This study explores how AI-powered functionalities support young ESL learners in developing English pronunciation skills in informal learning settings. Based on empirical evidence from six Chinese students (aged 14–15), the study identifies both the benefits and challenges of AI in pronunciation training. It maps the emerging field of AI in English education, offering insights for educators and developers to improve the design and application of AI tools, thereby advancing language learning practices.

This study bridges the theory-practice divide in learning design by adapting the Learning Design Triangle (LDT) framework to guide co-design processes. Conducted in Mainland China, it follows an experienced teacher redesigning a first-year engineering course. Findings highlight a transition toward skill-oriented outcomes, active learning strategies, and improved alignment between pedagogy and assessment. It offers practical guidance for facilitating teachers' transition to student-centered learning design, providing both tools and insights for systematic course improvement.

This symposium synthesises four empirical studies exploring the implementation of GenAI-assisted DMC in language education. The findings demonstrate that integrating GenAI into DMC enhances L2 text and multimodal composition and creative translanguaging, enriching teacher feedback and redefining language teachers' identity. Rather than replacing language teachers, this symposium claims that GenAI catalyses pedagogical and professional innovation for language educators. It provides a valuable reference and direction for future empirical research on GenAI-assisted DMC.

This paper discusses the implementation of generative artificial intelligence (GenAI) in project assignments of two university courses. Through analyzing students’ projects written with the assistance of GenAI, the competencies required for effectively applying these technologies for project writing are evaluated. The characteristics and quality of the outcomes are compared to the previous works without using GenAI, which informs the modification of pedagogy and assessment design in STEM courses that incorporate project-based learning.

This study examines how a formative assessment model enhances secondary school ESL (English as a Second Language) students’ writing awareness and feedback utilization. Using structured learning records and scaffolding strategies, students engaged in iterative writing cycles integrating pre-lesson diagnostics, scaffolded activities, and post-lesson reflections. Results show improved writing structure but persistent challenges in logical cohesion. The findings highlight the need for refining formative assessment to support self-regulated learning and revising.

This study constructs the AI-Agent School (AAS) simulation environment, aiming to leverage LLM-driven agents to optimize teaching strategies and enhance both teaching and learning outcomes. Additionally, the Zero-Exp strategy is introduced for knowledge base accumulation, significantly improving the capabilities of AI-agents. Experimental results show that students in AAS achieved an overall score of 78.9, outperforming the human teacher control group. This research provides insights and practical references for exploring innovative applications of AI in education.

Generative AI in medical education remains promising but its effects on learner performance are unclear. Our pilot randomised controlled trial studied the impact of ChatGPT-assisted learning on anaphylaxis in undergraduate medical students. The intervention group outperformed the control in learning outcomes, highlighting potential AI dependency concerns. While ChatGPT aided knowledge retrieval, its efficacy in complex tasks was limited. Further research is crucial to understand AI-human interactions and mitigate biases.

This study utilizes action research to construct and optimize intelligent programming learning environments, combining intelligent design and learning analytics technologies. It explores ways to enhance learner interactivity and adaptability, driving the intelligent evolution of the educational ecosystem. The research aims to offer a new perspective on the integration of intelligent learning environments and learning analytics, while promoting the ongoing development of educational practices.

Transitioning from traditional content-driven teaching to student-centered learning poses learning design challenges for teachers. Often, key learning design principles may easily be overlooked during curriculum development. This interactive workshop demonstrates how the IDEALS system, with embedded design principles and a thinking process informed by the Learning Design Triangle framework, supports teachers in designing meaningful learning experiences for students and in using learning analytics to enhance teaching and learning.

This professional workshop focuses on sharing research findings and practical experience on leveraging external and internal networks to prompt pedagogical innovation in primary and secondary STEAM education in Hong Kong. Featuring three talks by the project team at HKU and experienced STEAM coordinators at local schools. Through theoretical insights and practical cases, this workshop will equip participants with strategies for integrating external resources and internal expertise in STEAM education, promoting a culture of collaboration.

Explore the comprehensive AI literacy training initiatives and resources from the Learning and Research Services Team at the University of Hong Kong Libraries. Discover how the library empowers students through a curated guide to AI Literacy, engaging training and practical workshops that enhance university students’ AI literacy and foster critical thinking. Attendees will gain insights into effective approaches for integrating AI discussions into educational practices, making this session valuable for educators, librarians, and researchers alike.

As artificial intelligence (AI) transforms information retrieval, traditional search models are evolving, introducing both opportunities and challenges. This interactive workshop explores how AI-powered agents reshape retrieval processes, influencing accuracy, reliability, and transparency. Through comparative analysis, case studies, and hands-on exercises, participants will explore AI-driven ranking, query interpretation, and prompt engineering. Designed for researchers and professionals, whether experts or novices, this session equips attendees with practical strategies to optimize AI-assisted search and retrieval.

Generative AI technologies, namely ChatGPT and DALL-E, are reshaping the educational landscape by enhancing personalization, creativity, and engagement. This paper explores how GenAI can inspire and transform learning experiences while addressing these ethical dilemmas. It examines the role of GenAI in fostering intelligent learning design and multimodal composing, emphasizing its potential to touch hearts and inspire minds through meaningful human-AI collaboration. Recommendations are provided to ensure equitable, ethical, and transparent integration of GenAI in education.

