In this paper the notion of critical practice in English language education (ELE) is explored through examples from the critical work of educators and researchers in Hong Kong. The paper then concludes with a discussion of both the challenges and possibilities of engaging in critical practice in ELE in Hong Kong and possibly in other East Asian contexts, where similar cultures of teaching and learning predominate.

本研究透過文獻探究福祿貝爾（以下簡稱福氏）的遊戲教育理論，將其和香港的遊戲學習課程的政策和實踐做比較、討論，其中，從探究福氏的教育理念和遊戲教育論，參考其他福氏研究專家的詮釋資料，整理出關於福氏遊戲教育的原貌，再將福氏遊戲教育和香港的《幼稚園教育課程指引》，以及國際期刊中有關香港遊戲學習課程的實證研究結果，進行批判性分析和比較，藉此反思當代香港幼兒教育的遊戲中學習的理念，並深入探討福氏遊戲教育對現代香港幼兒教育倡導的遊戲中學習的啟示。本研究獲得以下主要結果：一、香港的遊戲學習課程原以福氏遊戲教育理論為基礎，但福氏遊戲教育中強調的幼兒自動自發遊戲的自主性，受到課程時間限制和各種社會文化因素，在香港幼兒教育課程的實踐上有一定的難度；二、福氏遊戲教育的核心要素——照料遊戲，雖類似香港幼兒教育課程政策提倡的教師多元化角色，但福氏的照料遊戲亦給了教師如何運用言語等去引導幼兒學習一個更明確的方向。本研究結果提供香港或其他提倡遊戲中學習的國家一個更明確的方向，幼兒教育課程政策上應提供更清楚指引達到幼兒自主性和教師的照料遊戲工作，實務上的意涵則是對實踐遊戲中學習的方向更清楚。 Copyright © 2022 中華民國比較教育學會.

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.