We opended a workshop at ICEEG 2018. Welcome Assoc. Prof. Vincent TY Ng from Hong Kong Polytechnic University, Hong Kong to be the chair of workshop and keynote speaker.
Assoc. Prof. Vincent TY Ng
Hong Kong Polytechnic University, Hong Kong
Vincent Ng received the B.Sc. degree in mathematics and computing science from the Simon Fraser University, Canada in 1982. He later studied in the University of Waterloo, Canada, and received his M. Math degree there in 1986. In 1994, he received his Ph.D. degree from Simon Fraser University. At present, he is an associate professor in the Department of Computing of the Hong Kong Polytechnic University. In PolyU, he received a number of awards in teaching and professional services. Dr. Ng is now the director of the Joint PolyU/IBM Enterprise Data Analytics Laboratory. His research interests include databases, data analytics and bioinformatics. He has many publications in academic journals and international conferences including Neurocomputing, Computational and Mathematical Methods in Medicine, ACM Transactions on Computing Education, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Journal of Computers in Biology and Medicine, International Journal of Artificial Intelligence Tools, IEEE TKDE, Mathematical Biosciences, and Journal of Clinical Oncology. Besides teaching and research, Dr. Ng is active in consultancy work and professional services. He received several awards from PolyU for his contributions in the consultancy area. He has been working with different government units in the HKSAR, such as the Securities and Futures Commission, Social Welfare Department, the Immigration Department, the Department of Justice, the Police Department, the Employment and Manpower Bureau, QEF, and the Civil Service Training and Development Institute. In the professional community, he has been the chairman of the Information Technology Division of the Hong Kong Institute of Engineers, a board member of The Hong Kong Institute for IT Professional Certification, and has organized a number of international conferences.
Using Learning Analytics with Jupyter as A Means to Inform Learning
Abstract: Learning Analytics uses learner data to understand and optimize learning. In an enterprise that hosts elearning content or discussion forums, instructional designers can identify patterns of learning behaviours and adjust the instructional strategies according to the results of statistical, qualitative analyses and text analysis.
In this workshop, we will introduce some basic features of Jupyter Notebook and how to use this widely used open source web application to work with data files to perform learner data analysis in learning management platforms such as Moodle. A sample dataset will be used to illustrate a variety of data visualization functions and machine learning techniques for exploring learning behaviors to improve the impact of the learning process.