This qualitative study investigates the impact of generative artificial intelligence (GenAI) on the emotional engagement, motivation and well-being of first-year university students in Hong Kong. We conducted semi-structured interviews with 21 students and three instructors to explore their perceptions of how GenAI influences the affective dimensions of language learning. The data were analyzed using manual coding and inductive thematic analysis to identify key themes. The findings revealed that GenAI generally enhances students’ motivation, reduces anxiety and stress, and fosters an emotionally supportive learning environment. However, challenges related to cultural context and technical issues were also identified. The study highlights the pivotal role of instructors in shaping students’ experiences with GenAI and underscores the need for ongoing support and professional development. It also demonstrates the importance of cultural sensitivity, technological infrastructure and balance. The study is valuable for those who aim to harness GenAI while preserving the irreplaceable human elements of teaching. It contributes to the growing body of knowledge on integrating AI in language learning. Copyright © 2025 The Authors. Published by Elsevier Ltd.

This chapter explores the influence of technology on the pedagogical strategies instructors employ to enhance student outcomes at an English-medium instruction (EMI) institution in Hong Kong. As an integral component of course delivery, technology presents both opportunities and challenges in EMI settings. This interpretive qualitative study involves nine students and three instructors, who volunteered to participate in semi-structured interviews. The findings indicate that technology is pivotal in bridging and enhancing learning outcomes. The students strongly preferred instructors who incorporated technology into their teaching, adopted student-centred approaches that facilitated language-learning autonomy, and offered clear guidance on digital tools. The study also identifies the need for professional development focused on using technology purposefully to support instructors’ learning goals. The findings offer valuable insights and recommendations for students, instructors, and institutions aiming to integrate technology into EMI environments effectively. Copyright © 2025 selection and editorial matter, Xuyan Qiu and Rui Yuan; individual chapters, the contributors.

This research investigates the academic emotions of pre-service primary school teachers in Hong Kong and the influence of these emotions on professional resilience. It can inform the development of teacher education programmes that address holistic emotional competencies. Applying the community of inquiry (CoI) framework as a conceptual lens, we focused on the cognitive, social and teaching presence of seven first-year Postgraduate Diploma in Education students. Data were collected through reflective journals and interviews and subjected to thematic analysis. We adopted an interpretivist paradigm and used the CoI framework as a scaffold to identify themes related to cognitive, social and teaching presence. The qualitative analysis indicated that the participants’ practicum experiences were characterised by the complex interplay of the three forms of presence, which contributed to professional growth and resilience. They encountered cognitive challenges that elicited strong emotional responses, found strength in their social connections and received guidance from experienced teachers. This study provides valuable insights for teachers, policymakers and teacher educators who aim to enhance support systems and foster professional resilience among pre-service teachers. Copyright © 2025 Informa UK Limited, trading as Taylor & Francis Group.

The rapid development of generative artificial intelligence (GenAI) tools (e.g. ChatGPT) has elicited mixed reactions among English language instructors and learners. This study explores how first-year students in an English for Academic Purposes (EAP) course at a Hong Kong university perceive GenAI and traditional grammar-checking tools (e.g. Grammarly, MS Word). We employed a qualitative methodology grounded in the interpretivist paradigm, conducting semi-structured interviews with 14 students. The findings revealed the students perceived GenAI tools to be more comprehensive and authoritative, as they provide detailed explanations and contextual insights that enhance language proficiency. However, they also noted concerns about overreliance, data privacy and equitable access to premium features. The study examines the ethical and pedagogical implications of integrating GenAI tools into higher education, highlighting their potential and the necessity of institutional guidance. It contributes to the ongoing discourse on the role of GenAI in academic writing instruction. Copyright © 2024 The Author(s).

Generative Artificial Intelligence (GenAI) tools have been argued to have transformative potential in education; yet existing literature suggests that language teachers generally lack the abilities to leverage these tools effectively and critically. Conducted in an initial language teacher education programme at a Hong Kong university, this mixed-method intervention study aims to explore the effects of explicit training for using GenAI tools for language teaching in rising pre-service language teachers’ professional GenAI competence (P-GenAI-C). 54 M.Ed students took part in an 11-week course intervention aiming to enhance the five aspects in the P-GenAI-C framework. Analysis of pre- and post-intervention questionnaires, which encompassed a mix of open and closed items to gather participants’ knowledge and perceptions of utilising GenAI tools, as well as the follow-up interviews, revealed that the intervention was effective in stretching all aspects of pre-service teachers’ P-GenAI-C. While there was greater evidence of improvement in participants’ pedagogical competence and critical awareness of GenAI tools deployment, there was less evidence of development in other aspects, such as teachers’ capacity to guide their students to use GenAI tools effectively and responsibly. This discrepancy might be attributed to the lack of such content in the course intervention. Implications for incorporating elements of P-GenAI-C into teacher preparation courses and programmes are discussed. Copyright © 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Technostress is a phenomenon in which rapid technological advancement affects teachers’ psychological well-being. It is an emerging concern in English language education, which may be exacerbated by the advent of generative artificial intelligence (GenAI) tools such as ChatGPT. This study explores the factors that influence technostress among English language teachers using GenAI tools and strategies that can alleviate it. Based on the analysis of qualitative data from semi-structured interviews with 16 instructors at higher education institutions in Hong Kong, the study identifies the rapid advancement of AI technology, inadequate training and lack of experience as contributors to technostress. It also names mitigating strategies including targeted professional development, online engagement and gradual integration. These techniques can foster Technological Pedagogical Content Knowledge (TPACK) and reduce the challenges of incorporating GenAI into English teaching. The findings align with existing literature on the impact of technostress and the role of TPACK. The practical implications include the need for comprehensive training, supportive communities and a balanced approach to AI integration. This investigation also expands the theoretical understanding of technostress in English language teaching and the use of GenAI tools, providing empirical support for existing frameworks. It also suggests directions for future research, which could investigate teacher well-being, effective AI integration and the impact of TPACK. Copyright © 2024 Educational Technology & Society.

