ABSTRACT

(1) Pre-Laboratory Preparations

Dr Joe LAM [Staff Profile]

Lecturer

Department of Applied Biology and Chemical Technology

The Hong Kong Polytechnic University

GenAI-Empowered Demonstration Videos to Support Students' Pre-Laboratory Class Study

This study investigates the application of GenAI-empowered laboratory class videos and the Panopto (uRewind) video platform in general education and disciplinary science courses. We have also evaluated the effectiveness of our approach using the students' survey and focused group interview. We invited approximately 250 students to participate in this study in the 2023/24 Semester 1, and we collected their feedback through surveys and focus group interviews. The results showed a significant increase in Panopto visits during weeks 5-7, coinciding with the start of laboratory classes. Student feedback indicated a strong preference for the flipped approach, with 31-71% of students agreeing or strongly agreeing with its effectiveness.

The findings suggest that our GenAI-supported active learning approach can provide better learning support for students. Further research is needed to confirm these initial results and explore their implications for science education in a post-pandemic context.

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(2) Practical Laboratory Skills Development

Dr Yee Ling CHONG [Staff Profile]

Senior Lecturer II

Department of Science and Environmental Studies

The Education University of Hong Kong

Integrating Microscopy and Artificial Intelligence to Foster Science Practical Skills

Microscopy has long served as a cornerstone of science education, enabling students to visualise the microscopic world and fostering a deeper understanding of natural phenomena. Modern digital microscopes with advanced imaging capabilities offer interactive learning experiences that bridge theoretical knowledge and practical application. These technologies can enhance microscopy by enabling personalised, adaptive learning pathways integrated with AI-powered tools. This presentation introduces a case study on developing a web-based platform for classifying tissue specimens, incorporating a supervised AI-driven deep learning system. The platform, designed to promote self-directed learning, aims to strengthen students' analytical skills in microscopy image analysis. Through the platform, students receive AI-generated feedback to validate and refine their image analyses, alongside self-assessment quizzes to reinforce learning. The presentation will share student feedback and experiences, illustrating the platform's effectiveness and practical implementation in laboratory exercises. Finally, the discussion will address challenges and considerations for integrating such transformative technologies into education, including balancing innovation with pedagogical goals and ensuring equitable access.

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(3) Assessment Innovation and Efficiency

Dr Sam HAU [Staff Profile]

Lecturer

Department of Chemistry

The Chinese University of Hong Kong

AI-Assisted Assignment Grading Platform for Chemistry Foundation Course

Foundation courses cater to over 350 students each academic year, presenting significant grading challenges for instructors and teaching assistants. With four take-home assignments, a mid-term quiz, and a centralised final examination each semester, the workload is immense. Therefore, we propose developing an AI-powered grading platform designed explicitly for essay-type assignments to address this. Our AI bot will train to recognise various writing styles and evaluate work through similarity checks. This innovative platform will handle six question types, revolutionising teaching and learning. By implementing this AI-driven solution, we can significantly reduce the grading burden on instructors and teaching assistants, allowing them to focus more on student engagement. The platform will provide timely feedback, including detailed performance reviews, helping students identify their strengths and weaknesses early on. In addition, it will generate comprehensive performance summaries for instructors, enhancing their ability to monitor and support student progress.