, participants, experimental designs, CAPT systems, pronunciation training scopes and approaches, pronunciation assessment practices, and learning measures. Using a pedagogically informed codebook, the pronunciation training and assessment practices were classified and evaluated based on established L2 pronunciation teaching guidelines. The findings indicated that most of the studies focused on the pronunciation training of adult English learners with an emphasis on the production of segmental features (i.e. vowels and consonants) rather than suprasegmental features (i.e. stress, intonation, and rhythm). Despite the innovation promised by CAPT technology, pronunciation practice in the studies reviewed was characterized by the predominant use of drilling through listen-and-repeat and read-aloud activities. As for assessment, most CAPT studies relied on human listeners to measure the accurate production of discrete pronunciation features (i.e. segmental and suprasegmental accuracy). Meanwhile, few studies employed global pronunciation learning measures such as intelligibility and comprehensibility. Recommendations for future research are provided based on the discussion of these results.

The research field of online informal English learning has revealed associations of various informal digital English activities and second language vocabulary development. However, most of these studies have regarded digital resources as uniform entities when investigating their potential for vocabulary development and have failed to consider learners’ idiosyncratic interaction with the resources driven by self-defined purposes of use. Informed by the uses and gratifications theory, this study explored how three purposes of extramural digital experience (entertainment, socialization and information) relate to vocabulary knowledge, based on the survey responses from 322 undergraduate Chinese EFL learners and their receptive vocabulary knowledge. PLS-SEM analysis uncovered differential associations of the three media use purposes with receptive vocabulary knowledge. The study also revealed that the associations between the purposes of informal digital activities and vocabulary knowledge differed depending on whether the vocabulary was high frequency or low frequency. Additionally, it was found that the strategic use of digital resources, in terms of cognitive attention to and processing of lexical information that are facilitative of vocabulary learning during and/or after the interaction, played a significant moderating role in the relationship between digital activities for information purposes and receptive knowledge of high-frequency vocabulary. The findings highlight the importance of considering media use purposes in future research and pedagogical practices.

In this qualitative systematic meta-synthesis study, 57 studies from the international literature published between 2010 and 2024 on the use of voice-based artificially intelligent chatbots in English language learning were analyzed. The present study aimed to explore the most recent studies on this topic by investigating the theoretical frameworks, methodological and technological properties, user reports of chatbot usage experience, and pedagogical implementations. It sought to identify research and implementation trends for voice-based chatbots via qualitative data analysis methods. Based on the reviewed studies, this paper presents data-based pedagogical implications that align with the latest voice-based AI chatbot research trends.