The 2010 KDD Cup Competition Dataset: Engaging the machine learning community in predictive learning analytics

Authors

  • John Stamper Carnegie Mellon University
  • Zachary A Pardos University of California, Berkeley

DOI:

https://doi.org/10.18608/jla.2016.32.16

Abstract

In the spring of 2010, the Association for Computing Machinery (ACM) Special Interest Group on Knowledge Discovery and Data-mining (KDD) selected a dataset from an educational technology for its annual competition. The competition, titled “Educational Data Mining Challenge”, tasked participants with predicting the correctness of student answers to questions within an Intelligent Tutoring System (ITS) from The Cognitive Tutors suite of tutors. This challenge was hosted by the PSLC DataShop, and included data provided by the Carnegie Learning Inc., producers of The Cognitive Tutors. Consisting of over 9GB of student data this was the largest KDD Cup dataset up to that point in time. The competition brought in 655 competitors submitting 3,400 solutions. Five years later, we believe the competition dataset has been the most often cited from an educational technology platform.

Author Biography

Zachary A Pardos, University of California, Berkeley

Graduate School of Education and School of Information

Assistant Professor

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Published

2016-09-17

How to Cite

Stamper, J., & Pardos, Z. A. (2016). The 2010 KDD Cup Competition Dataset: Engaging the machine learning community in predictive learning analytics. Journal of Learning Analytics, 3(2), 312-316. https://doi.org/10.18608/jla.2016.32.16

Issue

Vol. 3 No. 2 (2016): Multimodal and 21st Century Skills Learning Analytics and Datasets

Section

Special section: Dataset Descriptions for Learning Analytics

License

Copyright (c) 2016 Journal of Learning Analytics

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