This article reports on a qualitative study conducted at primary schools in Hong Kong exploring the use of microlearning to support the self-directed continuing professional development (CPD) of English language teachers. Microlearning refers to short, concise, and easily consumable segments of learning about a knowledge point or skill. These activities tend to be multimodal and delivered through digital platforms, making them accessible anytime and anywhere. Currently, little is known about teachers’ perceptions of microlearning. To address this gap, we developed and delivered a mobile course that followed a microlearning approach and covered various aspects of digital technologies and English language teaching. Eight primary school English teachers engaged in the course and shared their perceptions of the experience in semi-structured interviews. The findings suggest that they found microlearning to be more enriching and conducive to developing their digital competence than traditional CPD. It allowed them to address their immediate needs, develop practical skills, and integrate technology into their practices. The study provides important insights into the use of microlearning to support self-directed CPD. Copyright © 2024 The Open University.

Since the public release of ChatGPT in November 2022, generative AI tools—capable of creating human-like content such as audio, code, images, text, simulations, 3D objects, and videos—have gained significant attention. While the impact of these tools on language teaching and learning has been widely speculated, the perspective of language teacher educators concerning their influence on initial language teacher education (ILTE) remains unexplored. This study investigates how teacher educators, who play a crucial role in adapting ILTE to technological advancements, perceive the effects of generative AI tools on ILTE. Data were collected through in-depth interviews with thirteen English language teacher educators from all four Hong Kong government-funded universities offering ILTE. Findings reveal that participants believe generative AI tools will substantially affect the ILTE curriculum, instruction, and assessment. However, most participants believed they lacked the confidence and competence to address the implications of generative AI tools effectively. This study highlights the need for further research and training to support teacher educators in adapting ILTE to the emerging influence of generative AI. Copyright © 2024 The Authors.

Teachers fostering future-ready graduates need to master updated pedagogical and technological knowledge, so teacher professional development (TPD) is essential. Conventional TPD activities such as seminars and workshops are limited as they require specific time blocks and lack flexibility. The current study investigated TPD through microlearning courses in online and blended learning modes as an innovative TPD approach in Hong Kong. We applied a qualitative approach and thirty-two preservice teachers in the English language education program participated. The data were collected using questionnaires, semi-structured interviews, and observations for data collection. The pre-service teachers’ digital competencies were evaluated against an observation protocol based on the SAMR framework and TPACK model. The effects of microlearning and the participants’ digital competence needs were also identified. The results revealed how preservice teachers perceived the integration of technology and the challenges they encountered (e.g., design of learning tasks and time management). Based on the findings, personalized and hands-on training is recommended to fulfill teachers’ diverse learning targets in applying specific technology and deepen their understanding of technology use. Furthermore, as more conceptual frameworks for assisting microlearning in TPD are necessary, this study can help enrich the underpinning theories for the microlearning design of TPD. Copyright © 2024 International Forum of Educational Technology & Society, National Taiwan Normal University, Taiwan.

English-medium instruction (EMI) is taking hold within higher education in non-Anglophone settings, but there is insufficient research into the challenges students encounter when taking EMI courses online. This exploratory quantitative study conducted in Hong Kong examines the language and studying challenges faced by undergraduate students when in-person classes were suspended due to COVID-19. One hundred thirteen first- and second-year students completed a questionnaire, rating their perceived challenges in the areas of writing, speaking, reading, listening, and study skills. The results showed that they faced particular challenges with reading and study skills (especially self-motivation), as well as vocabulary range, which affected more than one skill. Corroborating existing research, students with less secondary school EMI experience reported greater challenges. As providing English for Academic Purposes (EAP) courses is a primary way to support the language skills of students in EMI settings, we offer guidance to EAP practitioners who seek to help their students overcome the challenges identified in this article. As online technology continues to deliver content in tertiary education, EAP courses must be closely aligned with the language and study skills needs of students in digital EMI environments. Copyright © 2023 by the authors.