This paper evaluates the potential of generative artificial intelligence (AI) in higher education, specifically its capacity to replace or assist human teachers. By reviewing relevant literature and analysing survey data from students and teachers, this mixed-methods study provides a comprehensive perspective on the future role of educators in the face of advancing generative AI technologies. An online survey was conducted to explore the perceptions of 399 university students and 184 teachers across different disciplines in eight higher education institutions in Hong Kong concerning the use of generative AI technologies. Findings suggest that although some believed generative AI may eventually replace teachers, the majority of participants argued that human teachers possess unique qualities, including critical thinking and emotions, which make them irreplaceable. Similarly, findings also emphasized the importance of social-emotional competencies developed through human interactions, something which generative AI technologies cannot currently replicate. Crucially, this study further found that students value and respect their human teachers, even as generative AI becomes more prevalent. As such, the authors propose that teachers can seek to effectively integrate generative AI to enhance teaching and learning without viewing it as their replacement. To do so, they must understand how generative AI can work well with teachers and students, avoid potential pitfalls, develop AI literacy, and address practical issues including ethics and privacy. Recommendations are offered on how universities, teachers, and students can adopt generative AI technologies in an approach that balances the strengths of human educators with generative AI technologies. As the future of education lies in the synergy between human teachers and generative AI, teachers, students, and universities should all understand and refine their unique qualities in order to effectively navigate the integration

Existing studies have measured the effect of video-based feedback on student performance or satisfaction. Other issues are underacknowledged or merit further investigation. These include sociocultural aspects which may shape the design and implementation of video-based feedback, the ways students use technology to engage in feedback, and the processes through technology may transform learning. This study investigates the design and implementation of a video-annotated peer feedback activity to develop students' presentation skills and knowledge of climate science. It explores how their use of a video annotation tool re-mediated established feedback practices and how the systematic analysis of contradictions in emerging practices informed the subsequent redesign and reimplementation of the approach. Employing a formative intervention design, the researchers intervened in the activity system of a first-year undergraduate education module to facilitate two cycles of expansive learning with an instructor and two groups of Hong Kong Chinese students (n = 97, n = 94) across two semesters. Instructor interviews, student surveys, and video annotation and system data were analysed using Activity Theory-derived criteria to highlight contradictions in each system and suggest how these could be overcome. The findings highlight the critical importance of active instructor facilitation; building student motivation by embedding social-affective support and positioning peer feedback as an integrated, formative process; and supporting students' use of appropriate cognitive scaffolding to encourage their interactive, efficient use of the annotation tool. Conclusions: In a field dominated by experimental and quasi-experimental studies, this study reveals how an Activity Theory-derived research design and framework can be used to systemically analyse cycles of design and implementation of video-annotated peer feedback. It also suggests how the new activity system might be consolidated and

While the importance of linguistically responsive teaching (LRT) in multilingual classrooms is well documented, preservice English teachers' conceptions of LRT and the pertinent sociocultural processes that shape their LRT conceptions and practices remain under-researched. Qualitatively examining the experiences and understandings of 15 preservice English teachers in Hong Kong shared in interviews and written reflections, this study reveals a positive attitude towards LRT in general, but a dissonance between LRT consciousness and LRT knowledge/skills. The study also identifies three distinct profiles of LRT teachers (Explorers, Activists, and Initiators) as well as a range of enabling and debilitating factors in understanding and implementing LRT. These findings call for attention to a need for revisiting mainstream English language teacher education trends and embracing more socio-politically informed linguistically responsive approaches. Copyright © 2024 Taylor and Francis Ltd.

Due to the prevalence of information and communication technologies (ICT) among secondary school students and the increasing significance of digital reading, exploring the impact of ICT on students' digital reading performance in English seems necessary. The current research aimed to examine the effects of ICT competencies factors on secondary school students' English digital reading performance. Data were obtained from 7703 15year-old students from three East Asian economies, Macau, Hong Kong, and Singapore, from the Programme for International Student Assessment (PISA) 2018 dataset. The results of hierarchical regression analysis revealed that students' ICT literacy was negatively correlated with their English digital reading performance, while the influence of attitudes toward ICT varied across the three East Asia economies. Additionally, males had lower English digital reading achievement, while students with higher socioeconomic status (SES) had higher English digital reading performance. Copyright © 2024 Elsevier.

During the COVID-19 pandemic, many online lessons for emergency remote teaching (ERT) were recorded. However, little is known about how these recordings can be reused as resources for students' active learning. This study aimed to design a post -video learning approach that uses recorded videos of lessons to remediate students' learning losses associated with the pedagogical challenges of ERT. Two classes (54 students in total) with two teachers of general studies and mathematics in a Hong Kong primary school participated in a quasi -experimental study in which they used an approach integrating video selection, visualizations of classroom dialogues, a discussion forum, and quizzes for 10 weeks. After the intervention, the students' mathematics knowledge had improved significantly relative to a comparison group, while the general studies class did not show significant changes. Eight students and two teachers were interviewed about their experiences with the post -video learning approach. The approach appeared to be a pedagogically meaningful way of engaging students in active learning activities and addressing the challenges raised by ERT by recycling recorded lessons. The results of this study also suggest that recorded lessons can be useful learning materials beyond tertiary education as they cater to younger learners' needs in video -based learning by, for example, segmenting class videos, using visualization for easier viewing, and including discussion forums and quizzes for enhanced interaction. The design implications of using video segments and visualized representations of classroom interactions as learning materials and how to foster knowledge co -construction through forums and quizzes are also discussed. Copyright © 2024 International Forum of Educational Technology and Society .

