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.

In Hong Kong higher education, students' learning outcomes are increasingly treated as evidence to inform course and teaching improvement. Therefore, outcome-based teaching and learning (OBTL) has been encouraged by the University Grants Committee (UGC) since 2007. OBTL has gradually been implemented by Hong Kong higher education institutions (HEIs) to enhance student learning outcomes. Relating OBTL to the social cohesion/regulation matrix, this chapter aims at analyzing how OBTL is being implemented by the HEIs in Hong Kong. Given the high institutional autonomy and academic freedom afforded to individual HEIs, each university has established its own systematic framework for integrating outcome-based approaches into its teaching, learning, and assessment. Unlike other higher education systems in Asia with strong government supervision, the government in Hong Kong acts as an enabler and facilitator, leaving the UGC to invite international experts as an independent audit body to assure the quality of student learning. As a result, this chapter chooses the eight UGC-funded universities to investigate how they engage their faculty members in OBTL, and what the enabling and hindering factors are. Based upon the social cohesion/regulation matrix, the Hong Kong higher education system is featured by the individualist way of promoting OBTL. Nonetheless, while universities are empowered with institutional autonomy to decide upon teaching, and student learning matters, their strong orientation with OBTL means they cannot simply do whatever they like. Adopting a robust quality assurance mechanism in evaluating university performance through University Accountability Agreements, the institutional autonomy that universities enjoy rests heavily upon their performance in teaching and student learning, which is assessed through rigorous international benchmarking via the Quality Assurance Audit conducted by the UGC and research performance through the Research Assessment Exercise.

This paper focused on students’ learning experiences in a flipped data science class integrated with peer instruction and just-in-time teaching. University students in Hong Kong participated in the research during the pandemic. Students’ perceptions of the flipped learning mode were investigated by a 5-point Likert scale questionnaire. According to the results, most students felt they enjoyed learning with the flipped mode since it allowed them to learn flexibly and independently. The course materials (i.e., instructional videos, lecture notes, and in-class exercises) were well-designed, and students perceived the materials were useful and user-friendly. As suggested by the students, more time should be given to the pre-class learning activities. Based on the suggestions, the researchers provide practical implications on improving teaching in the flipped science class. This study demonstrates how to flip a data science class and proves its value on students’ learning, providing implications for using flipped learning during the pandemic period. Copyright © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG.