2019 KDD Workshop on Deep Learning for Education (DL4Ed)

We are happy to announce that we will be organizing a half-day workshop at KDD 2019, as part of the Deep Learning Day. Details on the workshop will be updated soon. KDD 2019 will be held in Anchorage, Alaska, USA during August 4-8, 2019. See here.

Many people believe in education because of its power to maximize human potential, and transform lives; it is also a critical component of our society, since both school education and lifelong education play a central role in the development of the world’s workforce. However, compared to other applications of significant societal impact (e.g., healthcare, transportation, and social sciences), education remains a highly under-explored application field by the data mining and machine learning research communities.

Our workshop focuses on the use of deep learning to improve education; we aim at bringing together experts in the interrelated groups of machine learning, cognitive science, educational psychology, human computer interaction, and intelligent systems. In particular, we will focus on the following topics:


Relevant topics to this workshop include but are not limited to:

  • Utilizing machine learning to expand learning beyond the privileged few to remote corners of the world.

  • Using data mining to create alternatives in higher education that will prepare adults for the careers they want without the burden of excessive student debt.

  • Using data mining to help reverse the trend in K-12 of increasing spending to achieve the same learning outcomes.

  • Improving the interpretability of deep learning methods and using them to extract insights on how to improve learning outcomes.

  • Incorporating cognitive and behavioral science principles in the development of deep learning methods to improve their performance.

Tentative Schedule

The workshop will be held in the afternoon of August 5th, 2019.

13:00-13:15 Opening remarks

13:15-13:40 BI-GRU Capsule Networks for Student Answers Assessment. Nisrine Ait Khayi and Vasile Rus

13:40-14:05 Combating the Filter Bubble: Designing for Serendipity in a University Course Recommendation System. Zach Pardos and Weijie Jiang

14:05-14:30 Using Machine Learning and Genetic Algorithms to Optimize Scholarship Allocation for Student Yield. Lovenoor Aulck, Dev Nambi, and Jevin West

14:30-15:00 Coffee break

15:00-15:15 Computational Diagnostic Classification Model using Deep Feedforward Network based Semi-Supervised Learning. Kang Xue

15:15-15:30 CrossLang: The System of Cross-lingual Plagiarism Detection. Oleg Bakhteev, Alexandr Ogaltsov, Andrey Khazov, Kamil Safin, and Rita Kuznetsova

15:30-15:45 Bootstrapping a Flash Card Retrieval System Without Feedback Data. Ralph Edezhath and Jose Gonzalez-Brenes

15:45-16:45 Poster session:

16:45-17:00 Closing discussion

Call for Papers

All submissions must be in PDF format through EasyChair. Submissions are limited to a maximum of nine pages, including all content and references; shorter (at least four pages) submissions are allowed. Paper submission must be in the format specified in KDD submission direction available at: https://www.kdd.org/kdd2019/Calls/view/kdd-2019-call-for-research-papers. There is no need to anonymize your submission.

Final acceptance of a submission will be conditioned on providing a camera-ready version of the paper that fits the formatting instructions. Accepted papers will be shown on the workshop website but not be archived, thus submission does not preclude publications in other venues.

Important Dates

  • Submission Deadline: May 20, 2019
  • Acceptance Notification: June 1, 2019
  • Camera-ready Deadline: June 15, 2019
  • Workshop: August 5, 2019


  • Andrew S. Lan (University of Massachusetts Amherst)
  • Byung-Hak Kim (Udacity)
  • Richard Baraniuk (Rice University)
  • Michael Mozer (University of Colorado Boulder)
  • Jacob Whitehill (Worcester Polytechnic Institute)
Posted on March 15, 2019