AI-Driven Transformation of Mathematics Education

Join us to discover how AI technologies and tools are revolutionising mathematics teaching and learning and uncover AI potential in enhancing students' understanding, problem-solving skills, and overall mathematical proficiency.

This seminar aims to inspire academics and researchers to leverage AI in transforming mathematics education and preparing students for the digital age.

Join the 800 education practitioners and students from various academic disciplines at this seminar and be informed of the featured speakers' experiences using the latest AI technologies and tools in promoting student-centred teaching methods.

Points to Note:

[CUHK Teachers]

Kindly sign in with the single sign-on system (SSO) on Zoom and join us at this seminar. It will enable us to identify your affiliated institution and award you the credits for the Professional Development Course.

[MTAPTL Members]

Kindly type the name on Zoom as the same as you registered for this seminar to access the meeting. It will enable us to identify your affiliated association and award you the certificate of attendance.

Co-organisers:

The Centre for Learning Enhancement And Research (CLEAR) is an academic unit at The Chinese University of Hong Kong (CUHK) dedicated to promoting excellence and scholarship in teaching and learning. Committed to advancing high-quality education, CLEAR supports CUHK's mandate by fostering a culture of innovation and advancement in teaching. It provides opportunities for academics to share their experiences and collaboratively enhance teaching practices at the CUHK and beyond.

The Mathematics Teachers Association of the Philippines Tertiary Level, Inc (MTAPTL) is a professional organisation dedicated to promoting excellence in mathematics teaching and learning at the tertiary level in the Philippines. It serves as a platform for mathematics educators to collaborate, share best practices, and contribute to the continuous improvement of mathematics education in higher education institutions nationwide.

Moderators:

Professor Paul Lam joined the Centre for Learning Enhancement And Research at The Chinese University of Hong Kong (CUHK) in January 2003. As an educator committed to enhancing the learning experience, he has explored and developed expertise in teaching and learning principles, case-based teaching and learning, and web-assisted teaching and learning. His work extends to evaluating e-learning and m-learning environments, and he has a rich background in designing innovative education tools. Among his notable contributions, Professor Lam is the principal investigator of the "AI in Education" project (https://aiforeducation.net), which seeks to integrate artificial intelligence into education practices to improve learning outcomes. Additionally, Professor Lam supervised the development of uReply (http://web.ureply.mobi), an interactive classroom student response system designed to foster engagement and facilitate real-time feedback in education settings.

Dr Aileen A Diansuy, with an extensive educational background encompassing a Bachelor of Science in Mathematics and a PhD in Mathematics, is committed to continuous learning and academic excellence. She has demonstrated academic leadership by holding administrative roles such as Officer-in-Charge, Office of the President and the Chief Administrative Officer at the Antipolo Institute of Technology (AITECH). Her broad teaching experience, spanning institutions such as the University of the East, National University, Pamantasan ng Lungsod ng Maynila, and De La Salle-College of Saint Benilde, emphasises curriculum development and faculty training. Actively involved in research, she has presented at national and international conferences. Meanwhile, her role as the President of the Mathematics Teachers Association of the Philippines Tertiary Level, Inc (MTAPTL) underscores her commitment to professional development in mathematics education.

Topics & Speakers:

1. An Overview of the Impact of AI on Mathematics Education for College Students

Dr CHEUNG William, Senior Education Development Officer, Talent and Education Development (TED) Office, City University of Hong Kong

Recent technological advancements in AI, such as generative AI, have significantly impacted various aspects of our lives, and mathematics education at the tertiary level is no exception. This presentation attempts a non-exhaustive overview of how AI can be incorporated into learning, teaching, and assessing mathematics education, thus assisting students and educators in learning and teaching more effectively.

