The emergence of the Metaverse, supported by innovative technologies, especially extended reality, has opened up new possibilities for various fields of education. Some disciplines like STEM have already derived significant benefits from the immersive, interactive, and authentic learning opportunities afforded by the Metaverse. In contrast, only very few changes have been seen in language education, such as pedagogical design, technical support, and psychological endorsement in the Metaverse. To predict the future pathways of language education, the present paper aims to shed valuable light on the use of the Metaverse by discussing topics such as definitions, features, examples, and existing models. Based on this discussion, a new educational framework for language education in the Metaverse is proposed, covering five dimensions - Design, Pedagogy, Technology, Actors, and Learning. It is hoped that the framework will be of value to different educational stakeholders and provide constructive learning environments and opportunities for future language teaching and learning.

Despite the increasing ownership of mobile devices among Chinese postgraduate EFL learners, relevant studies regarding mobile English learning resources (MELR) use by postgraduate learners are still lacking. This study tries to understand the uses and the motivation behind language learners´ selection of MALL resources. In this research, 95 Chinese postgraduate students from four university levels took part in a questionnaire, and eight of them in an interview. The results show that “passing exams” was the top reason for using MELR and expanding one’s English vocabulary was the aspect learners aimed to improve. The portability of mobile devices enabled learners to use MELR during short time intervals¹, which suggests that MALL applications should target this behaviour. However, as a type of supplementary material, few students used MELR for more than one hour per day, and they were not regularly and actively involved in using MELR. Few learners were able to select suitable MELR to meet their current English learning needs, and they relied on recommendations from social media and authoritative education experts. Due to the importance of vocabulary, mobile dictionaries and vocabulary learning applications were the learners’ favourite type of MELR. As the participants suggested, enjoyment and interactivity were the two driving factors behind MELR selection and use. On the basis of Framework for the Rational Analysis of Mobile Education (FRAME, Koole, M. (2009). A model for framing mobile learning. In M. Ally (Ed.), Mobile learning: Transforming the delivery of education and training. Athabasca: Athabasca University Press, 25–47) and Technology Acceptance Model (TAM [Davis, F. D., (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Management Information Systems, 13, 319–339]; TAM 2 [Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204]), a new theoretical model for better understanding the complex nature of mobile-assisted language learning (MALL) and the importance of learners in the self-directed, non-formal English language learning setting is proposed in this study.

This study examined the effects of involvement load-based tasks on vocabulary learning in a foreign language, as well as the extent to which task effects are predicted by learners’ metacognition (i.e. metacognitive knowledge and regulation). A total of 120 Chinese university students of English as a foreign language (EFL) were randomly assigned to four task conditions: (1) reading; (2) reading + gap-fill; (3) reading + writing; and (4) reading + writing with the use of a digital dictionary. The Vocabulary Knowledge Scale was adapted to measure condition effects. The Metacognitive Awareness Inventory was used to examine learners’ metacognitive knowledge and regulation. Results revealed that the group of learners who completed reading + writing tasks with the use of a digital dictionary demonstrated the best performance in acquiring receptive and productive vocabulary knowledge, followed by the reading + writing group, the reading + gap-fill group, and, finally, the reading only group. Multiple regression analysis supported the predictive effects of metacognitive regulation on task-based vocabulary learning. Structural equation modelling presented an overall profile of task-based vocabulary learning and metacognition. Based on the findings, we proposed a framework to understand the relationship between learners’ metacognition, task type, and L2 vocabulary learning.

The enormous importance of second language learning, paired with the rapid development of mobile-assisted language learning, has led to the increasing use of mobile dictionaries by English as a Foreign Language (EFL) learners at Chinese universities. Although many studies have explored the role of dictionaries in English language learning, few have investigated mobile dictionaries (MDs) from learners’ perspectives. This study aimed to explore Chinese EFL learners’ acceptance of three types of MDs: monolingual, bilingualised and bilingual. A total of 125 participants used mobile dictionaries in various English learning contexts, especially in reading comprehension and vocabulary learning. Adapted from the Technology Acceptance Model and the mobile technology evaluation framework, the questionnaire in this study addressed three key themes: (1) perceived ease of use, (2) perceived usefulness, and (3) behavioural intention to use. Analysis shows that the bilingualised MD group reported the most positive perceptions, especially compared to the bilingual MD group. A total of 101 participants participated in semi-structured group interviews to further explore the reasons underlying their perceptions. Several factors impacting learner acceptance, from the micro to the macro level, are proposed and discussed. As an interdisciplinary study, this research fills theoretical and empirical gaps in investigating mobile-assisted language learning. It offers application designers and language teachers insights into learners’ acceptance of MDs. Moreover, it provides recommendations concerning making MDs more personalised, attractive and effective.

This article examines the effects of task conditions (i.e., with and without a sentence-writing task), multimedia input (definition only, definition + information, definition + information + videos), and combinations of these two variables on the learning gains of new words. This study involved a 2 × 3 research design. In total, 235 Chinese EFL learners were allocated to the six conditions. Vocabulary learning outcomes were measured by pre- and post-tests on 24 target items. The results showed that the definition + information + videos group scored significantly higher than the definition + information and the definition-only groups. Additionally, the sentence-writing task increased the effectiveness of vocabulary learning versus the condition without this task. The combination of the definition + information + videos condition and sentence-writing task was identified as the most effective technique for learning lexical items. This study highlighted the effectiveness of combining multimedia input with a sentence-writing task to learn new words. Relevant teaching and theoretical implications were also discussed.