- Teaching and Learning Computational Thinking at Scale
- Prof. Ting-Chuen PONG, Professor, Computer Science & Engineering Department, The Hong Kong University of Science and Technology
- 09:45-10:45, 9 June 2018 (Saturday)
- Rayson Huang Theatre, The University of Hong Kong
- Medium of instruction:
- English 英語
- Computational Thinking
- Prof. Nancy Law, Deputy Director, CITE, Faculty of Education, The University of Hong Kong
Slides & Video
In recent years, computational thinking has attracted a lot of attention because it is increasingly recognized as a fundamental 21st century skill for everyone. Computational thinking has been introduced into the national curricula starting as early as K-12 in various countries, as well as being offered to adult learners for professional development. In this presentation, I will share our experience in teaching computational thinking to a mass audience by using Massive Open Online Courses (MOOCs). These MOOCs were designed using the concepts of computational thinking as approaches to problem solving.
Education has gone through transformative changes since the launching of MOOCs in 2012. MOOCs can reach hundreds of thousands of learners from around the world. New pedagogies have been developed using MOOCs. Learning analytics on the large-scale data collected from MOOCs allow teachers to better understand how students learn and how the delivery of teaching and learning can be enhanced. I will discuss how to use MOOCs and learning analytics to enhance students’ learning experience in computational thinking through blended and experiential learning.
About the speaker
Professor Ting-Chuen Pong is a Senior Advisor to the Executive Vice-President & Provost, Director of the Center for Engineering Education Innovation and Professor of Computer Science & Engineering at the Hong Kong University of Science & Technology (HKUST). He is a founding faculty member of HKUST, where he had served as the Associate Vice-President for Academic Affairs, Associate Dean of Engineering and Director of the Sino Software Research Institute. Before joining HKUST, he was an Associate Professor of Computer Science at the University of Minnesota. He received his PhD in Computer Science from Virginia Polytechnic Institute and State University. His research interests include computer vision, multimedia computing and IT in Education. He is a recipient of the Pattern Recognition Society Award in 1990 and the HKUST Excellence in Teaching Innovation Award in 2001. In 2014, he led the HKUST team in the Wharton-QS Stars Awards Competition and was selected Winner of the Natural Sciences Award and Runner-up of the Hybrid Learning Award.