University admission consultation is a professional service that assists students with the university application process. Typically, accessing this service entails exploring university websites, directly contacting faculty members and officers via phone calls or emails, and engaging educational intermediaries. University admission consultation is crucial for both students and institutions. However, conventional consultation methods face challenges such as time and spatial constraints, leading to a growing interest in utilizing chatbots for university admission consultation. In this study, we propose a novel approach that leverages generative pretrained transformer (ChatGPT 3.5) models and implements the retrieval-augmented generation technique using the LlamaIndex framework. To evaluate the effectiveness of this approach, we applied it to undergraduate admission data from three universities: a science and technology university in the United States, a comprehensive university in Kenya, and a comprehensive university in Hong Kong. We also gathered feedback from 53 high school students who tested the chatbot. The results demonstrated a significant improvement in average accuracy, from 41.4% with the ChatGPT 3.5 model to 89.5% with the proposed chatbot, with peak accuracy reaching 94.7%. User reviews also indicated a generally positive perception of the admission chatbot. This methodology has the potential to revolutionize university admissions by utilizing chatbots based on large language models with retrieval-augmented generation. Copyright © 2024 International Forum of Educational Technology and Society .

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.

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.