IJCNN/WCCI 2016 Special Session on Smart Educational Techniques in Big Data Age


Data mining provides educational institutions the capability to explore, visualize and analyze large amounts of data in order to reveal valuable patterns in students' learning behaviors without having to resort to traditional survey methods. Turning raw data into useful information and knowledge also enables educational institutions to improve teaching and learning practices, and to facilitate the decision-making process in educational settings. Thus, it is becoming important for researchers to exploit the abundant data generated by various educational systems for enhancing teaching, learning and decision making.

In addition, the development and training of teachers in regional area can be also improved by adopting smart techniques in the big data age. How to get these tasks done smartly and effectively is another important issue that could be potentially addressed in Big data age.

To further contribute to the understanding of Smart Educational Techniques in Big Data Age, we invite original articles in relevant topics, which include but are not limited to:

  • Data mining in education
  • Learning analytics
  • "Big Data" applications and opportunities in learning and education
  • Integrating data mining and pedagogical theory
  • Data mining with emerging pedagogical environments such as educational games and MOOCs
  • Recommender systems for learning
  • Case studies in Educational Data
  • Data Driven Performance Evaluation

Submission Guidelines


Manuscripts submitted to special sessions should be done through the paper submission website of IEEE WCCI 2016. Please make sure that papers submitted to their special session clearly indicate the name of the special session the paper belongs to. All papers submitted to special sessions will be subject to the same peer-review procedure as the regular papers.

Organizers


Dr. Guandong Xu
Advanced Analytics Institute
University Technology Sydney, Australia
PO Box 123, Broadway, NSW 2007
guandong.xu@uts.edu.au

Dr. Gang Li
School of Information Technology
Deakin University, Melbourne Campus at Burwood
VIC 3125, Australia
gang.li@deakin.edu.au

Dr. Wu He
Department of Information Technology & Decision Sciences
College of Business and Public Administration
Old Dominion University, Norfolk, VA 23529
whe@odu.edu



Thanks to KDnuggets for publicity.