This study introduces a model of Bloom's taxonomy aimed at deepening learners' cognitive thinking. It investigates the process of questioning and reflection within the structured framework of Bloom's taxonomy and explores how these insights can be applied in students' utilisation of generative Artificial Intelligence. An experiment was conducted in a Year 5 class at an International Baccalaureate Primary school in Hong Kong, involving 25 students. The findings indicate that Creating and Evaluating were the dominant aspects in the students' questioning and answering process. However, the skill of 'Applying' showed a significantly low influence, suggesting a lack of proficiency in applying AI conversations to other learning areas. This research contributes to the field by providing insights into the integration of generative AI within Bloom's taxonomy. Educators and researches can utilise these findings to enhance critical thinking and learning outcomes through AI integration. Copyright © 2024 Routledge.

PurposeThis research investigates mobile security awareness among university students in Hong Kong, who increasingly rely on mobile devices for their daily activities and academic needs. This research seeks to inform targeted educational strategies and policies to enhance mobile security practices among young adults, particularly in regions similar to Hong Kong, where mobile usage is extensively integrated into everyday life.Design/methodology/approachUtilizing an online survey, this research assessed the mobile security awareness of 407 university students from Hong Kong. The Mann-Whitney U-test and other statistical methods were employed to analyze differences in security awareness based on demographic factors such as IT background, gender, educational level and participation in mobile security courses.FindingsThe research revealed a generally high level of mobile security awareness compared to similar research in other regions. It also highlighted that despite no significant difference in awareness between genders, students from IT-related fields or those who participated in mobile security courses exhibit higher awareness levels. These findings underscore the impact of focused education and training on enhancing mobile security awareness.Originality/valueThis research contributes to the limited but growing body of literature on mobile security awareness from the end-user perspective, particularly among university students in the Asia Pacific region. It offers valuable insights for governments, educators and corporate policymakers worldwide, providing a basis for integrating mobile security education into broader academic and professional training programs. Copyright © 2025 Emerald Group Publishing.

Although artificial intelligence (AI) is becoming more commonly integrated into our everyday lives, homes, and schools, there needs to be more research regarding parental attitudes toward using AI technologies and AI literacy education to understand better and advance AI and AI literacy in kindergarten. To address this gap, this study explored kindergarten parents' perceptions of using AI technologies and AI literacy education in kindergarten. In Study One, 215 parents completed a survey regarding their views and concerns about the use of AI technologies and AI literacy education in kindergarten, the challenges encountered in AI literacy education in kindergarten and their opinions on the use of AI technologies in kindergarten. In Study Two, we interviewed five parents to gain further insight into their perspectives. The results indicated that 74.4%, 19.1%, and 6.5% felt positive, neutral, and negative towards using AI technology in kindergarten settings, respectively, illustrating that most parents remained positive. Results showed that most parents reported that it is suitable for kindergarten children to learn about AI tools and AI literacy. The kindergarten level may be an appropriate starting point for learning AI literacy. We found that the four main challenges that parents reported their children encountered when learning about AI literacy are limited comprehension ability, time constraints, the difficulty of the AI learning content, and uncertainty regarding the appropriateness of AI learning content for children. The findings indicate that Hong Kong parents positively perceive using AI in kindergartens. Still, designing AI-based educational tools for kindergarten children must address the challenges identified while ensuring equal access for all children. Copyright © 2025 Springer.

Purposeful and strategic use of L1 can help with L2 learning. However, in many contexts, monolingual immersion approaches dominate, leading language teachers to refrain from using L1. It can also mean that teachers are not professionally prepared to implement evidence-informed uses of L1. In this article, we share the findings of an intervention study that aimed to raise preservice English language teachers' awareness of purposeful L1 use while co-exploring ways generative artificial intelligence (AI) tools (e.g. ChatGPT) can aid teachers' knowledge development and strategic utilization of L1 in L2 classrooms. Data were collected from fifty-six preservice language teachers in Hong Kong through a pre- and post-intervention mixed-method survey and follow-up group interviews. The findings show that explicit instruction on the use of L1 in L2 classrooms can increase preservice teachers' intention to use L1 as well as their knowledge about the evidence-informed use of L1 and the ways in which generative AI tools can assist their implementation of L1. Copyright © 2024 Oxford University Press.

University admission consultation is a professional service that assists students with the university application process. Typically, accessing this service entails exploring university websites, directly contacting faculty members and officers via phone calls or emails, and engaging educational intermediaries. University admission consultation is crucial for both students and institutions. However, conventional consultation methods face challenges such as time and spatial constraints, leading to a growing interest in utilizing chatbots for university admission consultation. In this study, we propose a novel approach that leverages generative pretrained transformer (ChatGPT 3.5) models and implements the retrieval-augmented generation technique using the LlamaIndex framework. To evaluate the effectiveness of this approach, we applied it to undergraduate admission data from three universities: a science and technology university in the United States, a comprehensive university in Kenya, and a comprehensive university in Hong Kong. We also gathered feedback from 53 high school students who tested the chatbot. The results demonstrated a significant improvement in average accuracy, from 41.4% with the ChatGPT 3.5 model to 89.5% with the proposed chatbot, with peak accuracy reaching 94.7%. User reviews also indicated a generally positive perception of the admission chatbot. This methodology has the potential to revolutionize university admissions by utilizing chatbots based on large language models with retrieval-augmented generation. Copyright © 2024 International Forum of Educational Technology and Society .