Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges


  • Yukino Baba Kyoto University; RIKEN Center for AIP
  • Tomoumi Takase Hokkaido University
  • Kyohei Atarashi Hokkaido University
  • Satoshi Oyama Hokkaido University; RIKEN Center for AIP
  • Hisashi Kashima Kyoto University; RIKEN Center for AIP


Data analysis education plays an important role in accelerating the efficient use of data analysis technologies in various domains. Not only the knowledge of statistics and machine learning, but also practical skills of deploying machine learning and data analysis techniques, are required for conducting data analysis projects in the real world. Data analysis competitions, such as Kaggle, have been considered as an efficient system for learning such skills by addressing real data analysis problems. However, current data analysis competitions are not designed for educational purposes and it is not well studied how data analysis competition platforms should be designed for enhancing educational effectiveness. To answer this research question, we built, and subsequently operated an educational data analysis competition platform called University of Big Data for several years. In this paper, we present our approaches for supporting and motivating learners and the results of our case studies. We found that providing a tutorial article is beneficial for encouraging active participation of learners, and a leaderboard system allowing an unlimited number of submissions can motivate the efforts of learners. We further discuss future directions of educational data analysis competitions.




How to Cite

Baba, Y., Takase, T., Atarashi, K., Oyama, S., & Kashima, H. (2018). Data Analysis Competition Platform for Educational Purposes: Lessons Learned and Future Challenges. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). Retrieved from