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.

Background: Since the outbreak of COVID-19, universities in Hong Kong have implemented online and hybrid teaching modes, making computer-assisted language learning (CALL) a primary way for English learning. Research on English learning motivation and self-regulation has seldom considered learners' emotions (satisfaction and preparedness) and the synchronic online courses in a CALL context. Objectives: This study analyses the relationship between Hong Kong university students' motivation and self-regulation by considering their emotions in computer-assisted synchronic online English courses. Methods: 311 Hong Kong university students were invited to complete two questionnaires that investigated students' motivation and self-regulation in computer-assisted online English courses. SPSS 26 was employed for exploratory factor analysis (EFA) to extract factors and exclude unsuitable items, and confirmatory factor analysis (CFA) was performed to verify the results of EFA. One-way ANOVA was conducted to detect the impact of personal emotion on motivation and self-regulation. AMOS 26 was adopted to construct a structural equation model (SEM) to explore the relationship between motivation and self-regulation in the CALL context. Results and Conclusions: The results show that satisfaction and preparedness positively correlate with online English learning motivation and self-regulation. Instrumentality-attitude significantly predicts all factors of self-regulation via SEM and goal setting significantly predicts all factors of motivation. With feasible English learning goals, Hong Kong university students are more proactive in learning English online where they actively interact with teachers and peers. Implications: Based on the L2 self-system (Dörnyei, The psychology of the language learner: Individual differences in second language acquisition, 2005) and self-determination theory (Barnard et al., Internet and Higher Education, 2009, 12, 1–6), this study clarifies the relationship

The sudden outbreak of COVID-19, which has presented great challenges to pedagogy, has catalyzed the transition of teaching and learning to the online mode. Uncovering the key factors that facilitate positive learning outcomes in online learning environments has thus gathered importance. To bring these factors to light, this study aims to understand and model the effect of perceived online connectedness on the relationship between student motivation and university learning outcomes. Based on 470 questionnaire responses collected by students from nine universities in Hong Kong and Macao, findings from structural equation modelling, showed students’ online connectedness partially mediated the relationship between online learning motivation and university learning outcomes. These results suggest that the learner’s motivation derives not only from the perceived relevance of the learning subject, but also from the learner’s attributes such as confidence, satisfaction, and attention during online learning. Moreover, students’ perceived connectedness, which considers the comfort, community, facilitation, interaction, and collaboration of students in an online context, plays a key role in students’ positive learning outcomes. Pedagogical implications for teachers, educators and students and university policy implications are discussed. Copyright © 2023 The Author(s), under exclusive licence to Springer Nature B.V.

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.

The COVID-19 pandemic has posed challenges to education systems around the world, resulting in a ‘new normal’ for school music education in which teaching and learning can no longer rely only on conventional classroom practices. Concerns have also been raised over music teachers’ digital competencies, given the perceived importance of the use of technology within the new educational landscape. This article presents the results of a study that examined the challenges and experiences associated with the digital competencies of music teachers during the pandemic period. Semi-structured interviews were conducted with full-time music teachers (N = 18), all of whom taught music as a subject at mainstream primary or secondary schools in Hong Kong. The findings revealed challenges and upskilling of music teachers during the lockdown period, including the technological constraints imposed by the school and the online environment, how they made use of technology to teach music online, and the different ways they developed their digital competencies. Alongside with the catalyst effect of the pandemic that stimulated their upskilling, curriculum changes in teacher training programmes are necessary to better prepare music teachers for the digital transformation of music education and future challenges under the post-pandemic ‘new normal’ situation. Copyright © 2023 The Author(s).

Successful implementation of formative assessment in classrooms relies on teachers’ formative assessment literacy, which is typically supported by professional development programs. This study reports on the impact of a professional development program on a group of in-service primary teachers in Hong Kong. The authors investigated the effectiveness of the program in developing teachers’ formative assessment literacy and how far the program assisted them in addressing the challenges they faced when implementing formative assessment in classrooms. With a mixed-method design, quantitative data were collected with a pre- and post-program survey (N = 27); qualitative data were collected with open-ended survey questions and a focus group with six participating teachers. The results provide evidence of the program’s success in developing teachers’ formative assessment literacy and equipping them with the necessary skills to address the challenges in implementation. The features of professional learning communities embedded in the program contributed to the positive impact of the program. Copyright © 2023 Teacher Development.

