Drawing upon Darvin and Norton’s (2015) model of investment, this article examines how Xing and Jimmy (both pseudonyms) as two male Chinese English as a foreign language learners from rural migrant backgrounds negotiate their identities and assemble their social and cultural resources to invest in autonomous digital literacies for language learning and the assertion of a legitimate place in urban spaces. Employing a connective ethnographic design, this study collected data through interviews, reflexive journals, digital artifacts, and on-campus observations. Data were analyzed using an inductive thematic approach as well as within- and cross-case data analysis methods. The findings indicate that Xing and Jimmy experienced a profound sense of alienation and exclusion as they migrated from under-resourced rural spaces to the urban elite field. The unequal power relations in urban classrooms subjected them to marginalized and inadequate rural identities by denying them the right to speak and be heard. However, engaging with digital literacies in the wild allowed these migrant learners to access a wide range of linguistic, cultural, and symbolic resources, empowering them to reframe their identities as legitimate English speakers. The acquisition of such legitimacy enabled them to challenge the prevailing rural–urban exclusionary ideologies to claim the right to speak. This article closes by offering implications for empowering rural migrant students as socially competent members of the Chinese higher education system in the digital age.

This three-year longitudinal case study explored how trilingual Uyghur intranational migrant students utilized digital technologies to learn languages and negotiate their identities in Han-dominant environments during their internal migrations within China, a topic that has been scarcely researched before. Adopting a poststructuralist perspective of identity, the study traced four Uyghur students who migrated from underdeveloped southern Xinjiang to northern Xinjiang for junior high school education, and to more developed cities in eastern and southern China for senior high school education and higher education. A qualitative approach was adopted, utilizing semi-structured interviews, class and campus observations, daily conversations, WeChat conversations, participants’ reflections, and assignments. Findings reveal that Uyghur minority students utilized digital technologies to bridge the English proficiency gap with Han students, negotiate their marginalized identities, integrate into the mainstream education system, and extend the empowerment to other ethnic minority students. This was in sharp contrast to the significant challenges and identity crises they faced when they did not have access to digital technologies to learn Mandarin in boarding secondary schools. An unprecedented finding is that, with digital empowerment, Uyghur minority students could achieve accomplishments that were even difficult for Han students to attain and gain upward social mobility by finding employment in Han-dominant first-tier cities. The implications of utilizing digital technologies to support intranational migrant ethnic minority students’ language learning and identity development are discussed.

This article addresses a critical gap in international research concerning digital literacies and empowerment among adults who are English as an additional language (EAL) learners. In the Australian context, where digital communication and services are embedded in all aspects of life and work, proficiency in digital literacies, including advanced technologies like generative artificial intelligence (AI), is vital for working and living in Australia. Despite the increasing prevalence and significance of generative AI platforms such as ChatGPT, there is a notable absence of dedicated programs to assist EAL learners in understanding and utilising generative AI, potentially impacting their employability and everyday life. This article presents findings from a larger study conducted within training providers, spanning adult educational institutions nationwide. Through analysis of data gathered from surveys and focus groups, the article investigates the knowledge and attitudes of students, educators, and leaders regarding integrating generative AI into the learning program for adult EAL learners. The results reveal a hesitance among educators, particularly concerning beginning language learners, in incorporating generative AI into educational programs. Conversely, many adult learners demonstrate enthusiasm for learning about its potential benefits despite having limited understanding. These disparities underscore the pressing need for comprehensive professional development for educators and program leaders. The findings also highlight the need to develop the AI literacy of learners to foster their understanding and digital empowerment. The article concludes by advocating for a systemic approach to include generative AI as an important part of learning programs with students often from adult migrant and refugee backgrounds.

The advent of generative artificial intelligence (AI) models holds potential for aiding teachers in the generation of pedagogical materials. However, numerous knowledge gaps concerning the behavior of these models obfuscate the generation of research-informed guidance for their effective usage. Here, we assess trends in prompt specificity, variability, and weaknesses in foreign language teacher lesson plans generated by zero-shot prompting in ChatGPT. Iterating a series of prompts that increased in complexity, we found that output lesson plans were generally high quality, though additional context and specificity to a prompt did not guarantee a concomitant increase in quality. Additionally, we observed extreme cases of variability in outputs generated by the same prompt. In many cases, this variability reflected a conflict between outdated (e.g. reciting scripted dialogues) and more current research-based pedagogical practices (e.g. a focus on communication). These results suggest that the training of generative AI models on classic texts concerning pedagogical practices may bias generated content toward teaching practices that have been long refuted by research. Collectively, our results offer immediate translational implications for practicing and training foreign language teachers on the use of AI tools. More broadly, these findings highlight trends in generative AI output that have implications for the development of pedagogical materials across a diversity of content areas.

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.