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.

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.

To prepare teachers for blended teaching, this study proposed ongoing teacher professional development activities that utilize the learning-by-doing approach within a professional learning community with the objective of developing the technological, pedagogical, content knowledge (TPACK) of teachers. The study explored the TPACK of 11 teachers and their perceptions of blended teaching through interviews and questionnaires. Analyses of interview data demonstrated that teachers perceived the technological benefits (e.g., supporting citywide resources) but noted that the teacher professional development training required high levels of self-regulation skills. The questionnaire results indicated significant improvements in TPACK, TCK, and TPCK but not for other dimensions of TPACK. Lastly, the study presented discussions and implications accordingly. Copyright © 2023 Education Research Institute, Seoul National University.

The shift from face-to-face teaching to emergency remote teaching has become the new normal due to the pandemic in 2020. However, little research has been conducted in Hong Kong to investigate pre-service teachers’ perceptions of the immediate adoption and delivery of online face-to-face teaching. In response to this call, the present research conducted a questionnaire survey with 48 pre-service teachers at a Hong Kong university to examine their perceptions of Zoom as a viable alternative to the suspended traditional face-to-face delivery mode of instruction. It also discussed key factors that lead to better online learning outcomes. The results showed that the participants had overall positive perceptions of Zoom-supported synchronous online education. The Zoom feature that most students considered useful was screen sharing on computers. Zoom-supported synchronous online learning benefited students by helping them to attend class meetings remotely, study course materials and content, communicate and collaborate with their instructors and classmates, and develop a sense of community and social presence. Four main factors may influence learners’ perceptions of synchronous online learning: the quality of online communication and collaboration, learning efficiency, learner autonomy and the usability of technology. Copyright © 2023 Laboratory for Knowledge Management & E-Learning, The University of Hong Kong.

This study explores the readiness of pre-service primary school teachers in Hong Kong to develop future-ready learners. Societal advances require the education sector to continuously update curricula to prepare young people for the future. Schools must equip students with the flexibility to use technologies that have not yet been invented and solve unanticipated problems. In this qualitative study, we analysed the perceptions of 15 pre-service primary school English language teachers at a university in Hong Kong. The study focused on the knowledge and learning environment necessary for developing future-ready learners. Via semi-structured interviews, the findings revealed that the participants believed it is essential to integrate technology into classrooms to address future digital literacy needs. They also noted that students must develop critical thinking skills, problem-solving skills, and soft skills to succeed in the future. The findings also suggest that teachers need to be innovative and adaptable in their pedagogical approaches as the existing primary school curriculum is not cultivating learners’ future-readiness. Copyright © 2023 National Institute of Education, Singapore.

The integration of generative artificial intelligence (AI) in English language teaching presents opportunities and challenges for instructors. This study explores the attitudes of higher education English language instructors towards generative AI tools, their intentions to use them and the institutional support and professional development necessary to teach and learn with them. As the field continues to evolve rapidly, it is essential to comprehend the readiness of front-line language instructors. This qualitative interpretive study seeks to identify the digital competencies and pedagogical knowledge required to implement generative AI in education and provide guidance for the design of professional development programmes that address the challenges and concerns associated with adopting AI. Drawing on semi-structured interviews with twelve instructors at a higher education institution in Hong Kong, the findings reveal the significance of familiarity and confidence with using AI-driven teaching tools, the challenges and concerns language instructors face and the need for tailored support and professional development. The study offers ten practical implications to cultivate language instructors’ digital competencies, pedagogical knowledge and positive attitudes towards integrating AI to enhance their students’ learning experiences. Copyright © 2023 The Authors. Published by Elsevier Ltd.