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.

This study investigates how the online behaviors of students can be associated with student outcomes via a learning analytics approach. The objective of this study is to examine whether online behaviors of students can predict student success in an English course. Also, this study aims to examine whether some machine learning techniques performed better than others. Learners in this study were students in an English for Academic Purposes course at a university in Hong Kong. Other than face-to-face teaching, this course included a mandatory multimodal language learning package first introduced in 2012. The research team retrieved a mega-dataset from all learners who took the course from 2012 to 2019 (n = 17,968). Using the Classification Tree technique, Logistical Regression, and Artificial Neural Networks, the research team derived three predictive algorithms to associate various online engagement variables (e.g., start day, first attempt scores, and number of attempts) with course success. Results suggest that Classification Tree performed better in predictive accuracy and F1 ratio. The chapter provides useful insights for adaptive design. The study also discusses several useful suggestions on how practitioners can adopt these algorithms for better adaptive design. Copyright © 2024 selection and editorial matter, Patsy D. Moskal, Charles D. Dziuban, and Anthony G. Picciano; individual chapters, the contributors.

Little attention has been given to computer-assisted language teaching (CALL) lecturers in community colleges in Hong Kong. In this chapter, we present a novel study of CALL lecturers’ emotions and well-being while coping with emergency remote teaching (ERT) at a community college in Hong Kong during the COVID-19 pandemic. In addition, this study sheds light on emergency CALL teaching design and technical preparation, as well as synchronous and asynchronous online teaching and assessment in this context. We employed interviews to give vivid accounts of four CALL lecturers’ inner voices. The resulting data were coded and grouped into themes, and we report the findings as narrative accounts from the representative lecturers and in-depth thematic descriptions. We found that, overall, the CALL lecturers were stressed and overworked, and their physical conditions, especially eyesight, were impaired due to long-term online activities. They were also concerned about the quality of delivery, student feedback, student learning outcomes, and privacy issues. The analysis further revealed practical strategies that the lecturers adopted to address the difficulties they faced during the pandemic. Based on these strategies and the interviews, we present a conceptual emergency adjustment (EA) model to help understand the experiences, emotions, and well-being of CALL lecturers in community colleges in Hong Kong under the impact of the COVID-19 pandemic. This research offers a significant contribution to the EA literature and the contextual adaptation of CALL lecturers in Hong Kong and elsewhere. In addition, the use of narrative accounts to present data could contribute to methodological developments in studying teaching and learning in an ERT environment. Copyright © 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The use of educational apps in teaching the humanities in higher education is increasingly widespread and commonplace. Understanding the efficacy of using such apps, however, presents a challenge due to the proliferation of countless different apps, each with unique and overlapping functions, often used in courses with very different content and objectives. The PICRAT model provides a framework to compare the educational efficacy of integrating various education apps, even when used in a variety of different courses. This paper presents the results of a project conducted at the Faculty of Humanities at a Hong Kong university. The objective was to develop examples of effective technology-enhanced teaching in the humanities that could be shared as models with other instructors teaching in the humanities. The PICRAT framework focuses on the students’ and teachers’ roles in using technology. All the project courses aimed to change the students’ role from one of more passive to more active and ultimately more creative engagement; and to advance the teachers’ use of technology from merely replacing traditional pedagogy to providing a more amplified and, whenever possible, transformative approach to its use. Examples from three of the twelve project case studies will be described; teacher and student perspectives of the efficacy of using the apps will be analyzed; and the PICRAT model will be used to analyze the overall conclusions that can be drawn from the range of diverse exemplars developed in the project. Copyright © 2023 ICLT.