Classroom dialogue is essential for students’ knowledge construction, yet its effectiveness in primary science classrooms remains limited. This study applies learning analytics to analyze 758 minutes of exemplary lessons, identifying dialogue sequence patterns and high-quality interactions. Findings reveal that a **student-centered approach**, enhanced teacher-student interaction, dynamic dialogue, and optimized feedback foster effective classroom discourse. This study offers valuable guidance for improving primary science teaching and supporting students’ knowledge construction.

This study investigates how peer feedback shapes grit in online collaborative learning. Analyzing 34 undergraduates' feedback patterns through lagged sequence analysis reveals distinct behavioral impacts. Results demonstrate peer feedback effectively enhances grit, offering actionable insights for designing resilience-focused online pedagogy.

Feedback seeking is a critical learning process wherein students elicit information from GenAI or human sources. Guided by self-determination theory, this study explores how students’ feedback seeking experiences shape their diverse motivation development. Interviews with university students reveal how interactions with GenAI, teachers, and peers influence subsequent intrinsic motivation, extrinsic motivation, and amotivation to seek feedback. The findings suggest insights to support students’ autonomous motivation and feedback seeking skills from both GenAI and humans.

In the context of technological innovation driving educational technology development, CPS and innovation skills are crucial for high-quality talent. This study focuses on cultivating human-AI collaborative learning abilities using ChatGPT across different knowledge contexts and learning stages. The research tracks students' knowledge mastery and collaborative learning processes, employing paired t-tests, independent t-tests, ANOVA, and qualitative feedback analysis. The findings show human-AI interaction significantly enhances students' collaborative learning abilities, providing substantial support for educators in teaching.

This panel discussion will explore collaborative networks in enhancing STEAM education sustainability in Hong Kong. Panelists will analyze how external collaboration networks can foster connections among various stakeholders, address challenges of resource constraints and limited professional development, and ultimately provide policy suggestions for promoting effective STEAM initiatives. Attendees will gain new insights into external collaboration in STEAM education and practical recommendations for advancing STEAM education at a systemic level.

This study examines AI literacy interventions for low-achievement secondary school students in Hong Kong. Two interventions—one timetabled over eight weeks and another as a four-hour workshop—were conducted at low-resource schools. Results showed significant improvements in students' AI literacy, particularly in prompt engineering and content evaluation, with no difference in effectiveness between intervention lengths. Findings suggest that short, structured interventions can enhance AI literacy, and schools may implement co-curricular approaches to address digital divide challenges.

This study found that writing improvements dominated research on ChatGPT in English as a Foreign Language learning, with studies on writing in 2024 increasing more than fourfold compared to 2023, focusing on more specific components and in-depth analysis. A surprising rise in speaking studies also emerged, with ChatGPT enhancing fluency. Future studies could explore long-term effects, specific affective factors, reading and listening and individual learner differences to further understand ChatGPT’s sustained impact on different aspects.

This study examines the digital well-being of 461 senior high school students from two private schools in Manila and Quezon City, Philippines. Using a descriptive quantitative design, it employed a self-structured survey based on the Six Pillars of Digital Wellness framework. Findings indicate generally positive feelings about digital well-being across physical, mental, spiritual, social, intellectual, and safety domains, though improvements are needed. The study proposes a digital well-being blueprint to enhance students’ online experiences.

This research proposal aims to investigate the impact of AI-supported teacher professional development on teacher confidence, competence, and classroom implementation. The study will employ mixed-methods approach to evaluate the effectiveness of AI tools in enhancing teachers' professional development through a case study of teacher training programs. The findings are expected to provide valuable insights into the benefits and challenges of integrating AI into teacher training and classroom practices, offering recommendations for future professional development programs.

This paper reviews language instructors’ technology adoption in classes, focusing on how technological tools have enhanced collaborative learning. Based on an in-depth review of 53 empirical studies, this paper presents the seven most commonly used technological tools,i.e., 1) Cloud-based platforms, 2) Video conferencing tools, 3) Social media, 4) Learning management systems, 5) Digital gameplay, 6) Single-display groupware, and 7) Social annotation platforms. Selected articles indicated those tools generally have a positive impact on students’ learning.

Abstract: This meta-analysis explores the impact of instructional processes on university students' flow state in VR/AR educational environments under the SRL framework. Analyzing 10 studies, results reveal robust moderate effects for full-phase SRL integration (g = 0.60, I² = 0%), while partial implementations show higher heterogeneity (I² = 89–94%) and unstable effects. Findings emphasize holistic SRL design to optimize flow experiences and reduce methodological variability in immersive education.

This paper introduces Optimizing Directional Stimulus Prompting Through Human Feedback (oDSP-HF), a structured approach to AI-powered scaffolding that enhances LLM-driven educational support. By refining ‘Directional Stimulus Prompting’ (DSP) through user interaction, oDSP-HF enables LLMs to generate adaptive, reflective hints rather than direct answers. This approach was applied in the system prompting of two AI agents—Aiza and Alice, designed to support Academic English writing and computational thinking, respectively—demonstrating its practical applications in education.

The panel comprises four recent HKU doctoral graduates who have taken up university teaching in Hong Kong. Chad Kwong (part-time EdD 2024; part-time HKU lecturer in learning technology design), Jeremy Ng (PhD 2025; HKU lecturer in educational technology), Tiffany Bai (PhD 2022; EdUHK assistant professor in technology-enhanced learning), and Holy Shum (PhD 2024; HKSYU assistant professor in digital sociology) share their practice-informed HKU learning and local university teaching and research experiences with emerging technologies.

(Abstract not available)

(Abstract not available)

(Abstract not available)

(Abstract not available)

(Abstract not available)

(Abstract not available)