Artificial Intelligence for Teaching, Learning and Assessment
[This webinar is a re-run of an HKU internal seminar organized on 17 February 2021, with new examples added.]
Artificial Intelligence (AI) is the fastest-growing technology in various fields. The adoption of AI spans the global learning landscape and has been used in experiential learning, tutoring, language learning, and knowledge testing. In higher education, some educators have identified the affordances of AI and utilized this technology in making teaching and learning more effective. In particular, there is a high demand for teachers to provide meaningful and prompt feedback to students within and beyond the classroom. However, designing such an experience can be challenging as this requires a lot of teachers’ time and attention to their students. Systems powered by AI can provide 24/7 support to teachers and multiple learners at the same time, with personalized support and guide them in an engaging way in the virtual environment. Some may worry that creating an AI tool from scratch requires complex computer programming skills but there are more and more AI-facilitated tools for teaching and learning.
In this webinar, we would like to discuss the potential and affordances of AI in education with some examples of AI tools for classroom engagement and assessment. Through the webinar, participants can reflect on better practices and design considerations in AI-facilitated teaching and learning.
Upon completion of this seminar, the participants will be able to:
- Identify the opportunities and challenges of adopting AI tools in the classroom; and
- Use the concept of AI learning technologies and learning analytics to facilitate classroom learning and assessment.
Dr. Leon Lei is currently an e-learning technologist in the University of Hong Kong (HKU). He received his Ph.D. degree in electrical and electronics engineering from HKU. He has been working on remote/blended/MOOC learning initiatives in higher education and K12 education. His research interests include learning analytics, open licensing and education, and chatbot tutors. He was awarded with the Best/Outstanding Paper Award in IEEE International Conference on Teaching, Assessment, and Learning for Engineering (TALE) 2013, 2017 and 2020. He is an IEEE Senior Member and an Advance HE Senior Fellow.
Dr. Christopher See is presently a lecturer at the School of Biomedical Sciences, Faculty of Medicine at the Chinese University of Hong Kong (CUHK) teaching human anatomy. He is a Fellow of the Academy of Medical Educators UK (FAcadMed) as well as the Higher Education Academy (FHEA). His research interests are gamification, e-learning and particularly the use of Artificial Intelligence (AI) in medical education. He graduated from the Oxford AI programme, the University of Oxford in 2020 and has taught modules on AI in Healthcare, introduction to Machine Learning, Neural Networks and Deep Learning as part of medical school curricula.
This webinar is supported by:
– UGC Special Grant for Strategic Development of Virtual Teaching and Learning – Inter-institutional Collaborative Activities Projects
– IEEE Region 10 Education Activities Committee (2021 Region-10 Call for Capacity Building Workshop under Educational Activity; IEEE R-10 EAC’s Call for Proposal for “Reaching Local Initiatives”)
– IEEE Hong Kong Section and IEEE Hong Kong Section Education Chapter.