Search

The current study explores the TikTok identities of Thai university teachers and how those identities impact their professional identity as teachers. Five English as a Foreign Language (EFL) university teachers in Thailand voluntarily participated in semi-structured individual interviews. Findings obtained using an exploratory-descriptive qualitative research design confirmed existing findings that teachers' identities are multifaceted. However, in the context of a digital teacher's identity, teachers displayed unique identities (e.g., expressive, relational, adaptive, and progressive) that also shaped their identity as teacher-educators. Such identities impact their professional teacher's identity, allowing them to project an authentic teacher-self, become caring and approachable teachers to their students and colleagues, forge genuine connections, and implement pedagogical innovations and practices. The findings also acknowledge the profound influence of TikTok on teachers' identities and professional practices. Furthermore, this study highlights the convergence of technology and social media platforms as influential in constructing a teacher's professional identity and promoting pedagogical advances. The findings offer a significant contribution, shedding light on the potential advantages of using TikTok within the teaching and learning process.

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.

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.

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 pre-service 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.

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.