This paper explored teacher professional development (TPD) for online and blended learning (OBL) via microlearning in the higher education English language teaching context in Hong Kong in 2021 and 2022. OBL requires teachers to integrate technology. This study drew on quantitative survey data (N = 67) and interviews (N = 12) that took place after the participants were exposed to microlearning. The findings illuminated that microlearning was perceived as flexible and stress-free and allowed teachers to focus on relevant and immediate tasks using bite-sized learning segments to achieve digital growth. Such activities created favourable conditions to equip them with the skills necessary to teach effectively in the context of the “new normal”. Moreover, the study shed light on how previous TPD activities were often considered too general to improve teachers’ digital competence. It concluded with a call for more research on microlearning and TPD for OBL to help teachers gain pedagogical, theoretical and practical knowledge to enhance their teaching. Copyright © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Since the first study on computer-mediated communication tools in support of language learning was published in 1992, asynchronous and synchronous tools have been widely adopted; however, few reviews have been conducted to explore the research status in this field. As COVID-19 has increased the use of online tools in education, the need to understand how asynchronous and synchronous tools are being used in language education has grown. In this bibliometric analysis, we reviewed asynchronous and synchronous online language learning (ASOLL) by analyzing the trends, topics, and findings of 319 articles on ASOLL. The results indicate that interest in ASOLL has increased over the past three decades with ASOLL for oral proficiency development and collaborative ASOLL being the two main research issues. Interest in three topics – collaborative ASOLL, emotions, and corrective feedback – was especially apparent. The review contributes to the understanding of ASOLL while providing practical implications for using information communication technologies to enhance language learning. Copyright © 2023 Laboratory for Knowledge Management & E-Learning, The University of Hong Kong.

Despite English being a priority in China and extensive policy changes over the past decades, English language teaching and learning at Chinese tertiary institutions remains insufficient. College English (CE) courses focus on holistic and humanistic education by teaching English for general purposes. However, they are often inefficient and unable to serve university students’ needs. Researchers and practitioners alike call for a transition from CE to English for Academic Purposes (EAP). This study explored pre-service teachers’ perceptions of EAP provision in mainland China through a qualitative, interpretive approach. Sixteen pre-service teachers, who completed their bachelor's education in China and master's education in Hong Kong, participated in semi-structured interviews, sharing their experiences and discussing the challenges and opportunities for EAP to serve as a replacement for or supplement to CE. Thematic analysis revealed complexities comprising current education, the traditional, top-down system, learning styles, status, and lack of professional development opportunities. This paper discusses the challenges of implementing EAP in mainland China in an effort to help policymakers, researchers, and practitioners identify the way out. Copyright © 2022 The Author(s). Published by Elsevier Ltd.

BACKGROUND: Research on Artificial Intelligence in Education (AIEd) has become increasingly active during the past 20 years, with great interest, rich literature, and huge diversity. The diversity in research topics and technologies keeps increasing along with the tremendous growth in the application scope of AIEd research. A comprehensive overview of this field is necessary to understand what had been concerned in AIEd research, what is going on in the field of AIEd, and what might be the future of AIEd research. METHODS: This paper combined the structural topic modeling (STM) with the bibliometric analysis to automatically identify prominent research topics from the large-scale AIEd literature in the past two decades. Specifically, by using STM, we uncovered important research topics concerned within the AIEd community. The evolution of these topics was explored by using a nonparametric Mann-Kendall (MK) trend test. In addition, the correlation between these topics was further explored and visualized based on a semi-parametric Gaussian procedure. RESULTS: The annual trend of publications concerning AIEd had grown consistently across the past 20 years, indicating that research on AIEd had received a growing interest from academia Analyses on topical trends, correlations, and clusters reveal distinct developmental trends of these topics and promising research orientations. Specifically, the top six topics having the highest proportions in the dataset were cognition and perception, programming education, prediction, MOOCs, semantic Web and recommender systems, assessment and feedback, and emotion detection. Results of the MK test highlighted five topics receiving an increase in research interest, including prediction, assessment and feedback, flipped classroom and biosignal data, STEM education, and English language learning. In addition, several inter-topic research directions were identified, including 1) flipped classroom and biosignal data, emotion detection, and