Keynote at The 19th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), November 22-25, 2015, Bangkok, Thailand
Big Education in the Era of Big Data
Irwin King
Department of Computer Science and Engineering
The Chinese University of Hong Kong
Abstract
Big Education is the convergence of Big Data in education as these are two hot topics of intense research and discussion in recent years. In particular, with the advent of Massive Open Online Course (MOOC), University Open Online Course (UOOC), Small Personal Online Course (SPOC), flipped classroom, etc., these novel online courses are providing quality education to the masses, and are fueling a transformative change with the use of technology. In this talk, I plan to introduce how Big Education can produce potentially relevant and positive teaching and learning experiences for the educators and students. We will also examine some technologies that are being used to support these changes in education. With the analytics being collected, we will be able to deliver better values to various stakeholders, e.g., identify at-risk students, help educators to teach more effectively, etc. Moreover, I will introduce a new project that is being funded by the Hong Kong SAR Government named, Knowledge and Education Exchange Platform (KEEP). The KEEP portal is a knowledge aggregator and technology integrator that provides access to educational resources anytime, anywhere, on any devices to anyone.
Biosketch
Prof. King's research interests include machine learning, social computing, web intelligence, data mining, and multimedia information processing. In these research areas, he has over 210 technical publications in journals (JMLR, ACM TOIS, IEEE TNN, Neurocomputing, NN, IEEE BME, PR, IEEE SMC, JAMC, JASIST, IJPRAI, DSS, etc.) and conferences (NIPS, IJCAI, CIKM, SIGIR, KDD, PAKDD, ICDM, WWW, WI/IAT, WCCI, IJCNN, ICONIP, ICDAR, etc.). In addition, he has contributed over 30 book chapters and edited volumes. Moreover, Prof. King has over 30 research and applied grants. One notable patented system he has developed is the VeriGuide System, previously known as the CUPIDE (Chinese University Plagiarism IDentification Engine) system, which detects similar sentences and performs readability analysis of text-based documents in both English and in Chinese to promote academic integrity and honesty.
Prof. King is the Book Series Editor for โ€Social Media and Social Computingโ€ with Taylor and Francis (CRC Press). He is also an Associate Editor of the ACM Transactions on Knowledge Discovery from Data (ACM TKDD) and a former Associate Editor of the IEEE Transactions on Neural Networks (TNN) and IEEE Computational Intelligence Magazine (CIM). He is a member of the Editorial Board of the Open Information Systems Journal, Journal of Nonlinear Analysis and Applied Mathematics, and Neural Information Processingโ€“Letters and Reviews Journal (NIP-LR). He has also served as Special Issue Guest Editor for Neurocomputing, International Journal of Intelligent Computing and Cybernetics (IJICC), Journal of Intelligent Information Systems (JIIS), and International Journal of Computational Intelligent Research (IJCIR). He is a senior member of IEEE and a member of ACM, International Neural Network Society (INNS), and Asian Pacific Neural Network Assembly (APNNA). Currently, he is serving the Neural Network Technical Committee (NNTC) and the Data Mining Technical Committee under the IEEE Computational Intelligence Society (formerly the IEEE Neural Network Society). He is also a member of the Board of Governors of INNS and a Vice-President and Governing Board Member of APNNA. He also serves INNS as the Vice-President for Membership in the Board of Governors. Moreover, he is the General Chair of WSDM2011, General Co-Chair of RecSys2013, and in various capacities in a number of top conferences such as WWW, NIPS, ICML, IJCAI, AAAI, etc.
Prof. King is Associate Dean (Education), Faculty of Engineering and Professor at the Department of Computer Science and Engineering, The Chinese University of Hong Kong. Recently, he was on leave with AT&T Labs Research, San Francisco and was also teaching Social Computing and Data Mining as a Visiting Professor at UC Berkeley. He received his B.Sc. degree in Engineering and Applied Science from California Institute of Technology, Pasadena and his M.Sc. and Ph.D. degree in Computer Science from the University of Southern California, Los Angeles.
