Providing Personalized Learning Guidance in MOOCs by Multi-Source Data Analysis
When: Thursday, October 18, 2018
Where: PGH 563
Time: 11:00 AM
Speaker: Prof. Ming Zhang, Peking University, China
Host: Prof. Zhigang Deng
Although millions of students have access to varieties of learning materials in Massive Open Online Courses (MOOCs), many of them feel lost or isolated in their learning experience. One of the potential reasons is the lack of interactions and guidance for individuals. Since MOOC students have diverse learning objectives, we propose to design different strategies for those students with different engagement styles. In this talk, I will introduce personalized learning guidance for MOOC students based on multi-source data analysis. We first conduct content analysis to identify key concepts in the courses. We then propose two structured model to evaluate student knowledge states. We also study on student learning behaviors and design a dropout prediction system. The experiments show the effectiveness of our algorithms and we discuss on the result both quantitatively and qualitatively. Last but not least, we employ a web application of online student assessment service for both students and instructors to display student learning states and provide suggestion for individuals.
Dr. Ming Zhang received her Bachelor, master and PhD degrees in Computer Science from Peking University respectively. She is a full professor at the School of Electronics Engineering and Computer Science, Peking University. Prof. Zhang is the vice director of CCF Educational Committee, a steering member of ACM Education Council and the Chair of ACM SIGCSE China. She is one of the five Executive Committee Members of ACM/IEEE IT2017 and a member of the ACM/IEEE CC2020 steering group. Her research interests are knowledge graph and deep learning. Currently, she is the leading three projects funded by National Natural Science Foundation of China. She has published more 200 research papers on machine learning in the top journals and conferences, such as ICML, KDD, AAAI, IJCAI, ACL, WWW and TKDE. She won the best paper of ICML 2014 and best paper nominee of WWW 2016. Prof. Zhang is the leading author of several textbooks and MOOC courses on Data Structures and Algorithms. The corresponding course is awarded as the National Elaborate Course by MOE China. More information can be found at http://net.pku.edu.cn/dlib/mzhang/.