Biography:

Over the past years, William has accumulated his experience in higher education as a frontline educator and a facilitator to promote the enhancement of learning and teaching. In terms of teaching, he has mainly been focusing on artificial intelligence literacy, general education for university students, and scientific literacy for science students (such as mathematical modelling and the scientific method). William is passionate about experimenting with various teaching methods, such as flipped classrooms, and engaging with students as partners. He also has experience organising science outreach activities to introduce science to a broader audience.

2. Leveraging Prompt Engineering in Large Language Models with Active Learning Strategies to Boost Mathematics Outcomes

Dr TING Fridolin, Senior Lecturer I, Office of the Vice President (Research & Development), The Education University of Hong Kong

This talk will explore integrating prompt engineering in large language models like ChatGPT with active learning pedagogies to advance mathematics education. We will investigate how ChatGPT's capacity to generate personalised and contextualised responses can enhance students' conceptual understanding and how specialised formatted prompts, like "zero-shot" and "chain of thought" techniques, can augment critical thinking and problem-solving skills. Practical examples will be showcased to illustrate their role in creating a more engaging and tailored learning experience and to demonstrate the application of these AI-driven strategies in classroom settings. The session will highlight the transformative potential of marrying generative AI with student-centred teaching approaches to improve learning outcomes in mathematics and science education significantly.

Biography:

Dr Ting has taught university-level mathematics in Canada and Hong Kong for over 20 years. He was the PI of a UGC triennium 2016-19 teaching and learning project called "Developing Active Learning Pedagogies and Mobile Applications in University STEM Education" (http://palms.polyu.edu.hk/), collaborating with four Hong Kong universities and 30+ professors and instructors. The PALMs project developed 13 active learning pedagogies and supporting apps to increase students' learning outcomes in STEM-related tertiary education and has won over ten local and international educational awards. He also was the PI for a QEF Project entitled "Developing Active Learning Pedagogies and Mobile Applications in Secondary School Mathematics Education", which involved nine secondary schools, 47 teachers and over 1800+ secondary school students. He was a finalist in Hong Kong's University Grants Committee (UGC) Teaching Awards (General Faculty) in 2021, President's Teaching Award at PolyU (2021), and has published over 20 articles in highly reputable educational and mathematical journals. He is now actively incorporating generative AI into active teaching pedagogies in science, mathematics, and student entrepreneurship education.

3. Blended Learning in Fundamental Mathematical Courses with AI Integration

Professor ZHUANG Xiaosheng, Associate Professor, Department of Mathematics, College of Science, City University of Hong Kong

In this new era of AI, many AI tools have been developed for various purposes, such as ChatGPT, Google Bard, Stable Diffusion, etc. Especially in education, it becomes increasingly important to know how AI can support teachers with more than just generalised ideas to change/enhance student learning outcomes. Blended learning (or flipped learning), collaborative learning, and other learning models in modern education can help improve students' learning experiences and outcomes. I will share my experiences integrating AI tools and basic learning models into teaching fundamental mathematical courses such as probability and statistics.

Biography:

Dr ZHUANG Xiaosheng received his bachelor's and master's degrees in mathematics from Sun Yat-sen (Zhongshan) University, China, in 2003 and 2005 respectively. He received his PhD in Applied Mathematics from the University of Alberta, Canada, in 2010. He was a Postdoctoral Fellow at Universität Osnabrück in 2011 and Technische Universität Berlin in 2012. He joined the Department of Mathematics of the City University of Hong Kong in 2012. He served as the department Associate Head from 2018 to 2021. He is now an Associate Professor in the Department of Mathematics at the City University of Hong Kong. Dr ZHUANG Xiaosheng's research focuses on applied and computational harmonic analysis, wavelet and framelet analysis, signal and image processing, deep and machine learning, etc. He has published more than 40 academic papers in international journals, including Applied and Computational Harmonic Analysis (ACHA), SIAM Journal on Imaging Sciences (SIIMS), Mathematics of Computation, ICML, JMLR, IEEE TNNLS, IEEE TIP, Neural Networks, Pattern Recognition, etc.