Drawing on the Chinese philosophical concepts developed in the course, six debaters coming from around the world will discuss the topic “We should follow the social conventions of our society” from the affirmative and negative perspectives. Course instructor Professor Chad Hansen will adjudicate the debate and summarize the ideas presented.
Details of the debate:
Date: August 15, 2015 (Saturday) Time: 22:00 HKT / 14:00 UTC Language: English
Organized by e-learning Pedagogical Support Unit, CETL
Speaker: Dr. Jingli Cheng, e-learning Pedagogical Support Unit Date : 13 August, 2015 (Thursday) Time : 12:45pm – 2:00pm Venue : Room 321, Run Run Shaw Building
Abstract:
Communities of practice as an approach to informal learning has received attention from various types of organizations, including higher education institutions. A fundamental process underlying successful communities of practice is knowledge sharing. Yet, empirical understanding of motivations for knowledge sharing is lacking, especially with regard to an important subset of participants in these communities, the experts. Based on a research study that the speaker conducted with Google and Symantec, this presentation will highlight the key factors that motivated expert participants’ knowledge sharing behaviors in the two companies’ online user communities.
Colleagues who are considering implementing communities of practice or knowledge sharing initiatives in and beyond their organizations may get useful insights from this presentation. Teachers who are thinking about motivating student participation in online communities may also find this workshop beneficial. All are welcome.
About the Speaker:
Dr. Jingli Cheng has extensive experience applying instructional design theories and best practices in various organizational settings to help learners improve their knowledge and skills. Before joining HKU’s e-learning Pedagogical Support Unit, he worked as Instructional Designer at Stanford University, the Hewlett Packard company and several other organizations in the United States. His research interests include motivation for knowledge sharing in online communities and informal learning in organizational settings.
Speaker: Dr. Jingli Cheng, e-learning Pedagogical Support Unit Date : 9 July, 2015 (Thursday) Time : 12:45pm – 2:00pm Venue : Room 321, Run Run Shaw Building
Abstract:
How Massive Open Online Courses (MOOCs) are changing the higher education landscape is much talked about in academic and popular writings, yet for professors, designers and support staff of MOOCs, very little exists that serves as practical guidance for design, production and implementation of MOOCs.
In May 2015, the University of Hong Kong successfully concluded a Massive Open Online Course on the topic of vernacular architecture. A rigorous design, production and implementation process was key to the success of this course. In this presentation, Dr. Jingli Cheng, lead instructional designer and project manager of the MOOC, will share experience, best practice, and lessons learned through the project.
Go behind the scene and learn about the essential elements that led to a successful MOOC!
About the Speaker:
Dr. Jingli Cheng has extensive experience applying instructional design theories and best practices in various organizational settings to help learners improve their knowledge and skills. Before joining the HKU’s e-learning Pedagogical Support Unit, he worked as Instructional Designer at Stanford University, the Hewlett Packard company and several other organizations in the United States. His research interests include motivation for knowledge sharing in online communities and informal learning in organizational settings.
Philosophy can be a daunting subject to teach, as it often involves the explanation of complex and abstract ideas, and encouraging students to think creatively and independently. The challenge becomes more pronounced in the context of online teaching, where students learn remotely and independently in front of their own computers. How do you engage the students and maintain their attention span, while doing justice to the intellectual depth of the subject? Such was the challenge we faced when we produced HKU03x Humanity and Nature in Chinese Thought.
Course Instructor Professor Chad Hansen is a brilliant philosophy teacher. His lectures are always intellectually challenging and interesting at the same time. So how did we turn his course into a MOOC? At first we tried the traditional method of asking the teacher to speak directly into a teleprompter, as if addressing the viewers himself. The result was not bad, but that could not capture the dynamic and engaging character that his lectures are well known for – something was missing.
So the production team tried a new and risky method – we put Professor Hansen in a small classroom setting and surrounded him with real students and cameras. We shot it like a mini-concert in order to capture his signature performance. We also spent weeks talking to Professor Hansen and the course team learning about the subject matter, and then got our graphic designer to design some interesting and relevant visuals to present those abstract philosophy concepts. And the result was great.
This balance between education and entertainment is a hard one to strike. And we hope, with this new attempt, we will be able to make the teaching of abstract subjects as informative, enlightening, and enjoyable as possible. And we cordially invite you to take part in this.
Speaker: Dr. Una-May O’Reilly, Principal Research Scientist, AnyScale Learning For All Group, MIT Computer Science and Artificial Intelligence Laboratory Date : 16 June, 2015 (Tuesday) Time : 12:45pm – 2:00pm Venue : Room 321, Run Run Shaw Building
Abstract:
Understanding why students stopout will help in understanding how students learn in Massive Open Online Courses (MOOCs). In this seminar, Dr. Una-May O’Reilly will describe how she and her research group build accurate predictive models of MOOC student stopout via a scalable, prediction methodology, end to end, from raw source data to model analysis. They attempted to predict stopout for the Fall 2012 offering of MIT’s 6.002x.
This involved the meticulous and crowd-sourced engineering of over 25 predictive features extracted for thousands of students, the creation of temporal and non-temporal data representations for use in predictive modeling, the derivation of over 10 thousand models with a variety of state-of-the-art machine learning techniques and the analysis of feature importance by examining over 70,000 models. They found that stopout prediction is a tractable problem. Their models achieved an AUC (receiver operating characteristic area-under-the-curve) as high as 0.95 (and generally 0.88) when predicting one week in advance. Even with more difficult prediction problems, such as predicting stop out at the end of the course with only one weeks’ data, the models attained AUCs of ~0.7.
About the Speakers:
Dr. Una-May O’Reilly (http://people.csail.mit.edu/unamay/) leads the AnyScale Learning For All (ALFA) group (http://groups.csail.mit.edu/ALFA) at Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory. ALFA focuses on scalable machine learning, evolutionary algorithms, and frameworks for knowledge mining, prediction and analytics. She received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013 and serves as Vice-Chair of ACM Special Interest Group for Genetic and Evolutionary Computation (SIGEVO).
