This workshop introduces core AI concepts, explores how large language models (LLMs) work, presents some basic AI tools, and examines the ethical considerations critical to education, such as bias, privacy, academic integrity, and equitable access. Through interactive discussions and real-world examples, participants will learn to use AI tools responsibly and develop an understanding of ethical guidelines for harnessing AI’s potential in learning and teaching. This workshop also lays the groundwork for subsequent workshops by establishing a shared vocabulary and ethical framework for AI use in learning and teaching.

This hands-on workshop introduces practical ways to use AI tools (e.g. EdUHK GenAI, Google Gemini) to search for information, generate content aligned with learning outcomes, create interactive and engaging learning activities, and produce data visualisations that support pedagogical decision-making. Participants will practise using AI tools for lesson planning and the preparation of teaching materials, with the aim of enhancing efficiency and reducing workload.

In learning and teaching, both teachers and students face the challenge of delivering high-quality, visually engaging content. This hands-on workshop introduces participants to practical applications of AI in graphic design and animated video production. By using AI tools (such as Dreamina, Kling, Pixverse, and CapCut), participants will learn how AI can streamline design processes, enhance creative skills, and produce compelling teaching materials. Participants will also practise crafting eye-catching task cards, infographic posters, and animated concept-explanation videos, making design tasks more efficient and accessible for everyone.

This hands-on workshop explores AI tools for generating practice questions, automated quizzes, personalised feedback comments, and progress dashboards. Participants will learn to combine AI efficiency with human insight to support formative assessment while maintaining academic integrity. Through practical exercises, participants will also practise generating quizzes automatically from their own lecture notes and materials. This workshop will equip participants with the practical skills to save time and enhance student learning outcomes through effective formative assessment.

Large classes pose significant challenges for instruction, feedback, and engagement. This workshop introduces practical ways to use AI and educational tools (e.g. Moodle, Mentimeter) to support large-class teaching while protecting academic integrity and maintaining learning quality. Participants will learn how to use these tools for tasks such as designing scaffolded activities, improving accessibility, and enhancing real-time interaction. The workshop will also explore effective ways to deploy teaching assistants to strengthen facilitation, responsiveness, and learning outcomes.

AI chatbots can provide instant feedback to support learning and teaching. This hands-on workshop guides participants in designing educational chatbots for tasks such as handling FAQs, providing student support, explaining concepts, and guiding learning through Socratic questioning. The workshop will demonstrate Retrieval-Augmented Generation (RAG) technology to enhance response accuracy and reduce hallucinations by grounding answers in participants’ course materials. It will also address limitations, data privacy considerations, and integration with existing Learning Management Systems (LMS) such as Moodle.

This hands-on workshop covers designing GenAI agents on AI platforms (e.g. the LTTC MaaS platform) to execute automated workflows and process complex documents. Participants will explore multi-step agent workflows and integration strategies suitable for learning and teaching. The workshop will also introduce “Vibe Coding” - an approach to software development using natural language prompts to generate code - as a means of creating customised learning tools for diverse teaching contexts. Participants will gain the skills needed to responsibly develop and deploy generative AI agents that enhance the learning and teaching experience.

This talk explores responsible AI and professional identity through the lens of human behaviour, trust, and digital wellbeing. Drawing on recent work on AI dependency, AI apprehension, trust calibration, explainability, and persuasive system design, it examines how Generative AI and Large Language Models are reshaping academic practice, cognitive effort, and human agency. The session discusses the tension between AI as augmentation and AI as a source of over-reliance, cognitive offloading, and behavioural influence. It further reflects on the role of educators and researchers in modelling responsible AI use in an era where conversational AI systems increasingly shape learning, decision-making, and professional practice.

As autonomous AI agents become increasingly capable, understanding their risks is crucial. This workshop will introduce current autonomous AI agent frameworks (e.g. OpenClaw, Hermes, etc.) and their functions, explore how AI may reshape professional identity and the value of human skills, and examine potential pitfalls in the agentic AI era, such as over-reliance, bias amplification, metacognitive laziness, and other practical or ethical concerns in educational settings, while providing practical suggestions for responsible use. It will also present case studies on learning, teaching, assessment, and educational administration to demonstrate how to maintain a human-centred mindset and sound decision-making practices when using autonomous AI agents.

As autonomous AI agents become increasingly capable, understanding their risks is crucial. This workshop will introduce current autonomous AI agent frameworks (e.g. OpenClaw, Hermes, etc.) and their functions, explore how AI may reshape professional identity and the value of human skills, and examine potential pitfalls in the agentic AI era, such as over-reliance, bias amplification, metacognitive laziness, and other practical or ethical concerns in educational settings, while providing practical suggestions for responsible use. It will also present case studies on learning, teaching, assessment, and educational administration to demonstrate how to maintain a human-centred mindset and sound decision-making practices when using autonomous AI agents.