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.

The issue of Artificial Intelligence (AI) literacy is gaining popularity in the field of education. Most research on AI literacy has focused on primary, secondary, and higher education, and there has been limited examination of AI literacy programs in early childhood education. This study aimed to evaluate the impact of an eight-week AI literacy program on young children’s AI literacy, AI-related creativity, and their perceptions of the AI4KG program. A total of 26 young children (average age of 4 years) enrolled in the program at a kindergarten in Hong Kong were the subjects of the study. The results indicated that (1) young children were capable of learning basic AI concepts and knowledge; (2) in terms of AI-related creativity, younger children were able to design a chatting robot via imagination, while older children created an AI robot to assist people in their drawings; (3) in regards to the children's perceptions of the AI4KG program, older children who enjoyed the activity were able to train AI, while younger children preferred to draw the future AI city and participate in the AI story activity. This study highlights the positive benefits of AI literacy education in preparing young children for an AI-driven future. Copyright © 2023 Informa UK Limited, trading as Taylor & Francis Group.

University closures due to the pandemic have taken learning and teaching from the confines of the physical campus to virtual spaces enabled by digital technologies. In order to ensure the quality of higher education learning and teaching, teaching staff need to be supported with quality professional development (PD) for building their capacity to plan for and implement online learning. It is crucial for universities to design and implement customised PD to address the professional learning needs of the teaching staff. This chapter examines how a faculty-based learning innovation team at a university in Hong Kong has adopted an experiential learning approach to design customised PD programmes for teaching staff to build their capacity to enhance the quality of online learning and teaching. Copyright © 2023 selection and editorial matter, Kevin Wai Ho Yung and Huixuan Xu; individual chapters, the contributors.

In the past few years, the education sector, including teacher education, has encountered unprecedented challenges resulting from the global pandemic of the Coronavirus (COVID-19). In Hong Kong, it was fuelled by protests and campus occupation due to the unstable political situation. Many universities were forced to suspend face-to-face instruction and adopt online teaching. This volume is a response to the global transformation of teaching and learning from the face-to-face mode to the online mode triggered by these challenges, with a focus on teacher education in Hong Kong. This introductory chapter pulls together the narrative of the volume by detailing such challenges and showcasing how the challenges have accelerated the use of e-technology in teaching and learning online. It provides an overview of the chapters included in this volume and discusses how they contribute to the rationale of the volume and the various sections, which include challenges in teaching and learning in times of crisis, curriculum and pedagogical innovations, assessment and feedback practices, and the scholarship of teaching and learning in the teacher education context. Copyright © 2023 selection and editorial matter, Kevin Wai Ho Yung and Huixuan Xu; individual chapters, the contributors.

Based on a case study of an undergraduate course for a teacher education program at a university in Hong Kong, this chapter examines how technology-enabled case-based learning engages pre-service teachers behaviorally, cognitively, and emotionally and prepares them for teaching in schools. Qualitative data obtained from individual interviews with four pre-service teachers and online discussion threads were analyzed using a content analysis approach. This chapter describes how the use of 360-degree panoramic videos and asynchronous discussion forums supports the development of pre-service teachers’ problem-solving skills in tackling school students’ undesirable classroom behaviors, enhancing their reflective skills, and consolidating their content knowledge in classroom management. This study sheds light on how technology-enabled case-based learning may contribute to teacher education programs and prepare pre-service teachers for effective classroom management. Copyright © 2022 Springer Nature Singapore Pte Ltd.

The innovative use of technologies in language learning and teaching significantly impacts language education. This paper aims to investigate technology-enhanced language learning (TeLL) and teaching (TeLT) in higher education through surveying 223 students and 93 teachers across four Hong Kong universities, and interviewing around 50 students and 20 teachers. The current study investigated the e-resources/tools frequently adopted in language learning and teaching, how participants perceived the affordances of TeLL and TeLT, and challenges they had faced in technology-enhanced language learning and teaching. The results reveal that students and teachers perceived several affordances of TeLL and TeLT, such as provision of authentic materials, enhancement of interactivity, and enhancement of learner autonomy. A list of commonly adopted e-resources/tools for language learning and teaching were identified. The students and teachers also indicated what support they would hope to receive from a Community of Practice (CoP) on technology-enhanced language learning and teaching. Copyright © 2022 IGI Global.